The Texts Matter: Essential Text Characteristics For Comprehension Intervention In The Intermediate Grades

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The Texts Matter: Essential Text Characteristics For The Texts Matter: Essential Text Characteristics For

Comprehension Intervention In The Intermediate Grades Comprehension Intervention In The Intermediate Grades

Tia Clasen

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THE TEXTS MATTER:

ESSENTIAL TEXT CHARACTERISTICS FOR COMPREHENSION INTERVENTION

IN THE INTERMEDIATE GRADES

Tia Botsford Clasen

A dissertation submitted in partial fulfillment of the requirements for the degree of

Doctorate in Education

Hamline University

St. Paul, Minnesota

2021

Dissertation Chair: Dr. Jennifer Carlson, School of Education, Hamline University

Readers:

Dr. Panayiota Kendeou, College of Education and Human Development, University of

Minnesota - Twin Cities

Dr. Kristen McMaster, College of Education and Human Development, University of Minnesota

- Twin Cities

DEDICATION

To my son, Samuel,

for your selflessness and countless sacrifices that this journey should come to fruition.

To my daughter, Alana,

For always being my inspiration to better myself.

To Mother and Jim,

Though I cannot see you, I can feel you with me, and I hope I have made you proud.

To all of my students whom I had the great fortune to teach,

Your struggles have stayed with me, your successes have launched me, and I am forever blessed

for having had the opportunity to learn from and with you.

To Dr. SueAnn Gruver,

For your mentorship, guidance, and support. Golly I wish you were here at the finish line!

To Andrea,

I know you are looking at my journey from above and saying, you can do this, girl.

Hell yeah, I could. I did it for both of us.

Finally, to my amazing and supportive husband, Scott,

For your love, patience and amazingly good food while I wrote, slept, and sometimes cursed.

I am forever grateful for you.

It was books that taught me that the things that tormented me most were the very things that

connected me with all the people who were alive, who had ever been alive.

- James Baldwin

Literacy is a tool of liberation, both personal and cultural.

-Gloria Ladson-Billings

I do believe something very magical happens when you read a book.

- J.K. Rowling

ACKNOWLEDGEMENT

A special thanks to Elly Orcutt at the University of Minnesota for her support in answering my

thousand questions.

TABLE OF CONTENTS

CHAPTER ONE: THE PROBLEM 14

Introduction to the Research Questions 14

Background of the Problem 18

Statement of the Problem 21

Research Questions 22

Context and Significance of the Research 23

Key Terms 25

Overview of Methodology 27

Limitations 29

Summary 31

CHAPTER TWO: THE LITERATURE REVIEW 32

Introduction and Significance of the Topic 32

Research Questions 34

Theoretical Framework 34

Reading Comprehension Pedagogy and Achievement in the United States 41

Informational Text as a Means to Building Content Knowledge 49

The Importance of Prior Knowledge in Reading Comprehension 51

The Acquisition of Knowledge Through Reading 55

The Role of Vocabulary Acquisition on Comprehension of Informational Texts 57

The Effects of Race, Class, and Language on Reading Comprehension and Reading

Achievement 60

The Effects of Socioeconomic Status on Reading Comprehension and Reading

Achievement 63

The Effects of Multilingualism on Reading Comprehension and Reading Achievement 67

New Literacies, Online Reading, and the Changing Nature of Reading Comprehension 72

The Role of Engagement, Motivation, and Attitude in Reading Comprehension 78

The Role of Culturally Relevant Texts on Successful Comprehension 85

Conclusion 89

CHAPTER THREE: METHODOLOGY 91

Introduction 91

Rationale for the Study 92

Research Paradigm 98

Research Setting and Participants 103

Research Setting 103

Interruption to the Research Setting 107

Overall and In-Person Student Participation in Summer Targeted Services 110

Demographics of In-Person Student Participation in Summer Targeted Services 114

Human Subject Review 115

Institutional Review Board 115

Study 1: Data Collection with Teachers To Inform Text Creation 116

Teacher Participants in the Research Study 117

Focus Group Materials 119

Natural Language Processing (NLP) Analysis of Texts 120

Focus Group Discussion 123

Study 2: Data Collection with Students To Inform Text Development 125

Student Participants in the Research Study 126

Elementary Reading Attitude Survey Data Collection 128

General Science Knowledge Data Collection 129

Data Collection on Text Reading and Paraphrasing 131

Data Analysis 136

Conclusion 140

CHAPTER FOUR: ANALYSIS AND RESULTS 142

Introduction 142

Study 1: Data Analysis To Inform Text Creation 144

Natural Language Processing (NLP) Analysis of Texts 145

Focus Group Qualitative Data Analysis 147

Analysis of the Texts Created and Used 149

Study 2: Student Data Analysis 152

Student Participant Data 155

Student Pre-Assessment Data. 157

Elementary Reading Attitude Survey (ERAS) 157

Science Pre-Assessment 163

Student Paraphrase Data 166

Student Engagement in Reading and Paraphrasing 168

Qualitative Observational Data Analysis 169

Quantitative Observational Data Analysis 176

Student Paraphrase Coding 181

Paraphrase Filter 181

Paraphrase Numerical Coding 182

Paraphrase Quality Data 183

Comparison of Paraphrase Data to Text Indices Data 191

Comparison of Paraphrase Data to Pre-Assessment Data 194

Paraphrase Data and Science Pre-Assessment Data 194

Paraphrase Data and Elementary Reading Attitude Survey Data 199

Student Perceptions of Text and Paraphrase Difficulty 203

Analysis of Text and Paraphrase Perception Data with Paraphrase Quality Data 212

Qualitative Student Interview Data 217

Conclusion 218

CHAPTER FIVE: DISCUSSION, RECOMMENDATIONS, AND IMPLICATIONS 220

Introduction 220

Discussion of the Findings 223

Essential Characteristics of Informational Texts 224

Motivation and Engagement With Digital Text 228

Student Engagement in Watching, Reading, and Paraphrasing. 228

Texts as Factors in Engagement and Motivation 230

Essential Text Characteristics in a Digital Environment 231

Diversity of Students in Grades 3 and 4 233

Delimitations to the Research Design 240

Limitations to the Research Design 242

Limitations of Study 1 243

Focus Group Work 243

Limitations of Study 2 244

The Summer Targeted Services Program. 244

Comprehension Intervention Research Focus 246

Student Participation Due to Absence 248

Researcher and Teacher 249

The Use of This Study in the Creation of the iSTART-Early Interface 240

Recommendations for Future Research 252

Implications for Classroom Practice 257

Concluding Thoughts 261

REFERENCES 264

APPENDICES

Appendix A: Teacher Focus Group Demographic Survey Responses 309

Appendix B: Indices Relevant to Reading Comprehension 310

Appendix C: Summer Targeted Services Text Data 312

Appendix D: Focus Group Initial Questions 313

Appendix E: Science Assessment (Modified from NAEP) 314

Appendix F: Student Observation Form Text Reading and Responding 316

Appendix G: Coding Table for Student Paraphrase Responses 325

Appendix H: De-Identified Student Pre-Assessment Data 326

Appendix I: Elementary Reading Attitude Survey Data 327

Appendix J: Themes from Student Observation 328

Appendix K: Student Text and Paraphrase Perception Data 330

Appendix L: Student Interview Constructed Responses 331

LIST OF TABLES

Table 3.1. District Demographics as of June, 2020 103

Table 3.2. Demographics of Third and Fourth Grade Students as of June, 2020 103

Table 3.3. Demographics of Student Participants in Summer Targeted Services 110

Table 3.4. Grade 3 and 4 Students’ Participation in On-Site Programming 111

Table 3.5. Demographics of In-Person Student Participation

in Summer Targeted Services, June 2020 113

Table 3.6. Research Study Student Participant Demographics 125

Table 4.1. Text Titles and Characteristics 145

Table 4.2. Teacher Focus Group Themes 146

Table 4.3. Components of the Coh-Metrix Text Ease and Readability Assessor

(T.E.R.A.) 148

Table 4.4. Mean Scores and Standard Deviation for

Coh-Metrix T.E.R.A. Components 150

Table 4.5. De-Identified Student Data 154

Table 4.6. Mean Recreational Reading Attitude Score Data by Gender

and Grade Level 159

Table 4.7. Mean Academic Reading Attitude Score Data by Gender

and Grade Level 160

Table 4.8. Mean Total Reading Attitude Score Data by Gender

and Grade Level 161

Table 4.9. Science Pre-Assessment Data 163

Table 4.10. Mean Science Pre-Assessment Data by Gender

and Grade Level 164

Table 4.11. Themes from Student Observations 169

Table 4.12. Engagement Indicators 175

Table 4.13. Engagement Observed in Paraphrasing Activity 177

Table 4.14. Paraphrase Filter Data 181

Table 4.15. Paraphrase Quality Data 182

Table 4.16. Paraphrase Quality Data by Text 182

Table 4.17. Paraphrase Quality Data by Student 185

Table 4.18. Paraphrase Quality Data by Gender 186

Table 4.19. Paraphrase Quality Data by Grade Level 189

Table 4.20. Paraphrase Quality Data for “A Visit to Mars” and “Wildfires 191

Table 4.21. T.E.R.A. Component Scores for “An Visit to Mars” and “Wildfires” 192

Table 4.22. Comparison of Students’ Paraphrase Quality Scores to

Science Pre-Assessment Scores 193

Table 4.23. Paraphrase Data by Science Pre-Assessment Score Percentage 194

Table 4.24. Comparison of Students’ Paraphrase Data to ERAS Scores 198

Table 4.25. Paraphrase Data by Elementary Reading Attitude Survey

Total Reading Percentile 199

Table 4.26. Text and Paraphrase Perception Data by Student and

Individual Text 203

Table 4.27. Text and Paraphrase Perception Data by Gender 209

Table 4.28. Comparison of Text and Paraphrase Perception Data to Paraphrase

Quality Data 212

LIST OF FIGURES

Figure 2.1. - Reader, Text, and Context 34

Figure 2.2. - Reader, Text, Context and Situation 36

CHAPTER ONE: THE PROBLEM

There ain’t no journey what don’t change you some.

-David Mitchell

Introduction to the Research Questions

What is one trait that humans here on Earth solely possess? Humans have very

sophisticated language skills. We are the only animal species on Earth that has a writing system.

We create text - sometimes for our own personal purposes (such as a diary), but mostly to

communicate ideas to others, which they acquire by reading. Therefore, “the writing system

matters” (Castles, Rastle, & Nation, 2018, p. 7). Reading authors’ texts is extremely important:

the amount of reading and the variety of texts in which students engage is a powerful predictor of

their future success (Sparks, Patton, & Murdoch, 2014; Cunningham & Stanovich, 2003;

Herbers, et al., 2012; Israel & Reutzel, 2017).

Comprehension - the ultimate goal of reading - is being able to both understand text and

make new meaning from it. It provides the ability to communicate across time and space and the

ability to create and share ideas in concrete and lasting form. Therefore, scaffolding and support

for comprehension early on is critical to later success as a reader and as a contributing member

of our human society. Strong readers are strong comprehenders; they read more often, and the

amount and the variety of reading in which they engage directly contributes to their academic

achievement skills and their ability to obtain a solid education (Cunningham & Stanovich, 1997;

Rapp, van den Broek, McMaster, Kendeou, & Espin, 2007; Sparks, 2014). However, many

students struggle in reading; and every year that goes by in their educational career where they

continue to struggle, a door potentially closes. Poor reading skills can lead to less motivation to

read, which may in turn lead to less time reading and less development of comprehension skills

(Cain & Oakhill, 2011; Guthrie, 2015; Troyer, Kim, Hale, Wantchekon, & Armstrong, 2019).

My interest in reading in general and comprehension in particular has been a career-long

passion. Now enjoying the 25th year of my education career, my passion for the power of

literacy is as strong as it was when I began my career. I continue to cringe when I hear students

say “I hate to read,” as reading can literally transform lives. Teaching both elementary school and

middle school, I witnessed firsthand the effects of ineffective instruction and intervention with

regard to reading comprehension, and students completely disengaged in the texts themselves.

Continuing to witness this as a district administrator compelled me to create this study which

focuses on the following question: What are the essential characteristics of informational texts

that can be used for training reading comprehension strategies in order to improve the reading

comprehension skills of diverse third and fourth grade students? I further guided this research

by further focusing on the following sub-questions:

● What are essential text characteristics (length, readability, structure, cohesion,

topics) for the selection of informational texts that can be used for teaching

reading comprehension strategies, such as paraphrasing, self-explanation,

summarization, and question asking, in a digital format?

● What are additional considerations when selecting appropriate texts for (a) a

racially and ethnically diverse population of third and fourth grade students and/or

(b) students who read below grade level?

Reading is powerful. It has provided me the ability to travel through time and through

worlds; it has offered me the opportunity to see my current world through others’ eyes. I focused,

when finally becoming a teacher, on how I could get others to love reading as much as I did, and

have been continuously learning throughout my career about literacy in general, and particularly

how people learn to read.

My love of reading is one reason why I wanted to become a teacher. I earned my

bachelor's degree in elementary education in 1995, and spent considerable time learning more

about literacy, as I knew the importance that the skill of reading had in school and outside of

school. In 2000, I earned a master’s degree in curriculum and instruction and again focused on

reading, conducting a short but in-depth action research case study on one of my eighth grade

students who was a struggling reader and had been his entire school career. Experiencing the joy

and success of reading myself, I wanted him to improve his skills in reading and to learn to love

it. Ultimately, I wrote my masters thesis on the effects of ability grouping on advanced readers,

as I believed the advanced readers were falling through the cracks, not being afforded the

opportunity to grow as in their achievement as much as they could potentially grow. They

deserved to enrich their life story as much as any other student.

I am an English teacher at heart, and deeply embrace the power of story. The story of my

journey in education - as a student, a teacher, and now as an administrator - reflects my deep

belief in and passion for education; however, my journey has not been a traditional one. When I

was in the classroom, my students often asked me, “If you could go back and do it all over again,

what would you do differently?” It was a great question, one that requires deep and continual

reflection. In 1995, at 32 years of age, with a second-grade daughter, I graduated summa cum

laude with a bachelor’s degree in elementary education after experiencing the pain and shame of

dropping out of college and spending eleven years away from learning. Although my career

started late, all of my life experiences have helped me connect to my students in ways I would

not have been able to otherwise. Being a strong reader certainly provided an avenue for me to hit

the restart button. I was able to change my world for the better.

My story reflects my conviction in strong reading skills as a way to change the world.

Students throughout my thirteen years in the classroom heard my mantra over and over again,

that knowledge is power, and much knowledge comes from reading. Friere (1970) points out that

students need to read words and the world, and teaching students to become literate means that

we must be committed to teaching them the “skills, attitudes, and commitments needed to

become citizens who will work for social justice… in the world” (Banks, 2003, p. 18). As a

teacher and now a district administrator, I have always believed in the power of literacy as a key

factor in the success of my students’ futures and, as Maxwell (2013) asked his readers to reflect

on why s/he is doing a particular study, I thought it was a good exercise to help ground my work,

so I asked it of myself. White (2017) calls out the fact that doctoral students “have a calling they

are answering” (p. 16), and in answering Maxwell’s (2013) question, I realized my calling. I

want to contribute to the body of research on reading comprehension. In order to do this,

educators must look carefully at the texts we are placing in front of our students. Not all texts are

a one-size-fits-all; our students are not a one-size-fits-all; not all tasks and environments are

exactly the same. Furthermore, our students’ lived experiences are not exactly the same; children

have been building their knowledge of language and learning before they ever begin formal

schooling (Luo, Tamis-LeMonda, & Mendelsohn, 2020). We must carefully match texts to the

task and the student. This includes the texts of new literacies, such as text messaging and

blogging, and the diverse students from all walks of life who put so much faith, everyday, in our

ability as educators.

At the culmination of this journey, I want to make my mark with something that can

change the trajectory for a child who is struggling with reading comprehension, because that

struggle can lead to a much larger struggle in learning content in other disciplines, and learning

about the world in general. I want that child’s future to be brighter, filled with more promise and

absent of as many obstacles as I can possibly eliminate. This sounds clichè, but it is anything but.

My research will provide the foundation for the development of a reading comprehension

intervention tool aimed to improve the comprehension skills of young readers. This research will

add to the body of research on matching the reader to the text and the task and will provide me

the opportunity to come to a deeper understanding of reading comprehension and the impact of

successful reading across a school career and in life, and how we are - or are not - creating

equitable experiences for students that will provide a brighter future.

Background of the Problem

The act of reading is an interaction between reader, text, and context (Anderson, Hiebert,

Scott, & Wilkinson, 1985; Hartman, Morsink, & Zheng, 2010; Kintsch, 1998; Kintsch, 2005;

Paris & Newman, 2009; Pearson & Cervetti, 2015). Strong acquisition of reading skills early on

leads not only to stronger reading achievement later on in school, but also builds other cognitive

skills, such as an increased vocabulary and content knowledge. That ongoing interaction between

reader, text and context continues to build both skill and knowledge which, in turn, can lead to

even greater success - in academics and in life (Pressley & Allington, 2015; Sparks, Patton, &

Murdoch, 2014). Reading is not just the ability to decode words; a person is literate if they can

understand the text they are reading. In our age of information, literacy is an essential skill

needed to find the most accurate information in the shortest amount of time possible in order to

problem-solve and communicate to others across the globe. Literacy is vital to the success of

global societies (Leu, 1997; Leu, et al., 2008). It is the foundation for the acquisition of

knowledge outside of one’s personal sphere of experience, for engagement within and between

cultures, and for a strong global economy. In 2018 alone, according to the World Literacy

Foundation (2018), the effects of illiteracy cost the global economy approximately $1.04 trillion,

and contributed to inequality in basic needs, such as hygiene, health, and safety. Underpinning

these alarming statistics are the names and faces of people living in poverty, incarcerated, or

exploited at least partially as a result of low literacy skills.

Although reading comprehension is vital to a student’s reading skills and a predictor of

future success, in the United States, a large number of students struggle in reading, as is

evidenced by the 2019 National Assessment of Education (NAEP) reading assessment. That

report showed that 65% of fourth graders in the United States scored below proficiency, which is

down from 2017 and statistically insignificant from results a decade ago (National Center for

Education Statistics, 2019). Further, a substantial gap continues to exist for fourth grade students

based on race and income inequality, with only the gap between White and Hispanic fourth

graders decreasing, albeit an insignificant amount (National Center for Education Statistics,

2019). The NAEP assessment, first administered in 1969 in science, writing, and citizenship, was

created to provide data on outputs in education - in other words, student learning - rather than

inputs, such as per-pupil expenditures and attendance. It was changed significantly in 1986 to

measure learning in reading, mathematics and science (National Center for Educational Sciences,

2019). The reading assessment is designed to measure students’ reading comprehension skills on

both literary (narrative) and informational texts.

As the goal of reading is to both understand and create new meaning, these statistics are

alarming, yet not new: Cunningham and Stanovich, in 2003, emphasized that the achievement

gap for nearly two-thirds of the nation’s fourth graders will continue to widen as a result of their

weak comprehension skills. These struggles can lead to a lifetime of struggle. According to the

National Center for Education Statistics, in 2019, one in five adults in the United States have low

literacy skills, which translates into approximately 43 million adults. Additionally, advancements

in technology have altered the digital landscape and continue to demand increased effective

reading skills for different texts. This study examined the essential text characteristics that can be

used to explicitly teach comprehension strategies to a diverse population of third and fourth

grade students reading below grade level and what essential text structures are needed for

comprehension strategy instruction in a digital format, thereby providing comparisons between

an offline (traditional, static printed text) format and an online (digital text) format. Additionally,

this study examined what additional considerations are needed when selecting appropriate texts

for a racially, ethnically and socioeconomically diverse population of students within a

classroom in need of reading comprehension intervention.

Statement of the Problem

Reading achievement in the United States in general, and in Minnesota specifically, has

remained stagnant over the last decade, with only one-third of fourth graders meeting grade-level

proficiency on assessments designed specifically to analyze reading trends and growth (National

Center for Education Statistics, 2019). This low level of proficiency has tremendous effects not

only on the individual reader, but collectively on global society. Further, classrooms across the

United States continue to become more diverse with regard to race, ethnicity, language, and

socio-economic status.

Technology, as well, continues to advance rapidly, with the Internet and other

technologies continually increasing in literacy worlds (Leu, Kinzer, Coiro, Castek, & Henry,

2013). With this rapidly changing technology come increased demands being made on reading

skills - skills that must be taught to be successful in the digital world of the Internet and

Information and Communication Technologies (ICTs). While studies continue to confirm the

impact of intervention on reading achievement, the what that is placed in front of students - the

texts themselves, and their essential characteristics with specific regard to comprehension

intervention - need deeper research in order to understand the role they play in the interventions.

How a person comprehends static text is not isomorphic with how they comprehend digital text;

thus we cannot utilize our same understanding of offline reading comprehension (static or printed

texts) with online reading comprehension (Dalton & Proctor, 2008; Leu, et al., 2011; Coiro,

2020). Therefore, the format of those texts placed in front of students for reading comprehension

intervention, especially with regard to an interactive, digital format versus a traditionally static

print format, is extremely important to research.

Research Questions

Due to the struggles that many students continue to face with regard to reading

comprehension, a better understanding of successful reading comprehension intervention is

needed. The purpose of this research is to identify essential text characteristics for texts that will

eventually be included in an online, automated reading strategy tutor. This tool will provide

instruction and practice designed to improve deep comprehension for a diverse population of

struggling third and fourth grade students, a set of grade levels that are a critical, yet

under-supported time of reading development. This research will guide the development of an

age-appropriate text library for informational text that is appropriate and interesting for students

in grades three and four. To that end, this mixed-methods study explores reading comprehension

and the role that texts and new literacies play in answering the central research question:

What are the essential characteristics of informational texts that can be used for

training reading comprehension strategies in order to improve the reading

comprehension skills of diverse third and fourth grade students?

This research is further guided by the following two sub-questions:

● What are essential text characteristics (length, readability, structure, cohesion,

topics) for the selection of informational texts that can be used for teaching

reading comprehension strategies, such as paraphrasing, self-explanation,

summarization, and question asking, in a digital format?

● What are additional considerations when selecting appropriate texts for (a) a

racially and ethnically diverse population of third and fourth grade students and/or

(b) students who read below grade level?

Context and Significance of the Research

The term diectic refers to a word, phrase or expression for which the meaning is

dependent upon the context in which it is used. While not a new linguistic term, it takes on new

force as digital tools and new technologies help to cement literacy as deictic in nature. “ . . . the

definition of literacy has expanded from traditional notions of reading and writing to include the

ability to learn, comprehend, and interact with technology in a meaningful way” (Selfe cited in

Coiro, 2003, p. 458).

Toward that end, my research serves as a foundational component of a larger research

study to develop an online reading strategy tutor that will help improve the reading

comprehension of students in third and fourth grade. This is a critical period of reading

development, as students are being presented with texts from which they have to learn, but have

content with which they are unfamiliar, which could lead to comprehension plateaus (Castles,

Rastle, & Nation, 2018; Goldman, Snow, & Vaughn, 2016; Guthrie, et al., 2004; Sweet & Snow,

2003). This online tool will support the strategies of comprehension monitoring, paraphrasing,

inferencing, question asking, explanation, and summarization. This tool is aimed to improve the

reading comprehension ability of students by providing individualized comprehension

instruction in a digital format during times of independent practice, as the findings from the

National Reading Panel (2000) show that the benefits of comprehension strategy instruction

begin to be shown after limited instructional time and, as Willingham (2006) explains, once the

strategy, or “trick” as he calls them (p. 39) is introduced and explained, students begin to use

them and discover they can be used in other situations (Castles, Rastle, & Nation, 2018;

Willingham, 2006). The online tutoring tool, once created, will allow students to practice what

they have learned, receiving both formative and summative feedback that is generated

automatically and immediately, which itself is part of the digital reading experience.

The tool will provide solid benefits for teachers as well. It will be easy to use and

adaptable to their curriculum - teachers will be able to load specific texts for individual students

and monitor their performance, providing more support as needed in a blended-learning format.

In addition, teachers will continue to hone their educational technology skills and knowledge.

Finally, the tool will advance the field of education’s understanding of how students learn

to comprehend, especially in a multimodal, digital format. The tool will leverage student

engagement in somewhat of a game-based format, which is an emerging field of understanding

for education (Squire, 2008; Gee, 2003; Steinkuehler, 2008), and will further inform teacher

practice, as it will provide the opportunity for teachers to choose texts that are reflective of the

individual student. This will increase student motivation as well.

Digital tools, including the vast wealth of texts easily available on the Internet, provide

the reader with a multitude of information to process in those meaningful ways - sometimes

simultaneously. For example, Strømsø, Bråten, and Samuelstuen (2003) showed that university

students who were more successful at course-end used reading strategies that helped them make

more connections across texts. The students’ skills were a culmination of a dozen or more years

of literacy instruction, practice, and assessment. In everyday life, as well, people of all ages seek

information digitally to answer questions and make sense of information. One can neither ignore

the changing face of literacy nor can we ignore those who struggle with their literacy skills. For

those students who struggle in reading, intervention on comprehension must be inclusive of the

materials with which a diverse body of students will interact on a daily basis, and must continue

to reflect how those texts, and those students, will continue to change over time. The texts matter.

Using the deictic terms today and tomorrow, increasing a student’s literacy skills today

leads to increased success tomorrow. But each today leads to a different tomorrow. As educators,

we know that what we do today influences how a student learns - and what success that student

will enjoy - tomorrow.

Key Terms

The following terms will provide clarity for the context presented throughout this study.

They are listed in alphabetical order.

Comprehension. Comprehension is defined as “the process of simultaneously extracting

and constructing meaning through interaction and involvement with written language” (Rand

Study Group, 2002, p. 11). Toward this end, a reader must decode, identify the words, and use

prior knowledge and experience to make meaning. Comprehension is constructive in nature.

New literacies. The term new literacies for the purpose of this study is defined as both

texts on the Internet and texts used as part of Information and Communication Technologies

(ICTs), and the skill needed to comprehend such texts (Leu, et al., 2011). While “new” is a

relative term, and “new literacies” was coined in or around 2008, texts today are not only

multimodal, they are deictic; therefore, the contexts continually change.

Literacy. The term literacy for the purpose of this study is defined as the ability to

identify, understand, interpret, create, communicate and compute, using printed and written

materials associated with varying contexts. Literacy involves a continuum of learning in enabling

individuals to achieve their goals, to develop their knowledge and potential, and to participate

fully in their community and wider society. Further, literacy is plural, being practiced in

particular contexts for particular purposes and using specific languages (United Nations

Educational, Scientific, and Cultural Organization, 2018).

Offline text. The term offline text refers to informational text that is printed and not in a

digital format. Such texts include trade books, magazines, newspapers, and textbooks (Coiro,

2011a).

Skill. The term skill has been used differently throughout time and across different

disciplines,including psychology and education, which has led to a lot of confusion both in

research and practice (Almasi & Fullerton, 2012; Afflerbach, Pearson, & Paris, 2008). Reading

skills are fluid and automatic, and are defined as “automatic actions that result in decoding and

comprehension with speed, efficiency, and fluency and usually occur without awareness of the

components or control involved” (Afflerbach, Pearson, & Paris, 2008, p. 368).

Strategy. The term strategy, like the term skill, has been inconsistently used in schools,

which can lead to confusion for students, teachers, and families (Afflerbach, Pearson, & Paris,

2008). A strategy is defined as “a deliberate, goal-directed attempt to control and modify the

reader’s efforts to decode text, understand words, and construct meanings of texts” (Afflerbach,

Pearson, & Paris, 2008, p. 368). We use strategies deliberately when we want to achieve a

particular goal, and in this case, the goal is comprehension of a text. A strategy differs from a

skill in that it is deliberate, rather than automatic.

The terms listed above are used universally throughout Chapters Two through Five, and it

is important to build clarity of these terms in the research. Other terms used in this study will be

defined in context as they arise in the discussion of the methodology employed, the analyses of

the data, limitations and recommendations for further study. The following section provides a

brief overview of the methodology utilized for this study.

Overview of Methodology

This research study focused on texts used in a digital comprehension intervention for

third and fourth- grade students in a small, urban Midwest public school district who are reading

below grade level and were identified by elementary school and district staff for additional

comprehension support. The student demographics in this district are quite diverse.

Approximately 40% of the elementary student body identifies as Latinx; approximately 30% of

the student body identifies as White, approximately 13% of the student body identifies as Black

Non-Hispanic; 10.4% identifies as two or more races, and the remainder of the student body

identifies as Asian, Native American, or Hawaiian/Island Pacific. The focus on third and fourth

grade students was deliberate as this is a critical time of reading comprehension development,

yet comprehension has historically been undersupported (Sparks, et al., 2014). Further, the

research was done during summer targeted services, which allowed for flexibility with regard to

time and materials for students.

This study used both Design-based implementation research (DBIR) and Mixed Methods

research. DBIR includes the active involvement of those who will ultimately be implementing

the strategy intervention which, for the purpose of this study, are both the teachers and their

students. The study used mixed-methods research as a natural continuation of DBIR. There were

two iterative cycles, the number determined based on previous findings in the qualitative

research focusing on teachers. The qualitative research employed a teacher/literacy expert focus

group, facilitated by the researcher, whose members worked on identifying the core parameters

for informational text development and selection. This group looked at informational texts

created to match science standards, and provided feedback on their appropriate use with third

and fourth grade students. The second part of the qualitative research focused on student

observation with texts and a short interview with all students who participated in the research.

The quantitative research was two-phased.

In the first phase, a focus group of teachers/literacy specialists was convened to focus on

parameters for informational text development and selection. The group helped to formulate the

parameters that encapsulated the essential characteristics of informational texts. This included,

but was not limited to, such characteristics as content, themes, the interests of the students, and

the developmental appropriateness of such texts with regard to third and fourth grade readers.

The feedback was both qualitative and quantifiable with regard to appropriate use.

The second phase involved a quasi-experiment where the texts were evaluated for

appropriateness by students in grades 3 and 4. Students were asked to read subsets of the texts

developed and engaged in paraphrasing, a strategy that has shown to be an effective

comprehension strategy (Hagaman & Casey, 2016; Hagaman, Casey, & Reid, 2016; Hagaman,

Casey, & Reid, 2012; Kletzien, 2009). Raters scored the level of the students’ responses. The

researcher observed the students as they were interacting with the texts and typing their

paraphrases. After each text, students were to rate the text on interest and ease, and to rate the

paraphrasing activity on interest and ease. Finally, the researcher interviewed the students to

ascertain whether they could remember how to paraphrase and if they thought paraphrasing

helped them become a better reader. As with any research study, there were limitations, which

will be outlined in the next section.

Limitations

The spring and summer of 2020 was unlike any other in recent history. The United States

found itself in the middle of the coronavirus pandemic, and public schools across the nation had

to quickly shift to remote, or distance, learning. This shift in Minnesota took place in early

March of 2020. The district in which this study took place began distance learning on April 5,

2020, the Monday after its spring break. The pandemic continued, and schools were unable to

open for the rest of the school year. However, districts had a bit more leeway with regard to their

summer targeted services structure, albeit adhering to strict social distancing and state mask

policies.

The district in which this study took place revised its plans for summer targeted services

programming. Many families in the district had limited access to digital technology; many

families had unreliable access to the Internet access and many had no access to the Internet

during the time of the full distance learning. Further, elementary students had a hard time

engaging with on-screen learning even if access was not an issue. Therefore, families of

elementary students recommended for summer targeted services were given the option to send

their students in person to school, or participate in summer programming remotely (distance

learning). While much more equitable, this choice limited the number of students who would

participate in this study; 121 of the 255 elementary students registered for summer targeted

services, or 47.5%, opted for in-person learning, which is less than half of the total elementary

students enrolled. From that pool of 121 students, 17 dropped; either they never attended or

stopped attending and were dropped from the roster once the summer targeted services program

began.

This study focused on students in grades 3 and 4. Summer targeted services enrollment

for these grades was as follows:

● Grade 3: of the 33 total students registered, four dropped, and 14 of 29 remaining

participated on site, for a 48.3% on-site participation

● Grade 4: of the 55 total students registered, 11 dropped, and 18 of 44 remaining

participated on site, for a 40.9% on-site participation

Shulman (1999) states, “Research on educational practice is inherently consequential. It

is often cross-cultural, carried on when the social class, language, ethnicity, or commitments of

those conducting the research are incongruent with those whom they study” (p. 165). I, as a

White, middle class, native English-speaking educator may not look like my students, or have

the same home language as them, or many of the same life experiences as them. I recognize that

and am committed to changing the trajectory of the narrative.

Summary

Because the act of reading is an interaction between reader, text, and context (Anderson,

Hiebert, Scott, & Wilkinson, 1985; Hartman, Morsink, & Zheng, 2010; Kintsch, 1998; Kintsch,

2005; Paris & Newman, 2009; Pearson & Cervetti, 2015), it was important for me as a researcher

to observe students interacting with the text. A data point (such as a score on an assessment) is

one piece of evidence; a better understanding of the origin of that data point comes from the

students themselves. More engaged readers are more motivated, have higher reading

self-efficacy, and tend to utilize strategies to continue comprehending the text (Castles, Rastle, &

Nation, 2018; Massey & Miller, 2017; Wigfield, et al., 2008; Willingham, 2017). Further, it is

important to understand the interactions and experiences a diverse body of students have with

texts, in order to provide the best texts possible in a reading comprehension intervention. The

role of engagement and motivation is found to be a greater problem for students of color, for

whom dropout rates are the highest (Fredricks, Blumenfeld, & Paris, 2004; Rumberger, 1987;

Rumberger, 1995). The texts, indeed, matter.

Chapter Two further explores the literature on reading comprehension, the changing face

of literacy with regard to online texts, and the engagement of diverse populations of students in

the act of making and creating meaning through reading.

CHAPTER TWO: THE LITERATURE REVIEW

You don’t have to burn books to destroy a culture. Just get people to stop reading them.

- Ray Bradbury

Introduction and Significance of the Topic

The ability to comprehend at high levels continues to be considered an extremely

important skill, both in school and throughout one’s life. It provides the opportunity for social

empowerment, the creation of more equitable aspects of learning, community, work, and

personal life, leading to a better life for everyone, especially those who are the least advantaged

(Coiro, 2020; Leu, et al, 2015). Therefore, it is imperative that we raise the reading achievement

of every student. For the purposes of this study, reading comprehension is defined using the

RAND Reading Group Study (2002) definition: “the process of simultaneously extracting and

constructing meaning through interaction and involvement with written language” (p. 11).

However, the scope of what is read has been shifting from solely on traditional paper pages

(offline) to both offline and digital formats, whether online or on an e-reader or other electronic

device (Goldman, Braasch, Wiley, Graesser, & Brodowinska, 2012; Hartman, Morsink & Zheng,

2010; H. J. Kaiser Family Foundation, 2010). Both formats must be included in a

comprehensive, evidence-based system of early intervention designed to ensure struggling

readers read and comprehend at levels commensurate with their successful grade level peers, and

that all readers, regardless of ability, continue to grow their reading prowess.

This review of the literature explored what is known about the complex skill of reading

comprehension and how that knowledge has continued to expand over the years. Specifically, it

explored the interaction of student, text, context, and environment, as every reading experience

uniquely involves a person, a text, and a purpose. The text itself, and its characteristics, is the

main factor we as researchers and educators have control over; it is our responsibility to ensure

every text placed in front of a student optimizes the interaction they have with that text to

improve reading comprehension. To that end, this literature review focused on the role of

informational text in successful reading comprehension with regard to building knowledge. Next,

the role that culture, socioeconomic status, and language play in reading achievement in the

elementary grades was examined as it intersects with successful reading comprehension and

reading achievement. Further, this review explored the literature on how students interact with

texts in a digital format and what that interaction means for students who struggle in reading.

With a focus on intervention for struggling third and fourth grade readers, an identified critical

time in the acquisition of reading skills (Feister, 2010; Goldman, Snow, & Vaughn, 2016; Sweet

& Snow, 2003), this review next explored new literacies and their implication on the changing

nature of reading comprehension, including new skills and strategies that are needed to read

successfully in a digital world. The chapter closes with a review of literature that explored the

role that motivation and engagement have with regard to reading comprehension in the

elementary grades.

Research Questions

The main research question of this study focused on identifying and optimizing the text

factor in the reader-text-context interaction: What are the essential characteristics of

informational texts that can be used for training reading comprehension strategies in order to

improve the reading comprehension skills of diverse third and fourth grade students? As the

nature of texts continually change in a digital world, the question was further guided by the

following sub-questions:

What are essential text characteristics (length, readability, structure, cohesion, topics) for

the selection of informational texts that can be used for teaching reading comprehension

strategies, such as paraphrasing, self-explanation, summarization, and question asking in a digital

format?

Because comprehension is a process that is an interaction between reader, text, and

context, the research question was also guided by the following second sub-question:

What are additional considerations when selecting appropriate texts for (a) a racially and

ethnically diverse population of third and fourth grade students, and/or (b) students who read

below grade level?

Theoretical Framework

Researchers, policy makers, and educators have spent the better part of six decades trying

to improve the reading achievement of students in the United States, during both literacy-specific

instructional time at the elementary level and during instruction in specific content areas at the

secondary level. There have been major shifts in thinking about reading comprehension,

especially in the last 55 years, but overall there have been three major factors considered

throughout all of it: the reader, the text, and context (Fox & Alexander, 2017; Pardo, 2004;

Pearson & Cervetti, 2015; RAND Reading Study Group, 2002). This interaction of those three

factors, and the resulting reading comprehension, is illustrated in Figure 2.1. Throughout the 55

years that were explored for the purposes of this study, different periods of time had a different

major focus on one of those factors as the most important factor accounting for successful

comprehension, and thus different theoretical models were created.

Figure 2.1

Reader, Text, and Context

In the 1950s and 1960s, models of reading comprehension were more text-centric; in the

1970s, the models tended to be more reader-focused. The decade of the 1980s brought with it

arguments between those who wanted the emphasis to be on bottom-up processes (decoding),

and top-down processes (language comprehension), giving rise to the ‘reading wars’ - phonics

versus whole language instruction. The simple view of reading (SVR) provided some clarity

about these two core components and their interrelation. Gough and Tumner (1986) illustrated

SVR with a mathematical equation; the SVR posits that reading (R) equals the product of

decoding (D) and comprehension (C), or R=DxC. The simple view of reading can be useful in

understanding that in order to become a skilled reading comprehender, neither decoding nor

linguistic comprehension (which differs from reading comprehension in that it encompasses

listening and language comprehension) is sufficient by itself. It takes both the skill of decoding

and the skill of language comprehension to become a skilled comprehender of written text.

However, reading (R) is much more complex than the simple view can represent. Reading

comprehension is the interplay of the cognitive processes of the reader on the text itself,

including the text features, the background knowledge of the reader, and the goals and purposes

for reading a particular text (Castles, Rastle, & Nation, 2018). As a result, the late 1980s and

beyond brought a greater focus on context (Pearson & Cervetti, 2015).

More recently, the element of context has been expanded to include the situation, which

is more of a sociocultural element and includes time, place and purpose of the act of reading,

which could include the stated or implied task for reading (Fox & Alexander, 2017; Hartman,

Morskin, & Zheng, 2010). This updated interaction can be seen in Figure 2.2. The characteristics

of all of these elements (text, reader, context, and situation) all interact, thus affecting the process

of comprehension. Important characteristics of the reader can include motivation, mood,

self-efficacy with reading skills, and content knowledge. Characteristics of the text could include

complexity, the content of the text, the genre of the text, even the font. Characteristics of context

could include the activity or task, such as finding evidence to support a main idea or evaluating

an argument, or a nurturing reading environment. Finally, characteristics of situation as part of

context could include a high-stakes testing situation, reading for pleasure, working with a

partner, interrogating the text for absent narratives, engaging in game-based literacy, or making

use of background knowledge to build understanding. Reading comprehension, as Castles,

Rastle, and Nation (2018) illustrate, is multi-dimensional, multi-faceted, and encompasses a

range of processes which are dependent upon many variables (p. 8).

Figure 2.2

Reader, Text, Context, and Situation

The theoretical framework for this study is guided by the construction-integration (C-I;

Kinstch & van Dijk, 1978; Kintsch, 1983; Snow, 2002) model of comprehension that provides a

more individualized understanding of reading comprehension, such as variance by age, skill,

format, and life experience (Fox & Alexander, 2017; Israel & Reutzel, 2017; Kintsch, 1998;

Paris & Hamilton, 2005). The C-I model provides a more balanced view of reader and text in

comparison with earlier models of reading comprehension, and also provides an extremely

important focus on context, which can be thought of as “a filter through which people perceive

the world” (Kintsch, 1988, p. 1). Further, as Pearson and Cervetti (2015) pointed out, this model

illustrates the current dominant model of comprehension in the literature today.

The C-I model views readers as active meaning-makers who are creating “mental

representations of texts” (Castles, Rastle, & Nation, 2018; Pearson & Cervetti, 2015; van den

Broek, 2010). To comprehend a text does not necessarily mean that a person regurgitates

verbatim what was read; the meaning is created by forming what is known as a situation model

(Kintsch, 1998) which continues to grow as the reader continues to read, and culminates with a

rich understanding of the text that goes beyond simply what was actually stated in the text

(Castles, Rastle, & Nation, 2018; Pearson & Cervetti, 2015). Simply put, the reader is making

their individualized meaning from the text, based on the actual words in the text but also using

the reader’s own background knowledge or prior experiences, including but not limited to rules

of grammar, knowledge of events, specific vocabulary, past experience, even emotions. This can

explain why, even though a reader may have loathed Cold Mountain (1997), the novel won the

Pulitzer Prize for Literature.

The construction-integration model uses both the bottom-up processes, which begin with

foundational skills needed for decoding (Angosto, Sánchez, Álvarez, Cuevas, & León, 2013),

and top-down processes, which involve larger chunks of text, prior knowledge, and memory,

guiding comprehension. Both are an integral part of comprehension, which is highly interactive

(Kintsch, 2005). Further, this model is used to explain how a reader tackles text: If the reader is a

fluent reader of the particular text, fewer strategies are needed. The reader is actively

constructing meaning, using the words on the page and their prior knowledge through such

critical skills as inference. However, even proficient adult readers come to words they do not

know in their own reading, or read a passage that is difficult and does not make sense, but as

Goodman, Goodman, and Allen (2017) point out, “proficient readers are more flexible in their

use of language knowledge and reading strategies than are less proficient readers” (p. 89). At the

point of struggle is when adept readers utilize strategies, such as re-reading. Kintsch (2005)

states, “only when the normal flow of comprehension breaks down does strategic problem

solving take over” (p. 126). Therefore, both skills and strategies are needed for successful

comprehension.

Because the landscape of reading and the resulting reading comprehension skills required

to traverse that landscape continue to evolve with continually changing technologies, the

construction-integration model of reading comprehension allows for the rapidly changing

construct of new literacies and the theories surrounding it. The construction-integration model of

reading comprehension values the individual meaning-making based on the format of the text,

the environment in which the text is being read, the purpose for reading the text and the reader’s

prior knowledge and experiences. Therefore, the C-I model can embrace the new literacies that

are part and parcel of our lives and help researchers and practitioners recognize that changes to

literacy are taking place at many levels (Leu, et al., 2013) and that we must prepare our students

through sound pedagogy. By understanding that comprehension is personal and individual, and

understanding that new literacies allow for readers to forge their own paths through various

linked texts, the construction-integration model of reading comprehension provides the space

needed for exploration of this new horizon of reader, text, context, and situation within a digital

world of reading intervention.

This review of literature began with research on reading comprehension instruction in the

United States, and discusses the resulting elementary student achievement in reading. Literacy,

specifically the component of reading under the literacy umbrella, continues to evolve as the

context and situation in which one reads continues to evolve (Hartman, et al., 2010; Leu, et al.,

2015; Leu, et al., 2013). This review of literature, therefore, explored several important facets

with regard to context and situation. First, research on reading as building content knowledge

was explored, especially as it relates to the intermediate grades in elementary school, when

students are increasingly exposed to expository texts and expected to comprehend them

successfully as a way to learn new content. Next, a deeper understanding of the similarities and

differences of online versus offline reading comprehension was warranted and further explored.

Additionally, this review of the literature focused on the role that motivation to read and

engagement of the reader play in successful reading comprehension, with regard to the content

and the format of the texts.

Finally, this literature review explored the additional considerations of culture and when

choosing texts for a diverse group of readers, especially those who struggle in reading for various

reasons, and whose achievement has led to an achievement gap in reading between them and

their majority group, grade-level peers. Before discussing the review of literature focusing on

context and situation, however, a review of the literature on comprehension pedagogy and

reading achievement in the United States provided foundational context for why this research

study took place.

Reading Comprehension Pedagogy and Achievement in the United States

Historically, reading comprehension had been framed as an interaction between reader

and text (Anderson, Hiebert, Scott, & Wilkinson, 1985; Hartman, Morsink, & Zheng, 2010;

Pearson & Cervetti, 2015), and also the interaction between the reader, the text that has been

written, and what is happening at that moment in time (Almasi & Fullerton, 2012; Butcher &

Kintsch, 2003; Pardo, 2004; Pearson & Cervetti, 2015; Snow, 2002). Hence, reading

comprehension is an extremely complex process, which can be mostly indirectly observed

(Johnston, 1984; Pearson & Cervetti, 2017). Continued creation of new technologies, however,

have forwarded the progress of understanding of reading comprehension through such new

technologies as eye movement photography, which are beginning to advance the opportunities

for real-time observation of the human mind (Castles, Rastle, & Nation, 2018; Israel & Reutzel,

2017; Shotter & Raynor, 2015). And, outside of those new technologies and infancy of new

understandings of how the mind works, there have historically been many definitions of

comprehension in the United States, and many periods of time in which the definition has had

little consensus (Paris & Hamilton; 2009). These varying definitions and periods lacking

consensus have affected the body of research on reading comprehension, leading to

wide-reaching implications, both for reading comprehension instruction and assessment, and the

creation of federal literacy policies in the United States (Kapinus & Long, 2015; Pearson, 2007;

Sarroub & Pearson, 1998). Those federal policies, in turn, have had far-reaching ramifications on

research on education in general, and reading comprehension in particular which, again, affect

reading comprehension instruction and assessment (Buly & Valencia, 2003; Durkin, 1978).

The review of the literature for this study constructed a synthesis of the past 55 years of

reading comprehension instruction. It focused on literacy reform, beginning with the Elementary

and Secondary Education Act (ESEA) of 1965, providing a contemporary focus on where we are

in the United States with regard to our students’ ability to comprehend visual/written texts. This

55-year period witnessed serious shifts in the way educators and researchers think about

processes and implications of reading comprehension for both educational and policy purposes.

These implications have had a strong impact on districts, schools, teachers and students (Pearson

& Cervetti, 2015) in such areas as assessment, intervention, evaluation, and even funding.

The Elementary and Secondary Education Act created national policy which shaped how

students in high poverty settings, and those whose first language was not English, were to be

educated (Kapinus & Long, 2015; Spring, 2017). This policy led to a focus on assessment. The

first National Assessment of Education Progress (NAEP), also known as The Nation’s Report

Card, which was created in 1968, analyzed trend data in order to address the needs of students

who were not achieving at adequate levels in schools as they existed (Lagemann, 2000). The

NAEP framework utilizes both narrative and informational texts in its assessment of reading

comprehension, recognizing that while some reading behaviors are text-agnostic, other reading

behaviors can vary based on the text with which the individual student interacts (National

Assessment Governing Board, 2019). The NAEP data showed that, from 1971 to 1999, average

reading scores of 9-year olds and 13-year olds grew only four points, from 208 to 212 and from

255 to 259, respectively; and average reading scores of 17-year olds grew three points, from 285

to 288 (National Center for Education Statistics, 2015). The NAEP framework for reading has

evolved over the years. The current framework used is from 2009; although there was an

opportunity for a new framework to be developed in 2019, one is just now being created. The

nation continues to use the 2009 framework, although students have been accessing that

assessment on an online platform since 2017 (National Assessment Governing Board, 2019).

Prior to the 1970s, the term literacy was not used in the formal, academic way it is today.

Lankshear and Knobel (2011) stated that reading, at that time, was a vehicle to get to the more

important “business of school learning” (p. 3), while the term literacy was relegated to informal

teaching of reading to more marginalized populations of adults who were illiterate as a result of

what was then termed “debilitating or dysfunctional conditions and circumstances” (p. 3).

Furthermore, as with the term comprehension, literacy has had varying agreement on a definition

and continually changes (Hillerich, 1976; Turnbill, 2002). For the purposes of this study, literacy

is defined as “the ability to identify, understand, interpret, create, communicate and compute,

using printed and written materials associated with varying contexts. Literacy involves a

continuum of learning in enabling individuals to achieve their goals, to develop their knowledge

and potential, and to participate fully in their community and wider society” (UNESCO, 2018).

In other words, a literate person uses reading, writing, speaking, listening, and thinking in order

to make sense of, learn, and create new meaning. Reading comprehension is a critically essential

component of literacy and, as such, it is imperative that research informs strong and explicit

teaching of reading comprehension.

Dolores Durkin, in 1978, published an iconic study focused on reading comprehension

instruction. She undertook this study because, in her observations of elementary school

instruction, she found almost no comprehension instruction taking place. She was compelled to

begin this study as a result of the National Institute of Education (NIE) completing a Request for

Proposal (RFP) outlining the need for a “Center for the Study of Reading whose central concern

would be comprehension” (Durkin, 1978, p. 483), outling an assumption that comprehension

instruction was, in fact, taking place. Durkin’s purpose for the study was to ascertain whether

elementary classrooms were providing comprehension instruction and, if so, how much time was

being allocated to that instruction, especially in the middle and upper elementary grades. Her

study revealed little attention to vocabulary and analysis of text structure, and an overwhelming

reliance on workbooks and assignment sheets both during the reading block and social studies

instructional time. In fourth grade, in particular, Durkin found that a fourth grade teacher was

“clearly an assignment giver, not an instructor” (Durkin, 1978, p. 505). Further, with regard to

informational text found in social studies and science content, “teaching children to be better

readers of content subject textbooks never entered into any of the observed activities” (Durkin,

1978, p. 520). Durkin recommended more “observational studies” and identification of practices

that lead to students becoming better readers.

Yet, reading scores continued to stay flat, as the NAEP trend scores illustrate. Due in part

to the relatively stagnant scores, Congress convened the National Reading Panel in 1997, and the

Panel submitted its iconic report, Teaching Children to Read: An Evidence-Based Assessment of

the Scientific Research Literature on Reading and its Implications for Reading Instruction to

Congress in 1999 (National Reading Panel & National Institute of Child Health and Human

Development, 2000). Neither the Panel itself nor the report were without their critics, but both

reported positive results for five of six “strategies” studied (Yatvin, 2003). Those strategies,

while never being identified as the essential strategies in the report, subsequently became known

as the Five Pillars of Reading. They are: phonemic awareness, phonics, fluency, comprehension,

and vocabulary, with comprehension being identified as the “essence” of reading (p. NRP, 2000,

p. 228).

Comprehension is identified as a critical and multidimensional component of learning in

general, and a strong predictor of later learning success because learning, especially in a school

setting, is largely derived from what students read (Cunningham & Stanovich, 2003; Herbers, et

al., 2012, Israel & Reutzel, 2017; Kendeou & O’Brien, 2016; Sparks, Patton & Murdoch, 2014).

However, despite the critical nature of strong reading comprehension skills, elementary readers

have historically acquired active comprehension strategies more informally (NRP, 2000, p. 232).

Early literacy instruction, in kindergarten and grade one especially, is mostly focused on the first

two pillars: phonemic awareness and phonics (Buly & Valencia, 2003; Duke, 2000; Durkin,

1978; Paris & Hamilton, 2009). The skills that encompass these two pillars precede the ability to

decode, which is a skill necessary for comprehension of written text, and many researchers have

focused their studies on the necessity and importance of decoding skills (for reviews, Castles,

Rastle, & Nation, 2020; Snowling & Hulme, 2005; Storch & Whitehurst, 2002).

Systematic phonics instruction, especially when implemented early (prior to first grade),

can improve decoding, spelling, and comprehension (Castles, Rastle & Nation, 2020). However,

while necessary, decoding is not the single skill needed for reading comprehension (Nation,

2005; Paris & Hamilton, 2009). Comprehension skills are essential for the creation of meaning

from text, and both decoding skills and comprehension skills contribute significantly to reading

comprehension performance (Kendeou, et al., 2009; Shanahan & Shanahan, 2008; Storch &

Whitehurst, 2002). Buly and Valencia outlined in their 2003 paper cautions and considerations

for state policy, and emphasized that the high-stakes tests utilized by states for educational

accountability purposes focus on comprehension, yet the stagnant achievement results suggest

“there is little data to suggest that working with early readers primarily on decoding will lead to

increased reading performance of comprehension when those readers are tested in the 4th grade”

(p. 6). Williams (2015) pointed out that the instructional activities teachers take advantage of in

teaching phonemic awareness and phonics involve little emphasis on comprehension, especially

with and of informational and expository texts.

Yet, even in the primary grades, teachers can make use of rich texts and model think-

alouds and other instructional strategies to begin building the background knowledge - in

comprehension skills and strategies as well as in general information knowledge - that students

will learn more fully as they matriculate through elementary school. Students become more

cognitively developmentally ready in third and fourth grade to improve such higher-order skills

as the use of comprehension strategies (Del Giudice, 2014; Del Giudice, 2018; Pearson &

Billman, 2016). Furthermore, expository and informational texts are replete with “timeless verb

constructions...generic noun constructions…[certain] text structures...and graphical elements,

such as diagrams” (Duke, 2000, p. 205) - all essential text components that, when learned to

navigate successfully, lead to strong reading comprehension later because, as McNamara, Ozuru,

and Floyd (2011) emphasize, using knowledge to comprehend depends in part on the text genre

and text features. The types of texts chosen for skill instruction are important; the youngest

readers can be immersed in a wide variety of both narrative and informative texts which, when

used to teach foundational reading skills, can also tap into the multidimensional processes of

reading comprehension needed to understand written information. Additionally, use of such texts

will provide much needed background knowledge as students get older.

Beginning in fourth grade, the use of informational texts increases as students are

expected to use these texts in order to learn in content areas such as science and social studies

(Jeong, Gaffney, & Choi, 2010; Ness, 2011). Yet these texts may present unfamiliar information

in complex structures, including language and vocabulary. Additionally, these texts often require

more demanding processing skills because of their increasingly complex structure, and they

require more complex strategies in order to comprehend, such as inference, summarization,

analysis, and metacognition, which is the evaluation of one’s understanding of what was read

(McNamara, Ozuru, & Floyd, 2011; Santoro, Baker, Fien, Smith, & Chard, 2016). Furthermore,

the issue may be exacerbated as students matriculate through the grade levels. Greenleaf and

Valencia (2016) discovered that “the vast majority of high school students in the diverse, urban

settings where [they] worked had problems with comprehension, not decoding, of the texts they

might encounter in school” (p. 237). Their study illustrated that students were woefully

inexperienced with the more complex text types and structures, and had inadequate prior

knowledge needed to comprehend those texts. Yet students, even those as young as first grade,

can learn to read while they read to learn, utilizing reading comprehension strategies, which are

higher-order processes and skills, to aid word reading skills such as decoding, which are

lower-order processes and skills (Castles, Rastle, & Nation, 2018; Landi, 2009; Perfetti & Hart,

2001). Sound explicit reading or meaning-making instruction, such as posing questions; teaching

prediction, inference and paraphrasing skills; and synthesizing as students read a text, may help

students build meaning and promote their word skills (McKeown, Beck, & Blake, 2009; Pearson

& Billman, 2016). Doing so at an early age will help students, who are interacting with

increasingly complex text as they matriculate through the grades, be successful in their learning.

This study was conducted in a very diverse school district in suburban Minnesota;

therefore, an analysis of students’ reading achievement in Minnesota specifically was warranted.

Minnesota historically enjoyed a higher than average achievement on the NAEP assessment in

comparison to the nation. However, Minnesota has also had one of the largest achievement gaps

in the nation. Therefore, for the purposes of this study, which was situated in the state of

Minnesota, an analysis was warranted of recent NAEP results for the state. In looking at the 2019

achievement results of fourth graders for Minnesota specifically, 39% of students achieved

proficiency or above in fourth grade reading, which is not statistically significant from the

nation’s average of 35%, and the scores are slightly down from 2017 (National Center for

Education Statistics, 2019). Although the Minnesota Department of Education believes in

“striving for excellence, equity, and opportunity” (Minnesota Department of Education, 2020),

Minnesota ranked 12th in fourth grade reading achievement in 2019 which, while being a

relatively consistent ranking overall for the state since 2003, is well below its ranking of fifth in

2002 (National Center for Education Statistics, 2019). Therefore, the challenges with reading

comprehension that have plagued our schools nationwide are the same challenges that have

plagued Minnesota for some time.

Currently, all state, national and international assessments employ online tools for

assessing offline literacy skills - those skills traditionally used by students when reading print

material. The digital age in which we interact, and the increased ability to access information

anywhere, anytime, has strong implications for knowledge acquisition in general, and reading

comprehension skills specifically, due to myriad opportunities for interacting with new and

diverse text formats and information that one may not have previously encountered. While new

learning opportunities are beneficial, they also present new challenges (Coiro, 2020; Coiro,

2011a; Goldman, Snow, & Vaughn, 2016). Students must not only be able to adeptly navigate

new text formats, they must also continually build their knowledge of increasingly complex

information and content, which occurs with successful comprehension of any text, no matter the

format.

Informational Text as a Means to Building Content Knowledge

This study focuses on comprehension as it relates to informational text through the

answering of the following questions:

What are the essential characteristics of informational texts that can be used for

training reading comprehension strategies in order to improve the reading

comprehension skills of diverse third and fourth grade students?

The research is further guided by the following two sub-questions:

● What are essential text characteristics (length, readability, structure, cohesion,

topics) for the selection of informational texts that can be used for teaching

reading comprehension strategies, such as paraphrasing, self-explanation,

summarization, and question asking, in a digital format?

● What are additional considerations when selecting appropriate texts for (a) a

racially and ethnically diverse population of third and fourth grade students and/or

(b) students who read below grade level?

It was imperative, therefore, to review the body of literature on informational text as a means to

build both content and world knowledge, to understand the importance of the role of prior

knowledge, and to both understand the role vocabulary plays in successful reading

comprehension.

By the time students are in third and fourth grade, they are at an extremely important

stage in their reading development, as the proportion of informational text to narrative text has

sharply increased from the primary grades to the intermediate grades, especially beginning in

grades 3 and 4 (Gaffney & Choi, 2010; McNamara, et al., 2011; Mol & Bus, 2011), and the

knowledge gained from reading informational text contributes greatly to comprehension

(McNamara, et al., 2011). However, the amount of time spent in reading instruction using

informational text is extremely small (Beerwinkle & Duke, 2000; Jeong, et al., 2010; Simpson,

1996; Strong, 2020; Wijekumar, Walpole, & Aguis, 2018), and the instructional activities used

with informational text do not require deep comprehension, such as completing a worksheet with

low level questions and activities like fill-in-the-blank or matching activities (Duke, 2000;

Gaffney & Choi, 2010). In addition, the genre of informational or expository text has structures

that differ widely from narrative texts, and comprehension is influenced by the text structure that

is utilized to convey the information (Kendeou & Van den Broeck, 2007; McNamara, et al.,

2011). This section provides the rationale behind the urgency to use informational text more

frequently and with increased rigor, both by the teacher in their instructional practices, and by the

learner in the types of learning in which they are asked to engage. Prior knowledge, how it is

acquired through the act of reading, and the role of vocabulary acquisition was explored as it

relates to successful reading comprehension, particularly of informational text.

The Importance of Prior Knowledge in Reading Comprehension

Prior knowledge plays a pivotal role in reading comprehension and in content learning,

because people learn things from what they read, and they apply that knowledge to new texts in

order to comprehend them (Afflerbach, 1990; Wharton-McDonald & Erickson, 2017). Because

reading is both an iterative and interactive process, the knowledge and experience a person has

and continues to gain helps to build new knowledge and new sense-making (Goodman, et al.,

2017; Kendeou & O’Brien, 2017; Kendeou & O’Brien, 2016; Pearson & Billman, 2016; Rupley,

1975; Willingham, 2017; Willingham, 2006). The greater the background knowledge, the more a

student is able to draw on it as they read, and the more profound the effects on reading

comprehension (Afflerbach, 1990; Castles, Rastle & Nation, 2018; Kendeou & O’Brien, 2016;

Oakhill, Cain, & Bryant, 2003; Pearson & Billman, 2016; Wharton-McDonald & Erickson,

2017; Willingham, 2017; Willingham, 2006). The research has shown that when a person is

reading and can make connections to the text from existing knowledge they have on a subject,

comprehension is enhanced (Afflerbach, 1990; Castles, Rastle, & Nation, 2018; Kendeou,

McMaster, & Christ, 2016; Kendeou & O’Brien, 2016; Spilich, Vesonder, Chiesi, & Voss, 1979).

The more comprehension is enhanced, the more the student is learning, and this new learning

contributes to a student’s body of knowledge. This cycle of continuous improvement can have

far-reaching effects on the successful achievement of students. Indeed, it is essential, for as

students matriculate through the grades, they must grapple with more complex, nuanced, and

challenging texts that require analyzing, interrogating, and synthesizing information found in and

across texts (Duhaylongsod, Snow, Selman, & Donovan, 2015; Moje, 2008; Shanahan &

Shanahan, 2008; Wharton-McDonald & Erickson, 2017).

Prior knowledge is not limited to information about a subject. Lipson (1982) stated that

“verbal knowledge, knowledge of text structure, knowledge about social interaction and human

intentionality, and knowledge of causal relations” (p. 244) are all prior knowledge structures,

along with prior world knowledge, and a reader brings these prior knowledge structures to any

new reading task. In her 2000 study on informational text, Nell Duke attended not only to the

contexts and intended audiences of texts, but to “specific linguistic features of text” (p. 205),

including grammatical constructions, graphical elements, definitions, and specific text structures,

such as comparative/contrastive and cause/effect structures. Further, she argued that a person

learns how to read a particular genre, like informational text, through experience with that genre,

and that this genre development can, and should, begin early on in a child’s life (pp. 206-207).

Doing so provides children with the opportunity to not only learn from informational and

expository texts, but to learn about them as well, including the structures and vocabulary

contained within them. This exposure builds the knowledge base needed to navigate the

increasingly complex texts that are used to teach content as students progress through the grades.

Prior knowledge also includes domain-specific vocabulary, such as the term birdie in

golf. Research continually shows the importance of academic vocabulary to the successful

navigation of informational, domain-specific, or content-specific texts in an academic setting

(Bailey & Heritage, 2008; Nagy, Townsend, Lesaux, & Schmitt, 2012). A person who is

navigating a text with domain-specific vocabulary with which they are familiar spends less

cognitive load determining the meaning of such words - which, as is the case with the golf term

birdie could have multiple meanings depending upon the topic - and more of a cognitive load

comprehending the text deeply, including such higher-order and cognitively complex skills as

determining main idea and author’s purpose, and determining the importance of details

(Afflerbach, 1990). In school, many words are discipline-specific, such as cytoplasm,

polynomial, or federalism, and understanding them within the context of reading is crucial to

meaning-making and comprehension (Nagy, et. al, 2012). A student who has great interest in

history may already have a strong understanding of the term federalism and will have an easier

time comprehending a text focusing on that concept.

It is not just the amount of prior knowledge a person has that is important; it is also the

quality of the prior knowledge that determines successful reading comprehension (Goodman, et

al., 2017; Kendeou & O’Brien, 2016). When reading a text, a person is continually using

previous knowledge to confirm or disconfirm information being presented in the text, whether

presented explicitly or implicitly. If presented implicitly, the reader must rely on inferential

processes to confirm or refute the information presented. Thus, a reader can create inaccurate

meaning from the text and will ultimately rely on inaccurate prior knowledge in future contextual

situations (Kendeou & O’Brien, 2016; Lipson, 1982). Accurate prior knowledge, however, can

be built early on in a child’s education. As Pearson and Billman (2016) emphasize, readers as

young as first grade are naturally curious about the world around them. Young students need

opportunities to engage in learning experiences that support learning new concepts and, as

importantly, support learning the words that represent those new concepts (content vocabulary),

and opportunities that help them learn and practice reading comprehension strategies such as

predicting, visualizing and asking questions (p. 24). Engaging in such activities by integrating

both disciplinary content and literacy provides an opportunity for young learners to learn to read

and read to learn, constructing meaning during reading to build what will become accurate prior

knowledge. Further, for some young readers, informational text is more engaging and interesting

than narrative text (Duke, 2000) and provides those students the opportunity to see and build

themselves as readers.

Yet research continues to show that, while the Common Core State Standards (2010),

with which the Minnesota State Standards in English Language Arts (2010) are closely

correlated, call for an increase in the use of informational text, there is still a dearth of

informational text being used for reading instruction in the lower elementary grades. Literacy

instruction in those grades continues to focus on phonemic awareness, phonics, and decoding,

and texts used to teach those skills do not include rich concepts that provide an opportunity for

students to make new meaning (Duke, 2000; Goldman, et al, 2016; Jeong, et al., Pearson &

Billman, 2016). Students, as they matriculate from the primary grades to the intermediate grades

and beyond, are asked to read and comprehend texts that are much more complex - in content,

structure, and vocabulary - yet they have not encountered these complex concepts, structures,

and specific vocabulary before, so they have not acquired the knowledge and skills needed to

navigate effectively and efficiently through these texts. Students can be further stymied in their

progress to grow as strong readers if they are not provided with the opportunities to learn new

content, text structures and syntax, and context correctly, creating new and accurate knowledge

for the next learning experience. It is easier for students to grasp main ideas by learning new

information correctly at the outset, rather than to have to correct inaccurate information

(Afflerbach, 1990; Kendeou & O’Brien, 2016; Lipson, 1982).

The Acquisition of Knowledge Through Reading

Reading can open up brand new worlds, and make the reader thirst for more. Reading can

answer questions and generate new questions. In other words, reading is a way to fuel curiosity

and learn new things. The premise upon which informational text is written is to inform, and

students’ abilities to read and comprehend texts directly affect their capacity to learn new content

and build new knowledge - which, in turn, affects their future possibilities (Wanzek, et al., 2018).

Students in third and fourth grade are expected to determine main ideas from informational texts,

to integrate ideas across two texts on the same subject, to draw inferences by using key

information from a text, and to explain how an author uses reason and evidence to support their

points (Minnesota Department of Education, 2010). These standards require deeper

comprehension of informational, expository and technical texts students encounter in school,

which in turn, require that a certain set of skills and strategies be taught in elementary school,

such as prediction and inference, to determine the meaning of texts - both explicit and implicit,

(Goodman, et al., 2017; Graesser, 2015; Kendeou, McMaster, & Christ, 2016; Wanzek, et al.,

2018). Because reading achievement scores have remained relatively stagnant over the last three

decades, reading researchers continue to argue for a shift from a focus on the teaching of more

generic comprehension strategies to a focus on instruction which makes use of disciplinary

strategies (Goldman, Snow & Vaughn, 2016; Goldman & Snow, 2015), in order for students to

better traverse the often unique features of texts in different disciplines.

As stated previously, beginning in third grade, students are expected to determine the

main idea of an informational text and provide supporting evidence. While this is an extremely

important skill, determining the main idea is a complex and often difficult task; when the main

idea is not stated explicitly within the text, the reader must construct the main idea through

comprehension of the supporting evidence found within the text (Afflerbach, 1990; Coiro, 2011,

van Dijk & Kintsch, 1983), and through inferences made in the text (Kendeou, McMaster, &

Christ, 2016; Wancek, et al., 2018). Chall’s stages of reading development (1983) outlines

reading as a process which changes as readers gain skill and proficiency. She outlined six stages

from pre-reading to mature reading. An extremely critical transition time is found between Stage

2 and Stage 3 (Chall & Jacobs, 2003; Chall, et al., 1990), when students are increasingly using

reading as a tool for learning. As Chall and Jacobs (2003) state, “If children are unable to make

the transition from Stage 2 to 3, their academic success is usually severely challenged” (para. 3).

Duncan and colleagues (2007) emphasized that academic achievement gains are cumulative,

meaning that learning is a process that involves improvement of already existing skills and

mastery of new ones. Students transitioning from Chall’s Stage 2 to Stage 3 are encountering

texts that are more complex and varied, including words and concepts that are new and

unfamiliar to the everyday lived experiences of most students and where, if they are successful,

they will continue to build their foundational knowledge.

Foundational concepts and knowledge makes students better readers of both narrative and

informational texts, and across content areas, because reading is a process of constructing

meaning and continuing to build knowledge (Cervetti & Hiebert, 2015; Pearson & Cervetti,

2015). While these texts provide challenge for all readers, students from low-income families

and multilingual learners, in particular, face an increased challenge, as basic oral language skills

and myriad word meanings are critical for understanding increasingly complex and difficult texts

(Duncan, et al., 2007; Herbers, et al., 2012; Towsend, Barber, & Carter, 2020), and therefore

critical for building new knowledge. Yet students from low-income families and multilingual

learners from low-income families in particular face challenges in procuring access to the types

of resources needed to build language and literacy skills, including building a strong academic

vocabulary, in order to succeed in school.

The Role of Vocabulary Acquisition on Comprehension of Informational Texts

When one comprehends a text, they learn new things. Students leaving third grade and

moving to fourth grade are encountering more complex texts from which they are to learn new

information. Unfortunately, the now infamous term “fourth grade slump” (Chall & Jacobs, 2003;

McNamara, et al., 2011; Sweet & Snow, 2003; Wharton-McDonald & Erickson, 2017) refers to

myriads of students who are not achieving at grade level. However, Chall and Jacobs (2003)

found that the students’ decline was not in overall comprehension, but had its roots in a decline

in word recognition and word understanding (Wharton-McDonald & Erickson, 2017). As Beck,

Perfetti, and McKeown (1982) aptly state, “words are just labels for concepts” (p. 508), and for

decades, researchers have found that knowledge of word meanings - the concept behind the label

- is strongly related to successful comprehension (Anderson & Freebody, 1981; McKenna &

Dougherty Stahl, 2015; Rupley & Nichols, 2005; Stahl & Fairbanks, 1986). The more words that

students know, the more they are able to comprehend a multitude of texts at increasingly

complex levels. The act of reading is a complicated process, requiring countless connections

being both made in the brain and activated as one traverses a sentence, a paragraph, an article, or

a tome. Words are verbal and visual representations of concepts, and as a reader travels through a

text, they simultaneously comprehend and create new meaning, thus creating new knowledge

and new concepts in the mind. Readers do so by building a mental dictionary, which “uses more

precise definitions” (Willingham, 2017, p. 79), and they continually build new knowledge.

For the purposes of this study, vocabulary is defined “as the number of printed words that

are both decoded and understood” (White, Graves, & Slater, 1990, p. 281). In other words, a

student’s working vocabulary consists of the number of words the student can read and

understand. Knowledge of word meanings is strongly correlated with comprehension (Carroll,

1993; Oakhill, Cain, & Bryant, 2003; Rupley & Nichols, 2005). Building a strong vocabulary,

however, means more than knowing a lot of words. Rapid lexical access during the act of reading

and within a certain situation is critical to understanding a particular text, as many words have

multiple meanings which are not universally appropriate in every situation (Ash & Baumann,

2017; Beck, Perfetti, & McKeown, 1982; Mezynski, 1983). Lexical access and quality is how

accurately and how quickly a person can retrieve a stored mental representation of a word

(Castles, Rastle, & Nation, 2018; Perfetti, 2007; Perfetti & Hart, 2002); such lexical access and

quality includes both spelling (i.e. the difference between face, farce, and fare), and multiple

meaning of the same word (i.e. the difference between the meaning of eating jam and sitting in a

traffic jam). The greater understanding of words and word meaning, the more cognitive resources

are freed up for comprehension and meaning-making (Beck, Perfetti, & McKeown, 1982;

Castles, Rastle, & Nation, 2018; Perfetti, 2007). Vocabulary instruction, therefore, must include

instructional strategies that increase the accuracy of word meanings, fluency with regard to

lexical access (how quickly a student can retrieve the correct meaning of the word), and a strong

understanding by the teacher of the effects that such accuracy and fluency have on

comprehension (McKeown, Beck, Omanson, & Perfetti, 1984).

However, as Michael Graves (2015) pointed out, research indicates that not much robust

vocabulary instruction is taking place in classrooms - the kind of vocabulary instruction that

engages students in challenging and deep meaning-making word work (p. 124). Indeed, Rupley

and Nichols (2005) summarized the historical teaching of vocabulary through an exercise done

with college students earning their teaching degree, whereas they asked the students to describe

their recollections of vocabulary instruction: “. . . receiving an arbitrary list of words on

Monday, looking up the definitions of the words in the dictionary on Monday and Tuesday, doing

some type of skill work . . . on Wednesday and Thursday, and taking a test on Friday” (p. 240).

Indeed, there is a vast difference between memorizing a list of words for a test (the definitional

knowledge) and learning vocabulary at a contextual knowledge level, which has a stronger

connection to text and therefore a stronger ability to aid comprehension (Cunningham &

Stanovich, 1997; Rupley & Nichols, 2005; Watts, 1995).

The absence of robust vocabulary instruction and strong word work, such as learning

prefixes, affixes, roots and suffixes, is quite unfortunate, as the size of students’ vocabularies

varies among different linguistic and socioeconomic groups. Systemic barriers, such as poverty

and income segregation, which will be discussed further in the next section, contribute to the fact

that students from lower socioeconomic groups have less access to literacy resources and

opportunities (Luo, Tamis-Lemonda, & Mendelsohn, 2019; Neuman & Celano, 2001; Neuman &

Moland, 2016), and therefore have different language skills when they reach school age (Hoff,

2013) and smaller vocabularies than their more advantaged peers. English Learner (EL) students

typically have smaller English vocabularies than their English-speaking peers and have different

language development trajectories despite linguistic strengths, and those gaps widen with age,

affecting student achievement (Graves, 2015; Hart & Risley, 1995; Hoff, 2013; White, Graves, &

Slater, 1990).

The Effects of Race, Class, and Language on Reading Comprehension and Reading

Achievement

Schools are often seen as the hearts of a community. The community which is served by

the district in which this study took place is a small, first ring urban/suburban district, and

because of its proximity to a large urban area, the school district is very diverse in terms of race,

class, and home language. While the success of a community can be attributed to data such as

business growth, household income and other economic indicators, the future success of a

community is based largely in part on the education success of its members which, in turn, is

based largely on how well they can read (Angiulli, SIegel, & Maggi, 2004). Disparities in

achievement based upon race, socioeconomic status and language, unfortunately, have been a

stubborn issue in schools in the United States, and in the district in which this study took place.

Therefore, a review of the literature with regard to the effects of native language, socioeconomic

status, and race was warranted.

This study aimed to contribute to the body of research on reading comprehension by

answering the following questions:

What are the essential characteristics of informational texts that can be used for

training reading comprehension strategies in order to improve the reading

comprehension skills of diverse third and fourth grade students?

This research was further guided by the following two sub-questions:

● What are essential text characteristics (length, readability, structure, cohesion,

topics) for the selection of informational texts that can be used for teaching

reading comprehension strategies, such as paraphrasing, self-explanation,

summarization, and question asking, in a digital format?

● What are additional considerations when selecting appropriate texts for (a) a

racially and ethnically diverse population of third and fourth grade students and/or

(b) students who read below grade level?

Children from all walks of life, no matter the race, income status, language, or culture,

gain their funds of knowledge through language - in the home, with friends and families, in the

community, and through other relationships (Conley, 2017; Moje, et al., 2004; Orellana,

Reynolds, & Martínez, 2010). They experience life in their neighborhoods, learn skills from

elders; they learn the idioms of their language, and they learn the norms of traversing their part

of the world. However, issues of race, class, language, and dialect keep underserved populations

in the United States from enjoying the same reading achievement in schools as their White,

middle-class peers (Almasi, Palmer, & Hart, 2010; National Center for Education Statistics,

2019; Troyer, et al., 2019). The literacy achievement gap begins at kindergarten entry and

persists throughout a child’s school career (Hoff, 2013; Neuman & Celano, 2001; Neuman &

Moland, 2019) because of multiple societal factors faced in early childhood. There continues the

need to examine the effects of institutional systems and circumstances that marginalize these

underserved populations and keep them from achieving at rates similar to their peers of the

majority population. Additionally, there continues the need for research on the effects of placing

students at the center of the curricula for students from different ethnic, cultural, linguistic and

socioeconomic backgrounds, and creating new opportunities for learning based on lived

experiences that challenge the continuing view of education found within mainstream value

orientations of a largely White teacher community (Heath, 1999), and that embrace the social

community in which children also learn.

Learning is personal as well as social, as Goodman, et al. (2017) so succinctly pointed

out. A teacher can support or hinder a child’s learning, as there is “no simple one-to-one

correspondence between what teachers teach and what students learn” (p. 91), and studies have

shown that expectations, especially of White teachers, can be lower for English learners and

other underserved populations of students, such as students of color, as teachers’ expectations are

framed by their own class- and experience-based beliefs (Jiménez, et al., 2015; Marx, 2000;

Redding, 2019). Indeed, instruction often is not inclusive of or responsive to students’ lived

experiences and the assets that come with the varying cultures, languages, genders, and races that

are and can be enjoyed in classrooms of diverse students (Almasi, et. al, 2010; Emdin, 2016;

Moje, 2000). Diversity also continues to play a role in the relationship between text and reader

(Pearson & Cervetti, 2017). There can be quite a disconnect between a student’s lived

experiences outside of school and the experiences they have within the school walls. Students

from varying backgrounds and cultures read, write, and speak for different purposes outside of

school, and are quite successful, while in school they are still judged as lacking skill (Hoff, 2013;

Shuman, 1986).

Yet, ironically, there is, at least partially, a remedy for this that has been in existence for

nearly 30 years, and has been articulated theoretically (for a review of the literature, see

Fairbanks, Cooper, Webb, & Masterson, 2017). Students will connect more deeply to and learn

more from texts in classrooms where teachers employ instruction that is culturally relevant and

responsive, including “bringing the relevance of the text to the child’s own experience to help

him or her make sense of the world” (Fairbanks, et al., 2017, p. 460; Kourea, Gibson, &

Werunga, 2017). Epistemology, or our conception of knowledge and how it is created, has

extremely deep undertones. As Neumann, Pallas, and Peterson (1999) explain, epistemologies

are “created through personal and social interactions attuned to the nature of thought (in

Lagemann & Shumann, 1999, p. 258). Much of what we know is rooted in our lived experience.

It’s been said that a person does not go to school to learn what they already know. However, our

lived experiences can help us learn more, but those lived experiences must be validated and

honored in classrooms through belief systems and strong instructional pedagogy (Fairbanks, et

al., 2017; Ladson-Billings, 2014; Ladson-Billings, 1995).

This section explored, in particular, the effects of socioeconomic status and language on

reading comprehension and reading achievement, both within and outside of the classroom.

Additionally, this section explored the effects on reading comprehension of the inclusion of texts

that reflect the cultures and the lived experiences of young readers, and the role those texts have

with regard to reading success.

The Effects of Socioeconomic Status on Reading Comprehension and Reading Achievement

Children begin learning the moment they are born. Oral language plays an important role

in that early learning. Additionally, access early on in a child’s development to print resources,

such as stories, narrative and informational books, poetry and even board books, has a strong

positive effect on a student’s vocabulary and background knowledge, and, as they continue to

matriculate through school, their comprehension of what they are reading, and differences in

print exposure are already apparent prior to any formal education in school (Allington, et al.,

2010; Evans, Kelley, Sikora, & Treiman, 2010; Mol & Bus, 2011; Neuman & Moland, 2019;

Rupley & Nichols, 2005). Because reading is an iterative process, these effects are both

immediate and long-term (Neuman & Moland, 2019). The more a child reads and comprehends

what they are reading, the more they learn, the more vocabulary they build, and the better they

can read increasingly complex texts. The more success they have in reading, the more they will

continue to read; they are motivated by that success, which in turn increases reading achievement

(Allington, 2014; Pribesh, Gavigan, & Dickinson, 2011; Taylor, Frye, & Maruyama, 1990;

Troyer, et al., 2019). Students who read much and read often repeat this cycle and success begets

success.

In the United States, however, children from lower socioeconomic backgrounds

underperform compared to their middle class counterparts, a well-documented problem that has

been persistent in public education for decades (Allington, et al., 2010; Hoff, 2013; Reardon &

Portilla, 2016; for a review see Neuman & Celano, 2001). This inequality, however, has been

historically attributed to individuals rather than to systems (Duncan, Morris, & Rodrigues, 2011;

Neuman & Celano, 2001), including the American education system and the racial and income

segregation of communities and neighborhoods. Emphasis must be placed at this time on the

difference between an inequity of systems, and the oft-quoted, oversimplified argument of the

“culture of poverty” (Lewis, 1966). The latter argues an ongoing, generational view of poverty

that includes dysfunction in families and communities, distorting “the concept of culture and

absolv[ing] social structures—governmental and institutional—of responsibility”

(Ladson-Billings, 2017, p. 82), whereas the former embraces an environmental view of poverty

emphasizing place, and focusing on the impact of social structures, such as the American

educational system and the systemic racial and income segregation of communities and

neighborhoods. A review of the literature focusing on literacy achievement with regard to

income disparity and income segregation was warranted, as lower-income neighborhoods

continue to be populated disproportionately by families of color (Neuman & Moland, 2019).

Contrasts in neighborhoods are stark, and the effects are deleterious for children.

Higher-income neighborhoods are able to provide resources and opportunities that are easily

accessible by families to help ready their students for school. Children in lower-income

neighborhoods have limited access to those same types of resources - in their homes and in their

communities (Allington, et al., 2010; Ladson-Billings, 2017; Mol & Bus, 2011; Neuman &

Moland, 2017). These resources include health and safety resources, green space with parks and

other recreational amenities, resource-rich schools that attract high performing teachers, and

school library media centers that have a plethora of both print and electronic materials.

Although access to print resources, which speaks to the environment in which a person

lives, continues to prove beneficial, the body of research is now just blossoming on the

socioeconomic makeup of communities and the effects therein that the lack of resources and

quality schools in low-income communities has on literacy achievement (Lareau & Goyette,

2014; Neuman & Celano, 2001; Neuman & Moland, 2019; Owens, Reardon & Jencks, 2016;

Rideout & Katz, 2016). For the purposes of this study, the term income segregation is used to

describe the system of “residential sorting” (Bischoff & Reardon, 2014) that leads to inequities

in access for children. Generally speaking, in low-income neighborhoods, libraries are scarce.

Families inconsistently have home libraries of books. Schools in lower income neighborhoods

have smaller media centers and classroom libraries than those found in middle class

neighborhoods, and they are quite smaller than those in upper-class neighborhoods (Allington,

2014; Pribesh, Gavigan, & Dickinson, 2011). One can only think for a moment about the annual

tradition of a school book fair and its impact on school and classroom libraries to visualize the

disparities between lower-income neighborhood schools and their middle- and upper-class

counterparts. Further - and sadly ironic - is the fact that many school library media centers are

open less days of the week than their middle-class and upper-class counterparts, yet middle- and

upper-class students frequent them less than lower-income students (Pribesh, Gavigan &

Dickinson, 2011; Worthy, Moorman & Turner, 1999). The sheer accessibility to a variety of

books and other texts has a great impact on reading achievement, as it is hard to read a book that

does not exist within one’s community.

Access to books is linked to voluntary reading, especially when there is a wide variety of

books from which to choose (Allington, 2014; McQuillan & Au, 2001). Voluntary reading means

more time spent reading which, as has been discussed previously, has a direct impact on reading

comprehension and reading achievement. Additionally, differences in access to a wide variety of

books and other print materials impact opportunities for learning and thinking that are related to

reading achievement, reading comprehension, and reading growth (Neuman & Celano, 2001).

Allington (2014) conveys an important argument, when he states, “. . . when you live in

a ‘book desert’, as do too many children from low-income families, one should not expect that

these children will engage in much voluntary reading” (p. 21). Yet, simply increasing the access

to texts that are of interest to children has a dramatic effect on reading comprehension, growth,

and achievement, as has been discussed previously (see also Lindsay, 2013). Additionally,

providing extended time to read quality literature in the classroom, especially classrooms which

are composed of students whose families have limited economic means, can have great effects on

reading comprehension, growth, and achievement. However, schools that serve largely

lower-income students typically are in poorer physical condition, have fewer instructional

resources, less rigorous curricula, less books per child, poorer quality books per child, fewer

computers per child, lower expectations for achievement, and teachers and media specialists with

fewer formal qualifications; this is overwhelmingly due to the social structures, including school

funding issues (Neuman & Celano, 2001; Owens, Reardon, & Jencks, 2016), and all of these

factors come into play with regard to achievement.

The Effects of Multilingualism on Reading Comprehension and Reading Achievement

As has been established in this review of the literature, strong literacy skills are a crucial

component of academic achievement. The majority of assessments that students in the United

States take to show mastery or proficiency in literacy/English language Arts/reading

achievement are in English. In the state in which this study was conducted, public school

districts are mandated to administer the state standardized reading assessment beginning in

grades three through eight, and once again in grade 10. However, classrooms across America

continue to increase in diversity, and diversity of language. Nearly 45 million immigrants lived

in the United States in 2018, the highest number recorded since any census records have been

kept (Batalova, Blizzard, & Bolter, 2020). However, most of that population is over the age of

40. According to Batalova, Blizzard & Bolter (2020), “Fewer than 1 percent of immigrants were

under age 5 in 2018. . . Five percent of immigrants were aged 5 to 17 years” (para. 18). Most of

the English Language learner (EL) students in schools are children of immigrants who were born

in the United States, and much of the rise in overall diversity in schools comes from the rise of

English learners (ELs), or multilingual learners (MLLs) (Brown, 2017; Slavin & Cheung, 2005).

These learners live in families where the home language is different from the language dominant

in school-based instruction in the United States, which is English, and it is important to

emphasize that a majority of ELs live in poverty (Brown, 2017; Zong & Batalova, 2015).

English Language learners are often thought about in the collective; however, they are

anything but. They come from all over the world, from cultures that speak myriad languages, and

they all fall along a continuum of diverse, educational needs. These students must also take a

yearly language proficiency assessment, gauging their proficiency in the English language in

four domains: reading, writing, speaking, and listening, until they attain scores that show a level

of proficiency where they can be exited from service (Minnesota Department of Education,

2020). While the goal of these regulations is college- and career readiness in the English

language, the system cannot and should not ignore the language assets that students have and use

outside of those that are assessed through formal schooling. They include rich language that

serves many communicative and cultural purposes and are found in normal, daily routines,

situations, and interactions (Goodman, et al., 2017; Tong, Irby, Lara-Alecio & Koch, 2014).

Strong literacy skills are a crucial component of academic success, especially in subjects

that are academically and conceptually demanding, such as science. Furthermore, the lack of

strong literacy skills is evidenced by graduation and the high dropout rate among students who

struggle in reading (Ardasheva, Y., Norton-Meier, L., & Hand, B, 2015; Cook, Pérusse, & Rojas,

2012; Hoff, 2013). In 2016 the national graduation rate for ELs was 67%, which is up from

2010, but still lagging far behind the non-EL average of 85% (U. S. Department of Education,

“Graduation Rates,” n.d., para. 1). Latinx dual language learners make up the largest population

of ELs in the United States, although the largest majority of them are United States citizens, born

in the United States (Hoff, 2013; U. S. Department of Education “Who Are English Learners,”

n.d., para. 1), and for the purposes of this study, this statistic is important: Latinx students make

up the majority population of the ELs learners in the district in which this study took place.

A review of the literature showed that the development of literacy skills is quite similar

whether a student is an EL learner or a student for whom English is their first language, and the

learning of literacy skills in a student’s native language can form the foundation for a successful

transfer of skills to a second language (Angiulli, et al., 2004; Brown, 2017; Palmer, Shackelford,

Miller, & Leclere, 2007), but much depends upon the way transfer is taught. Like non-EL

students who are from lower socioeconomic families, “[l]iteracy is not learned differently in

school and out of school. If there is a difference in success, it is the way literacy is taught in

school, not the way it is learned” (Goodman, et al., 2017, p. 93). Proficient bilingual readers have

been explicitly taught both transfer skills and strategies, vocabulary acquisition strategies, and

were also taught to recognize the similarities and differences in each language (Brown, 2017;

Palmer, et. al, 2007). There is a relationship between multilingual children’s oral language skills

in their heritage language and the acquisition of literacy in English, especially when the student’s

first language uses phonetic orthographies as English does (Slavin & Cheung, 2005). The skills

of phonological awareness, awareness of morphology and higher-order comprehension that a

child learns in their heritage language transfer to the learning of English literacy as well, and

when measuring language knowledge in both languages combined, bilingual children are equal

to, or sometimes even exceed, their monolingual counterparts in vocabulary acquisition (Hoff,

2013, p.10), concepts of print (Bialystok & Feng, 2011), and greater phonological awareness

(Bialystock, 2003). This framing has strong implications for both instruction and learning, and

ultimately academic success, especially when taken from an asset-based point of view.

While proficiency in the English language of ELs lags behind their English monolingual

peers, especially with regard to English vocabulary knowledge and English word-learning

strategies, strong instruction can help ELs catch up (Brown, 2017). However, the instruction

must be carefully planned to reduce cognitive overload. EL students are learning content in

tandem with language, and texts, especially informational texts in content areas, can be “lexically

dense” - that is, have a high number of content words per sentence (Ardasheva, et al., 2015),

which is difficult for many students, and can slow text processing and comprehension, especially

for EL students who are acquiring both general and specific academic language. Furthermore,

although explicit comprehension strategy instruction is beneficial, it, too, can overload EL

learners, especially young EL students. Therefore carefully planned instruction that includes

modified approaches is more beneficial, such as visual and linguistic scaffolding, graphic

organizers, cooperative grouping, and concrete examples (Brown, 2017; Ardasheva, et al., 2015).

Explicit vocabulary instruction and the minimization of the use of out-of-context

instruction and memorization activities are two additional ways to strengthen comprehension

instruction for all students, especially ELs and their low-socioeconomic peers. Out-of-context

activities, such as the use of low-level worksheets and word lists counter the fact that people use

literacy and/or language everyday, as literacy encompasses speaking and listening as well as

reading and writing. Literacy is firmly rooted in social situations. Even reading a book in a

solitary environment is a social situation, because the reader is interacting with the author’s

words, thoughts, purposes and intent. Communication is taking place. However, in a classroom,

that social situation rooted in the dominant language may be unfamiliar to students for whom

English is not their dominant language. Strong reading comprehension is linked to strong oral

language skills, including a wide vocabulary and strong understanding of syntax (August &

Shanahan, 2006; Hoff, 2013). The dominant language of American schools is English, and

English is prolific in examples of figurative language, especially idioms, which teachers use in

roughly 1 out of 10 words in their instruction (Palmer, et al.). Castles, et al.(2018) highlight the

nuances of the English language, such as idioms and other figurative language, and their

importance for second language learners: “For second-language learners, reading comprehension

processes are not deficient in themselves, but limitations in reading comprehension might follow

from differences in knowledge relative to children whose first language is the majority language”

(p. 29).

An EL student may be deemed deficient in literacy, when the truth is that they may be

lacking in the understanding of the nuances of the English language, and skills of academic

literacy - reading, writing, speaking and listening across content in that dominant language of

schools in the United States. However, bilingual children have experiences in another language

that provide background knowledge for understanding but are not reflected in their English

vocabularies (Hoff, 2013). Given the proper support, instruction, motivating activities connected

to the students’ lives, and adequate time, EL students can learn English at levels required to

achieve academic success in school (Angiulli, et al., 2004; Hoff, 2013; Palmer, et al., 2007;

Slavin & Cheung, 2005) and can use the language when needed throughout their professional

and personal lives in a global society.

New Literacies, Online Reading, and the Changing Nature of Reading Comprehension

The Internet, one of our most transformative technologies, has rapidly become the

defining place to find information and to communicate with others; indeed, the scale of change

that the Internet has brought is unprecedented with regard to the use by the number of people in

the number of places and in the short amount of time (Castek, et al, 2015; Coiro, Knobel,

Lankshear, & Leu, 2008; Roser, Ritchie, & Ortiz-Ospina, 2020; Wyatt-Smith & Elkins, 2008). In

2016, 76% of the population in the United States was considered Internet users (Roser, Ritchie,

& Ortiz-Ospina, 2020, para 6). Technology has changed the way texts are displayed and

connected; therefore, technology has changed the way we acquire and read information. K-12

students in the United States, like adults, are increasingly using the Internet to find and process

their information (Goldman, Braasch, Wiley, Graesser, & Brodowinska, 2012), and both the

Internet and wi-fi create new spaces for social interaction, which requires new social practices

and understanding, including comprehension of those social practices, such as blogging, text

messaging, and the use of email (Leu, et al., 2015).

While the term online reading continues to be used, it is gradually becoming engulfed in

a more precise term, which not only eliminates the separation of online reading and offline

(printed) reading, but encapsulates more what the reader is doing, which is utilizing strategic

searching often to solve a problem or do research on an issue (Wharton-McDonald & Erickson,

2017), and “connect[ing] social practices, people, technology, values, and literate activity” (Selfe

& Hawisher, 2004, p. 2, as quoted in Wyatt-Smith & Elkins, 2008). This term is called new

literacies ( Castek, Coiro, Henry, Leu & Hartman, 2015; Coiro, 2011a; Coiro, 2020; Coiro,

Knobel, Lankshear, & Leu, 2008; Gallego & Hollingsworth, 1992; Haetman, Morsink & Zheng,

2010; Leu, et al., 2008; Leu, et al., 2015), which encompasses social practices, the act of writing

(using and creating knowledge), and cultural contexts, including the literacies found in students’

communities and personal lives (Coiro, 2011a; Gallego & Hollingsworth, 1992; Wyatt-Smith &

Elkins, 2008), as well as technical skills.

The term itself is often used in different ways, but it overarchingly reflects the belief that

the idea of literacy (used here in the singular) is rapidly changing and transforming as new

technologies emerge to include multiple literacies (used in the plural) of community literacy,

disciplinary literacy, and social literacy, which is collaborative in nature (Gallego &

Hollingsworth, 2992; Hartman, et. al, 2010; Leu, et al., 2015; Wyatt-Smith & Elkins, 2008), and

for which multiple texts are inherently used in relation to other texts in the act of comprehending

(Hartman, et al., 2010). The Internet is a global network capable of providing infinite, connected

information in a myriad of different text structures (blogs, wikis, videos, chats) with a simple

click of a key on a keyboard. Literacy is no longer a static construct; it changes continually, and

comprehension of all of the various texts, including evaluation with regard to accuracy and

validity of those texts, becomes more complex and requires additional skills, placing more

processing demands on the reader (Baker, 2010, Coiro, Knobel, Lankshear, & Leu, 2008; Leu, et

al., 2015). However, traditional education, especially in the elementary years, has lagged in its

ability to teach the skills required to navigate the demands that the new literacies require

(vanDijk & van Deursen, 2014).

If skills required to become adept at online comprehension are not taught at an early age

in school, the situation is even more dire, as there is still a strong digital divide outside of school,

never more publicly pronounced than during the COVID-19 pandemic. According to recent

research from the Pew Research Center, “35% of households with children ages 6 to 17 and an

annual income below $30,000 a year do not have high-speed Internet connection at home,

compared with just 6% of such households earning $75,000 or more a year,” and this issue is

more pronounced for low-income students of color (Auxier & Anderson, 2020, para. 4). This is

not a new issue; the Pew Research Center reported similar data in 2012 (Leu, et al., 2015), and is

an important factor in the disenfranchisement of already marginalized students, as the home has

become a key factor in learning digitally (Leu, et al, 2015; Rogers, 2016; Wyatt-Smith & Elkins,

2008).

While the term digital divide was coined during the Clinton administration to define the

inequitable access to computers, the Internet, and other information and communication

technologies (ICTs), the term has evolved over the last several decades to include inequalities in

technology skills, how those skills are acquired, and how the technologies are used in daily life

(Rogers, 2016). In order to eliminate today’s digital divide, students must be taught how to

navigate digital texts, and must be provided with ample opportunities for practice with engaging

tasks. The types of digital texts available through blogs, social media, websites and the like, have

altered the landscape of what we read, and students even in elementary school must be taught

how to navigate it in order to access, process, communicate, and comprehend the overwhelming

abundance of information that is at their fingertips.

A testament to this altered landscape is the recent National Council of Teachers of

English (NCTE) chat on Twitter and announced on an NCTE blog post: “Which qualities do you

believe are the most important to be literate in this digital age?” (NCTE, 2020). However, as

evidenced by the plethora of posts on social media and conflicting news reports, anyone can post

just about anything on the Internet and tout it as “real” or “fake” information. As consumers of

these texts, it is incumbent upon us as readers and users of the information to discern the

accuracy of informational digital texts in order to make sense of them. This is part of

comprehension: evaluating the validity of the information read in texts.

Unfortunately, students in the United States do not receive adequate, explicit digital

reading comprehension skill instruction (Leu, et al., 2008), even though students can become

better readers through the explicit teaching of comprehension strategies - strategies that are used

for offline (printed) texts but that can be transferred to online reading environments (Almasi, et

al., 2010; Brown, Pressley, Van Meter, & Schuder, 1996; Guthrie & Cox, 2001; Pressley &

Allington, 2015). Digital reading skills have as their foundation the traditional printed text

reading skills of vocabulary, word recognition, response to literature, and comprehension, but

offline reading comprehension skills and online, digital reading comprehension skills are not

isomorphic ( Leu, et al., 2013; Coiro, 2007; Mokhtari, Kymes, & Edwards, 2009). A person

needs both types of comprehension skills to fully comprehend what they read online, and a

broader understanding of reader, text, context and purpose, as well as environment, is needed by

both the literary community and educators (Coiro, 2020). Specifically, Coiro (2003) outlined

new reading practices gained through the use of the Internet to read, such as different interaction

with text (e.g. hyperlinks), types of background knowledge; and new activities, such as creating

and publishing multimedia projects and participating in digital conversations.

However, no state reading assessment to date includes the assessment of digital reading

comprehension skills, nor does the National Assessment of Educational Progress (NAEP), even

though the Common Core State Standards (CCSS), which the state in which this study took place

is completely aligned, and actually has included additional media literacy standards, requires that

students use technology and digital media to comprehend (English Language Arts

Standards>Anchor Standards>College and Career Readiness Anchor Standards for Reading,

n.d.; English Language Arts, n.d.). However, The Organisation for Economic Cooperation and

Development (OECD) has shown it values reading in a digital environment. The OECD

launched the Programme for International Student Assessment (PISA) for the first time in the

late 1990s, and in 2018 the PISA reading assessment focused on “reading in a digital

environment” (Leu, et al., 2008; Graesser, 2015; OECD, 2018). That said, the PISA assessment

is not utilized by any state for educational accountability purposes under the Every Student

Succeeds Act (ESSA), due to the fact that PISA uses a random sampling of 15-year old students

from schools throughout districts and states, and from countries that volunteer to take part in the

assessment (OECD, 2018). This assessment has no consequences on schools and districts, unlike

state standardized tests, which currently assess only offline reading skills but are used by states

for accountability purposes to satisfy federal law. State accountability tests have public

consequences and with them, the adage that what gets tested gets taught. In other words, state

accountability tests impact the content and materials that teachers teach and students learn

(“What Gets Tested Gets Taught,” 2018). With no current assessment of digital reading skills,

online reading comprehension and strategy instruction is being under-taught, and under-assessed.

As Leu, et al. (2008) emphasize, “To continue ignoring online reading comprehension in

reading assessments and during classroom reading instruction is to reify a static and increasingly

less-relevant understanding of reading comprehension in a world that has gone online, global,

and networked” (p. 335). Stated previously, students are increasingly using the Internet and other

online and technology tools to find and process information, as the Internet and social media

apps have a wealth of informational text. If students struggle in reading, however, they are

inclined to dislike reading and to read less (Cunningham & Stanovich, 1997; Herbers, et al.,

2012). New literacies present challenges, especially for students who already struggle with

traditional print reading, in terms of fluency and critical reading habits (Dalton & Proctor, 2008).

The less they read, the less motivated they are to read and the further they fall behind, leading to

long-term academic trajectories that are hard to disrupt (Herbers, 2012). Motivation and

engagement play a large part in student success, and technology can provide a helpful

environment for that motivation and engagement, especially when students are taught how to

navigate that environment. Digital texts can increase the engagement in the reading process for

struggling readers through the use of multimedia, graphic images, and even the use of Command

+F, and various digital text features and approaches, such as multimedia and gaming support

engagement as well (Dalton & Proctor, 2008; Leu, et al., 2013). Further, computer-based reading

and learning provide the arena for independence, choice, and different formats in which to learn,

and can provide opportunities for practice, intentional scaffolding, and tutoring (Hooshyar,

Ahmad, Yousefi, Fathi, Abdollahi, Horng, & Lim; 2016). Multiple text options and opportunities

for engagement through different online tools can influence students’ self-regulation with regard

to reading (Azevedo & Cromley, 2004; Kulikowich, 2008; Massey & Miller, 2017) and provide

the environment in which reading can be engaging and students are motivated to learn.

The Role of Engagement, Motivation, and Attitude in Reading Comprehension

Because comprehension is inherently an interaction between the text and the reader, this

section explores the role that engagement and motivation in the act of reading imparts on reading

achievement. As stated previously, successful reading achievement leads to success in school and

beyond. Two other factors that relate to school success are the engagement of the student in

school, in school subjects, and the motivation to learn (Duke, 2000; Guthrie, 2015; Guthrie, et

al., 2004; Reschly & Christenson, 2012; Troyer, et al., 2019), including the motivation to read

and engagement in the act of reading, both within the school walls and outside of school,

especially in the summer (Duke, 2000; Duke & Martin, 2015; Guthrie, et al., 2006; Mol & Bus,

2011; Troyer, et al., 2019).

Scholars have differed on their use of the terms motivation and engagement - some using

the terms interchangeably, some keeping the two terms more distinct (Reschly & Christenson,

2012; Unrau & Quirk, 2014), but both terms have been used to describe factors that lead to

reading behaviors and reading achievement. Further, there is not full agreement in the research

on the precise definitions of the two terms. Motivation is generally thought to be an internal and

malleable process which includes emotions as well as thoughts and beliefs that is an influential

force, but that can be shaped through the use of different factors (Guthrie, et al., 2006; Troyer, et

al., 2019; Unrau & Quirk, 2014; Varuzza, Sinatra, Eschenauer, & Blake, 2014). Engagement, like

motivation, also has many definitions but is connected to a person and their individual actions

(Reschly & Christenson, 2012; Unrau & Quirk, 2014); as well, engagement also is thought to be

malleable (Fredricks, Blumenfeld & Paris, 2004). That motivation and engagement are seen as

being malleable is significant for education researchers and educators alike, as it means that both

can change as a result of student experience. For the purpose of this study, engagement is viewed

as action and motivation as intent - somewhat separate but very much related concepts. Further,

and more importantly, both concepts are a significant predictor of students’ reading

comprehension and achievement (Guthrie, et al., 2010; Reschly & Christenson, 2012; Troyer, et

al., 2019; Varuzza, et al., 2014).

Engagement inherently links different contexts to the students, including lived

experiences outside of school; relationships with others, such as peers; and the school

experiences themselves, including relationships with teachers. Students spend the majority of

their formal school experience in classrooms with teachers, so the environment that teachers

create in their classrooms, including the instructional practices they employ, affect how students

see themselves as learners and help to shape their attitude toward reading (Varuzza, et al., 2014).

When a student is engaged in a learning experience, they are active: they are active listeners,

active participants in discussion, active writers, actively engrossed in a text; in other words, they

are actively learning. Varuzza et al. (2014) also found that students enjoyed reading activities that

utilized oral language interaction - in other words, discussion that helped the students further

understand and enjoy the readings. The study conducted by Varuzza and his colleagues was of

particular interest, as their study involved large populations of Hispanic, low socioeconomic and

English language learners (Varuzza, et al., 2014), which is critical to this study and to this

literature review. It has been established in this literature review that low socioeconomic

students, students of color (especially Black and Brown students) and students for whom English

is not their first language continue to struggle in reading achievement. Further, as Guthrie and

Cox (2001) explained, engaged readers “are intrinsically motivated to read for the knowledge

and enjoyment it provides” (p. 284). They read often, learning about new worlds as they traverse

their texts. They enjoy the act of reading, especially of and with texts that are of great interest to

them.

Motivation, on the other hand, is more nuanced, as it encompasses values and beliefs,

along with behaviors (Guthrie, 2015; Guthrie & Wigfield, 2000; Troyer, et al., 2019; Unrau &

Quirk, 2014; Varuzza, et al., 2014). While motivation is a difficult concept to measure, as it is

seen as multidimensional (De Naeghel, Van Keer, Vansteenkiste, & Rosseel, 2012; Varuzza, et

al., 2014), as it encompasses feelings, emotions, and desires, it has been found to be a strong

predictor of comprehension assessment scores, strategy use and engagement (Varuzza, et al,

2014). Motivation has classically been delineated into two types: intrinsic motivation and

extrinsic motivation (De Naeghel, et al., 2012; Massey & Miller, 2017; Unrau & Quirk, 2014;

Guthrie, 2015). While extrinsic motivation can propel our behavior, it is intrinsic motivation that

has a long-term impact on reading achievement (Guthrie, 2015).

It is important to understand the concept of reading motivation in order to help students

stay motivated to read, as different motivations can present themselves in either positive or

negative forms, either driving students to reading or pushing them away from reading (Guthrie,

2015; Guthrie, et al., 2006; Naeghel, Van Keer, Vansteenkiste, & Rosseer, 2012). Motivation has

been historically viewed in the United States as very individual (Massey & Miller, 2017; Guthrie

& Wigfield, 2000), but reading comprehension strengthens as a result of the student being

engaged in the text, motivated to comprehend with intentional reading purposes, and engaging

with tasks within the context of interesting texts (Coiro, 2011a; Duke & Martin, 2015; Guthrie, et

al, 2006), all of which can be influenced within a classroom context.

Engaged and motivated readers are also strategic; less engaged readers show less use of

reading strategies to comprehend a text (Guthrie & Cox, 2001; Wigfield, et al, 2008). Strategy

instruction can increase engagement and motivation along with reading comprehension, using

several approaches, such as self-monitoring, gleaning main ideas, questioning, summarizing,

paraphrasing, and inference (Wigfield, et al., 2008). Relevant to this research are those adopted

in Concept-Oriented Reading Instruction (CORI; Guthrie & Cox, 2001; Guthrie et al., 1996,

2007; Wigfield et al., 2014). Concept-Oriented Reading Instruction is focused on informational

texts to explicitly teach reading strategies, and the elements of CORI are sound instructional

practices. Implemented in CORI are six teaching practices to increase student motivation: 1)

providing thematic content information, 2) optimizing choice, 3) explicit teaching of reading

strategies, 4) hands-on activities, 5) providing interesting texts, and 6) collaboration (Guthrie &

Cox, 2001; Guthrie, et al., 1996, 2007). Other studies have shown that these six are effective,

along with an additional variable, which is having reading goals (Guthrie & Cox, 2001; Wigfield,

et al., 2008). Students who experience teaching practices like those found in CORI have shown

larger comprehension gains and demonstrated both greater reading strategy use and reading

motivation than those given only strategy training or traditional reading instruction. These effects

have been found at both third grade (Guthrie et al., 2004) and fourth grade (Wigfield et al.,

2008).

Motivation to read begins to decline as children get older, beginning near the end of the

elementary years (De Naeghel, et al., 2012; Skinner & Pitzer, 2012; Troyer, et al., 2019; Varuzza,

et al., 2014; Wharton-McDonald & Erickson, 2017). However, this decline in motivation is more

pronounced for students for whom reading is a struggle; they take less pleasure from reading and

this has a cumulative effect on both reading achievement and the motivation to learn

(Wharton-McDonald & Erickson, 2017). When students are not given choice in reading, or when

students feel the texts are irrelevant or they do not find themselves or their experiences reflected

in the books they read, their intrinsic motivation to read declines, as they feel devalued not only

in the classroom, but in the larger society for which the classroom is an extension (Bishop,

1990). This issue can be mitigated, however, through the structure of a positive learning

environment. Skinner and Pitzer (2012) called attention to the belief that students “come with a

wellspring of intrinsic motivation that does not have to be acquired and cannot be lost” (p. 33).

Gay (2010) spoke eloquently about the creation of learning spaces that celebrate students,

especially students of color, asking teachers to engage students “to and through their personal

and cultural strengths, their intelletctual capabilities, and their prior accomplishments” (p. 26).

The creation of a culturally inclusive, more engaging classroom environment that includes strong

pedagogy, can build student agency and offset the natural decline in reading motivation that

students experience as they get older (De Naeghel, et al., 2012).

Culture and ethnicity play a central role in engagement, especially given the

underachievement of African American, Latinx, and American Indian students in the United

States and the achievement gap of these populations and their White peers (Bingham & Okagaki,

2012). Engagement and motivation take on a more urgent role for students who are experiencing

structural racism within impoverished communities, negative stereotypes, and systemic racism in

formal schooling whereby students of color do not feel included or acknowledged for who they

are (Reynolds, Sneva, & Beehler, 2010; Tatum, 2006; Thomas, 2018), as their prior knowledge

and lived experiences are less likely to be prominent in many of the instructional materials and

assessments used in classrooms (McCullough, 2013). Additionally, many students of color lack

positive role models within an academic setting - including teachers of color and positive

representation in texts read in school, as it is as important for students to make personal

connections to their school experiences and learning as it is to provide students with new

experiences and learning (Bishop, 1990. Christ & Sharma, 2018; Tatum, 2006).

Bishop (1990) coined the terms mirrors, windows, and sliding glass doors (p. 1) to

describe the endless possibility of experiences students of color could have in classrooms that

would further engage and motivate them. Texts provide windows, or a way of seeing and

viewing new or imagined worlds; they provide sliding glass doors which, like windows offer

new and exciting views of the world but also offer the opportunity for students to see themselves

in those new worlds; and they provide mirrors, wherein readers can see their “lives and

experiences as part of the larger human experience” (Bishop, 1990, p. 1). Reading and learning

from relevant texts, then, can be not only a self-affirming experience, but an experience that

strengthens students’ self-efficacy, particularly for students of color.

Related to motivation and engagement is reading attitude. The attitudes that students

bring to the act of reading are inextricably linked to motivation and engagement. Attitudes are

tied to feelings and emotions, especially with regard to school in general and the act of reading

specifically (Alexander & Filler, 1976; Fiedler & Beier, 2014; Logan & Johnston, 2009;

McKenna, Kear & Ellsworth, 1995; Smith, 1990; Wade, 2012). Reading attitude, especially with

regard to students’ perceptions of themselves with regard to the act of reading, influences the

amount of independent reading, involvement in activities related to reading, and use of cognitive

strategies (Akbari, Ghonsooly, Ghazanfari, & Shahriari, 2017; Logan & Johnston, 2009;

McKenna, et al., 1995; Varuzza, et al., 2014), as attitude contributes to a student embracing or

evading a situation that involves reading (McKenna, et al., 1995).

McKenna, et al. (1995) stated that “an individual’s attitude toward reading will develop

over time principally as the result of three factors: normative beliefs, beliefs about the outcomes

of reading, and specific reading experiences (p. 939). Further, reading attitude encompasses

social norms, especially in a school setting where students are forming and re-forming identities

and group affinities, students are looking for affirmation from teachers, and there is a perceived,

if not real, competition for different statuses (e.g. academic, athletic, artistic, popularity).

Unfortunately, as stated previously, positive reading attitudes can decline as students matriculate

through the grades (Martínez, Aricak, & Jewell, 2008; McKenna, et al., 1995; Smith, 1990;

Varuzza, et al., 2014).

Attitudes form as a result of experience, success and failure, and cultural expectations,

including the expectations by gender (Akbari, et al., 2017; Logan & Johnston, 2009; McKenna,

et al., 1995) as well as by ethnicity, socioeconomic status, and first language (Akbari, et al.,

2017; McKenna, 19997; McKenna, et al., 1995; Mohd-Asraf & Abdullah, 2016; Wade, 2012).

Therefore, the importance of attitude toward reading warranted a review of the literature

focusing on gender, socioeconomic, ethnic, and language differences.

With regard to traditional gender, girls were found to have more positive attitudes toward

reading, they read more, and had higher reading achievement than boys (Akbari, et al., 2017;

Logan & Johnston, 2009; McKenna, et al., 1995; Mohd-Asraf & Abdullah, 2016; Swalander &

Taube, 2007). This was also the case when socioeconomic status was a factor (McKenna, 1997).

With regard to ethnicity and race, McKenna, et al. (1997), citing work from McDermott (1974)

and Long (1963), stated that students of color could sense that teachers judged them and their

abilities differently than the majority population, ignoring their cultural identity and forcing

mainstream cultural norms upon them that felt oppressive (p. 939). Akbari, et al. (2017)

emphasized that reading is a skill, no matter the first or home language; however, the attitude

toward the home language was highly correlated to the attitude toward the second language (L2),

and gender also played a role in the attitude toward L2 reading (Mohd-Asraf & Abdullah, 2016).

Cultural norms, whether economic, linguistic, ethnic or genderized, are a factor with regard to

reading attitude.

The Role of Culturally Relevant Texts on Successful Comprehension

The term culture is nuanced in meaning. Merriam Webster has several definitions of the

term that reference shared experiences and features of groups of people and also institutions

(Merriam-Webster, n.d.). Examples can include teen culture, school culture, hip-hop culture, and

a myriad more. However, culture is often used when referring to the lived experiences of people

of color. In that vein, the term culture can carry with it harmful baggage with regard to

assumption and judgment and, as a result, the assignment of greater or lesser worth, with terms

coined such as cultural deprivation, cultural disadvantage, and culture of poverty (Erickson,

2012, p. 561). When used, these terms assign a preconception of ability and validity to students

based on their lived experiences. It is true that the faces that greet teachers in public schools in

the United States continue to be more diverse with regard to ethnicity, culture, and language, but

each of those students come with assets that others do not have. According to the National

Center for Education Statistics (2019), of the projected 50.7 million public K-12 students in

2020, only 46.1% are White; the second most populous group identify as Hispanic, at 27.6%,

followed by 15% who identify as Black, 5% who identify as Asian, 4.5% who identify as two or

more races, 1% who identify as American Indian, and .3% who identify as Pacific Islanders

(NCES, 2019, What are the demographics of public school students), with the population of

Latinx, Black and Asian students increasing every year (Glass, 2019).

As established previously through a review of the literature, there is an alarming, yet

persistent gap in reading achievement between students of color, students from low

socioeconomic families, and EL students and their White, middle-class peers and, if not

mediated by the time students are in grades 3 and 4, the chances that students will catch up to

their grade level peers is slim (Barber, et al., 2018). However, as Erickson (2012) emphasizes,

outside lived experiences often “don’t fit well with the cultural practices of . . . classrooms” (p.

562); therefore, it becomes incumbent upon schools and teachers to become responsive to the

students’ strengths and interests. While motivation for reading begins to decline in elementary

school, the beliefs and practices that teachers bring into an inclusive classroom environment,

including culturally relevant text selection and pedagogy, can support motivation and

engagement, which in turn support positive reading achievement (Barber, et al., 2018; De

Naeghel, et al., 2012; Christ & Sharma, 2018; Guthrie, 2015). Guthrie and Cox (2001) stated the

use of relevant books quite succinctly: “For reading instruction, text is central” (p. 291). Using

literature in reading instruction that is positively reflective of and relevant and interesting across

different cultures and experiences, that reflects the students in the classroom and draws upon

their backgrounds and languages, and with which the students can identify, has a positive impact

on reading achievement and on readers’ self esteem (Barber, et al., 2018; Ebe, 2010;

Ladson-Billings, 1995; Kourea, Gibson, & Werunga, 2017; Tatum, 2006, Troyer, et al., 2019).

High quality, engaging materials matter. When students have an opportunity to interact

with high quality literature that reflects them and their lived experiences, reading comes to life, it

takes on new meaning and urgency, and it becomes meaningful to the students (Keis, 2005).

Troyer, et al., (2019) used the term “high reading quality” (pp. 1204, 1206) to describe texts that

were matched to both the students’ reading ability and their interests, including their experiences

outside of school, which Ladson-Billings (1992, 1995) describes as “culturally relevant” with

regard to texts and teacher practice. Bringing students’ lived experiences into the classroom, and

finding materials to match them, celebrates the students and their cultures - in other words, it

legitimizes them and their experiences. It “place[s] education into culture, rather than

place[s]culture into education” (Pewewardy, 1993, p. 78) which, of course, is less surface culture

and more authentic learning. However, as Ladson-Billings (1992) echoed, it is imperative that

leaders in education, whether it be at national, state, district or classroom levels, use the culture

of the students to help them understand themselves and to understand and interact with the world

around them and to “conceptualize knowledge” (Ladson-Billings, p. 314) to challenge existing

assumptions and structures in order to create endless opportunities for the future. In order to do

that, students must be provided with texts that reflect themselves, and their lives, in ways that

open doors.

Although the texts matter, there continues to be a struggle to find quality literature written

by and about Black, Indigenous, and People of Color (BIPOC). Each year, the Cooperative

Children’s Book Center, housed at the University of Wisconsin-Madison, which is a research

library in service to librarians, teachers, early childhood providers, and others, provides

information on diversity in publications for children and teens (Cooperative Children’s Book

Center, n.d.). In June of 2020, they released the 2019 CCBC Diversity Statistics, which is later

than usual due to the COVID-19 pandemic (The Numbers are In: 2019 CCBC Diversity

Statistics, 2020, para.1). While three of the five identified ethnicities showed a slight increase in

the number and percentage of books that represented BIPOC, the increases were quite slight:

0.5% increase for books that had significant Black/African content (from 11.7% to 12.02%),

0.2% increase for First/Native Nations (from 1.0% to 1.2%), and 0.5% increase for Asian/Asian

Americans (from 8.5% to 9%). There was a decrease of 1.0% in the number of books that

significantly represented Latinx students (from 7.3% to 6.3%), and 2019 was the first year that

Pacific Islander was a category of itself, with 0.1% of the total number of books representing

students identifying in this category (The Numbers are In: 2019 CCBC Diversity Statistics,

2020, Percentage of Total Books Received by CCBC: About [US Publishers]).

The low numbers of books written by and for people of color are disconcerting given the

fact that no one-size fits all curriculum benefits all children (Crowe, Connor, & Petscher, 2009).

Our students of color, low socioeconomic students, and students for whom English is not their

first language continue to achieve at lower levels than our White middle-class students.

Culturally relevant texts are those texts that students can connect to on many levels, drawing on

their life experiences and background knowledge to create new meaning (Ebe, 2010). Yet the

number of books that are by BIPOC authors or about BIPOC main characters, which books could

contribute to increased individual interest and which would lead to “increased attention, greater

concentration, pleasant feelings of applied effort, and increased willingness to learn” (Krapp,

Hidi, & Renninger, 1992, p. 9 as cited by Worthy, Moorman, & Turner, 1999, p. 15), continues to

lag far beyond those books by White authors and about White main characters or about

non-human characters. In fact, in 2019, nearly three-quarters of the children’s and young adult

books published in 2019 featured white children or non-human characters (The Numbers are In:

2019 CCBC Diversity Statistics, 2020). The diversity of the students in our public schools,

however, and the diversity of their lived experiences and those experiences of their families, call

upon us to find as many books as we can that reflect our students in positive ways. Keis (2006),

cited Rich (1986) by stating the following:

When those who have the power to name and to socially construct reality choose not to

see you or hear you . . . when someone with the authority of a teacher describes our

society and you’re not in it . . . the experience becomes a moment of psychic

disequilibrium, as if you looked into a mirror and saw nothing. (p. 199)

Finding and tapping into the assets that our students bring to the classroom everyday, and finding

and intentionally using high quality, culturally relevant texts in the classroom, is to create an

opportunity for our students to become engaged and motivated to learn more, and ergo to grow

and flourish, because they will be validated, seen, and heard (Keis, 2006; Ladson-Billings, 1992;

Ladson-Billings, 1995; Troyer, 2018).

Conclusion

The act of reading is quite complex, situated in cognitive, social, linguistic, and

socio-cultural contexts between the reader, the text, the context, and the situation. To further

exacerbate the complexity, the United States has been long grappling with the ugly reality of

reading achievement disparities between students of the dominant culture of White, western

European, middle class culture and those students who are not of that culture - in particular,

African American, Latinx, students of limited economic means, and students for whom English

is not their first language. Quite often, one student can identify in all of those categories. Further,

the review of the literature established that a crucial period of reading proficiency is grades 3 and

4; if a student is not proficient in their literacy skills by that time, they continue to fall further

behind. Further, the landscape of literacy and texts continues to change with fast-paced advances

in technology.

The goal of reading is to understand what is read; in other words, comprehending the text

- in order to create new knowledge. Reading is fundamental to successful achievement in school.

Therefore, it is imperative that education researchers and practitioners alike fully understand the

barriers that keep students from successful comprehension, and create inviting, engaging, and

affirming environments, opportunities, and interventions, both offline and online, that eliminate

those barriers. In doing so, students will see themselves as strong and competent learners.

In that light, it was the goal of this research to study a particular intervention, the

paraphrasing intervention, with students in grades three and four in an online environment, and

the effects it has on student engagement and efficacy, as well as their comprehension of the

informational texts they were provided as part of this research. The specific rationale for and

methodology used in this study is discussed in Chapter Three.

CHAPTER THREE: METHODOLOGY

No research is ever quite complete. It is the glory of a good bit of work that it opens the way for

something still better, and this repeatedly leads to its own eclipse.

-Mervin Gordon

Introduction

The purpose of this mixed-methods research study was to explore specific components of

reading comprehension with regard to the role of texts and reading digitally. This study

researched the impact of informational texts on reading comprehension skills. Specifically, the

study looked at essential characteristics of informational texts with regard to comprehension

intervention in an online format for students in grades three and four who were at-risk of reading

difficulties or already struggling in reading comprehension. More precisely, the researcher

examined those characteristics of informational texts utilized in an online comprehension

intervention that lead to greater student engagement with the texts, and can also lead to

comprehension success.

This design-based implementation and mixed-methods study explored reading

comprehension and the role that texts and new literacies play in answering the central research

question:

What are the essential characteristics of informational texts that can be used for training

reading comprehension strategies in order to improve the reading comprehension skills of

diverse third and fourth grade students?

This research study was further guided by the following two sub-questions:

● What are essential text characteristics (length, readability, structure, cohesion,

topics) for the selection of informational texts that can be used for teaching

reading comprehension strategies, such as paraphrasing, self-explanation,

summarization, and question asking, in a digital format?

● What are additional considerations when selecting appropriate texts for (a) a

racially and ethnically diverse population of third and fourth grade students and/or

(b) students who read below grade level?

This chapter introduces and reviews the methodology used for the study. The description

and discussion of the methodology used in the study will center on each research question. This

review of the methodology includes the rationale for the study; the research paradigm; the

research setting and participants; overview of the data, including the methods and tools used for

data collection; methods for analysis of the data; and ethical considerations, biases and

limitations.

Rationale for the Study

While public education has had many goals since its inception in the early nineteenth

century, one goal has remained consistent throughout the tenure of public education: to provide

access to and equality of opportunity (Spring, 2018). To that end, early success in reading is a

strong predictor of success in high school (Cunningham & Stanovich, 1997; Sparks et al, 2014).

The goal of reading is to understand what is read - in other words, comprehending the text - in

order to create new knowledge. Yet many students in the United States, and in Minnesota, where

this study took place, continue to struggle in reading. Their struggle is evidenced by stagnant

reading proficiency scores over the last decade. Only one-third of fourth graders have met

grade-level proficiency on assessments designed specifically to analyze trends and growth

(National Center for Education Statistics, 2015; 2019), despite increased time dedicated to

standardized assessment of students’ ability to comprehend texts. Additionally, a significant gap

persists for fourth grade students based on race and socioeconomic status (National Center for

Education Statistics, 2019). Further, the results on state and national reading assessments indicate

that students in the United States, and in Minnesota, continue to struggle to comprehend

expository texts, which are used in content-specific instruction as students move up grade levels

(National Center for Education Statistics, 2019; Minnesota Department of Education, 2020).

Much instruction at these grade levels continues to focus on more generic and low-level

strategies to promote learning from texts, including recall of information or inferring word

meanings from surrounding content (Goldman, et al., 2016). Students often do not have the

requisite prior knowledge needed to comprehend expository texts fully, yet prior knowledge is an

integral component of reading comprehension (Kendeou & O’Brien, 2016). Given these factors,

and the results currently realized in reading achievement as evidenced by state and national

reading assessments (National Center for Education Statistics, 2019; Minnesota Department of

Education, 2020), there is a great need for explicit and effective reading comprehension

instruction utilizing texts of all genres at the elementary level, beginning in the early grades; and

for a strong system of comprehension intervention for students who are struggling with this skill.

Furthermore, expository texts are necessary for comprehension and new learning in content areas

such as social studies and science; therefore, identification of essential characteristics of

expository texts will further inform instructional practice as teachers continue to make decisions

on what texts to place in front of their students.

Because of this need, there is currently a large national research study funded through the

Institute of Educational Sciences (IES) that is developing a comprehension intervention tool,

called the Interactive Strategy Training for Active Reading and Thinking for younger readers

(iSTART-Early). The tool will be a web-based reading comprehension strategy tutor that will

provide both instruction and opportunity for student practice. Once created, the tool will target

students in grades 3 and 4, two years in a student’s academic career that are critical for reading

development.

Because this small research study is one leg of the larger national study focusing on

grades 3 and 4, the target group of students for this study were third and fourth grade students

who were identified, by the district through normed and standardized testing scores, as reading

below grade level, and struggle to comprehend expository texts from which they are to acquire

new knowledge (Duke, 2000; Jeong, et al., 2010, Pearson & Billman, 2016). Although these

students struggle, they are maturing and many are becoming developmentally ready for

introduction of higher-order cognitive processes which have the potential to improve reading

comprehension (Del Giudice, 2014; Del Giudice, 2018). Additionally, there is an increase of

expository texts in the curriculum beginning at this age and grade level, texts from which

students are expected to gain new knowledge. However, as Duke (2000) and Jeong, Gaffney, and

Choi (2010) examined, the majority of classroom print prior to third grade is narrative and the

proportion of informational text is small, especially in schools with higher numbers of

low-income students. The time spent on reading instruction specifically focusing on

informational text, including time spent on informational text structure, is but a miniscule portion

of the student’s school day (Beerwinkle, et al., 2018; Duke, 2000; Strong, 2020).

Compounding this issue is that the time students spend engaging in informational text,

and the time spent instructing using informational text, may be miniscule compared to the school

day itself (Beerwinkle, et al., 2018; Duke, 2000; Ness, 2011; Strong, 2020). These texts are used

by students to acquire new meaning. However, the texts present challenges for which some

students are unprepared, including increasing text complexity, density of language, increased

length, lack of cohesion across text, and abstract concepts that require knowledge of the world

that students may not have (Chall, 1983; Jeong, Gaffney, & Choi, 2010). This lack of exposure

and preparation results in many fourth graders experiencing a decline in reading achievement,

beginning during the transition from primary to intermediate grades in elementary school, and

which continues into middle school (Best, Floyd & McNamara, 2008; Chall, 1983; Chall &

Jacobs, 2003; Chall, Jacobs & Baldwin, 1990; McNamara, et al., 2011; Wharton-McDonald &

Erickson, 2017). Further, this lack of exposure and preparation may also impede students’

learning of the content in areas such as science and social studies.

This researcher made the decision to focus the research in this study specifically on

science texts, and did so for two reasons. First, Minnesota adopted a new set of K-12 science

standards in 2019 which included changes that have significant implications on instructional

pedagogy, and for districts, initiates review of curriculum used in classrooms. Therefore, this

work is timely with the shift in the standards. Second, the district historically placed less

emphasis on science instruction in the elementary grades than instruction in literacy and math,

because the state requires annual assessment in those two content areas beginning in third grade.

However, less science instruction means less exposure to topics of interest for a variety of

students, especially students of color (Lee, 2020), and less exposure to content-specific

vocabulary needed to successfully navigate science texts. As was discussed in Chapter Two, the

reading of various texts provides students with the ability to gain knowledge of different topics,

which aids the students in comprehending more complex texts (Goodman, et al., 2017; Kendeou

& O’Brien, 2016). Since there was less science instruction throughout the day and week, there

was less use of science texts for instructional purposes, and therefore less understanding by the

students of science concepts, which contributes to comprehension difficulties. The use of science

texts would provide participating students with another opportunity to read texts that focused on

science concepts.

Additionally, a large achievement gap persists in the reading proficiency between White

students and students of color (SoC), many of whom are multilingual learners and many of

limited socioeconomic means (National Center for Education Statistics, 2019). These factors,

through a review of the literature, contribute to reading difficulties, whether through language,

vocabulary, or prior knowledge. Finally, review of the literature uncovered a need for teachers to

better understand the comprehension skills needed to successfully read online texts and how

those skills may be different than those needed to successfully read printed texts. This

understanding will better equip teachers to help their students navigate through new literacies.

Additionally, this understanding will help teachers realize what assets struggling readers do have

and what skills they are still lacking, in order to make strong instructional decisions that lead to

greater reading comprehension in both printed and digital text formats.

Because students are becoming increasingly exposed to digital text, this researcher,

herself a former English language arts teacher and a current district administrator, built a strong

partnership between the school district used for this study, and a major research university

located in the same metropolitan area; this was a partnership that initially focused on the role that

inference has to reading comprehension in the younger grades. The major research university has

created online tools for improving inference-making in reading, which is a strategy known to

increase reading comprehension (Kendeou, McMaster, & Christ, 2016; Wanzek, et al., 2018).

The strong partnership between the district and the research university provided the opportunity

to design a study that would help to inform the creation of a new web-based comprehension

intervention tool titled Interactive Strategy Training for Active Reading and Thinking for young

developing readers: iSTART-Early, designed specifically for students during a very critical

period in reading development: grades 3 and 4. The iSTART-Early tool is currently being

developed and, once created, will focus on the comprehension strategies of comprehension

monitoring, paraphrasing, inference (prediction/bridging/elaboration), question asking,

explanation, and summarization. The researcher, who was a district administrator overseeing the

work of literacy in the district, spent the last several years disaggregating reading achievement

data in the district, and knew that these years were critical for student success in reading.

Therefore, she made the decision to focus this study on better understanding the role that the

texts themselves play in students’ reading success to help inform the types of texts that could be

utilized in iSTART-Early.

The iSTART-Early tool has a module sequence that was designed similarly to its

predecessor, iSTART, which was built for older students through funding from a national,

multi-year Institute of Educational Sciences (IES) grant. In iSTART-Early, there are five

modules planned for the tool. They incorporate six reading comprehension strategies

(paraphrasing, comprehension monitoring, question asking, elaboration, bridging, and

summarizing). The five modules are as follows: Ask It, which is an overview of comprehension

monitoring and question asking; Reword It, which incorporates the paraphrasing strategy; Find

It, which also works with paraphrasing; Explain It, which works on elaboration, bridging,

question asking, and paraphrasing, and Summarize It, which helps students with retelling and

explanation, and also includes work on main idea. The modules are presented in sequential

design, with the strategies building off one another. Paraphrasing is the first module in which

students generate actual responses to text (the first module requires only identification tasks).

This study will help to inform the larger research study and the eventual creation of

iSTART-Early by identifying essential text characteristics for texts that will be developed for the

iSTART-Early tool, especially in schools and districts that serve a higher proportion of

disadvantaged students, including students of color and English Language learner (EL) students.

Research Paradigm

In schools, most teachers use texts to teach reading and to teach content. Students

increasingly use texts to gain new understanding, beginning in earnest in third grade. Thus, it is

important to gather information from both users to ascertain the essential characteristics of an

informational text to help improve reading comprehension. Teachers, who plan lessons and units

using reading materials, must understand why the characteristics are important. Further, it is

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imperative that researchers understand how students traverse through informational text. As

McMillian and Schumacher (2010) illustrated, relying on just qualitative or quantitative methods

can be insufficient to provide a complete picture for which the purpose of a study requires. Their

statement rings true for the purposes of this research study; both qualitative and quantitative data

was needed to help answer the research questions. This study analyzed teachers’ input on the

texts utilized in this study with regard to length, readability, structure, cohesion, interests and

topics (qualitative data), and analyzed students’ understanding of the texts through the strategy of

paraphrasing, which is the first module in which students would engage in the final

iSTART-Early intervention tool. Additionally, the students did so in an online format

(quantitative data).

The theoretical framework for this study was guided by the construction-integration (C-I;

Kinstch & van dijK, 1978; Kintsch, 1983; Snow, 2002) model of comprehension that provides a

more individualized understanding of reading comprehension, such as variance by age, skill,

format, and life experience (Fox & Alexander, 2017; Israel & Reutzel, 2017; Kintsch, 1998;

Paris & Hamilton, 2005). The C-I model provides a more balanced view of reader and text, and

provides an extremely important focus on context, which is a filter of sorts that people use to

view the world and make meaning (Kintsch, 1988). Construction-integration brings together the

reader, text, context and situation; the research design for this study provided the data needed to

ascertain a holistic view of the type of texts needed for a diverse group of third and fourth

graders who struggle with reading comprehension.

Because this study focused on the interaction of students with texts, this research was

viewed through the lens of pragmatism, which as Cresswell and Cresswell (2018) explain, arises

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out of “actions, situations, and consequences rather than antecedent conditions” (p. 10). This

epistemological paradigm fits well in the theoretical framework of construction-integration with

regard to reading comprehension. Readers interact with a text in a certain situation; they bring

with them their lived experiences and other sources of knowledge that have helped to form their

knowledge base, which may or may not be accurate (Kendeou & O’Brien, 2016; Kendeou, et al.,

2016). Reading comprehension is the result of that interaction, those life experiences, prior

knowledge and knowledge bases, and the situation in which the reader is engaged.

To account for these complex interactions, this study used both Design-based

implementation research (DBIR; Fishman et al., 2013; Penuel, Fishman, Cheng & Sabelli., 2011)

and Mixed Methods research. Design-based research (Cobb et al., 2003) is a research design

with which Mills (2010) recommended increased use with regard to literacy. It fosters flexible

conceptions of literacy, especially digital literacy, and provides formative data that is

contextually situated. DBIR is an extension of design-based research that includes the active

involvement of those who will ultimately be implementing the strategy intervention – for this

study, it was teachers and students. This research approach involves iterative, collaborative

design of solutions targeting multiple levels of the system: design that is informed by ongoing

and systematic inquiry into implementation and outcomes. The four key principles of DBIR align

well with education research, especially to the persistent low achievement in literacy, because

DBIR includes the development and testing of ideas and innovations that can improve teaching

and learning (Penuel, et al., 2011). Paraphrasing Fishman, et al., (2013, pp. 142-143), these four

principles are:

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● Focusing in persistent problems of practice, especially from multiple

stakeholders’ perspectives (in this case, teachers, students, researchers);

● Committing to a collaborative design that is iterative in nature (trying something

out, analyzing data, revising, implementing again);

● Committing to developing both theory and knowledge of students’ learning in the

classroom, and the implementation of strong instructional practice through

systemic inquiry;

● Committing to creating capacity for sustainable change in systems.

With DBIR, there is a common commitment to building theory and knowledge within the

research community (Fishman, et al., 2013). It is not enough to know that an innovative

intervention strategy is effective – it is also important to understand the key active ingredients

and the underlying mechanisms that are related to promise and sustainable change; this

ultimately informs practice in the classroom. For this study, there were two iterative cycles, a

number which was unknown at the beginning of the research as the cycles were continually

determined based on previous findings throughout the research phase of the study.

Mixed methods research (MMR, Johnson & Christensen, 2017) is the type of research in

which the researcher combines elements of qualitative and quantitative research approaches. This

research design can be very helpful in providing information in the way of themes, issues, and

other information that will be the focus of quantitative research (McMillian & Schumacher,

2010). A mixed methods approach is congruent with the principles of DBIR, in that the two

types of data obtained (qualitative and quantitative) can come from multiple stakeholders in the

study. In this study, the researcher used qualitative research to obtain data from practitioners

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(teachers and literacy experts) regarding types and characteristics of texts that they would use in

literacy instruction with third and fourth grade students. That data was then used to create a set of

texts used in a research environment where students in grades 3 and 4 interacted with the texts

(reading and engaging in paraphrasing in an online environment, and answering questions

focusing on how they felt about the texts they read) whereby quantitative data could be obtained.

The researcher also gathered data on student participants’ reading attitudes and their basic

understanding of grade level science concepts, which data could be quantified and compared

with the paraphrasing results. Finally, the researcher interviewed each participant individually at

the end of the observation cycle to obtain information on what they remembered about the

strategy used, and also abou their own efficacy as a reader.

For the purposes of this study, the researcher utilized exploratory sequential mixed

methods design (Cresswell & Cresswell, 2018). She began with qualitative research to explore

the ideas, opinions, and views of practitioners. Analysis of that data informed the creation of

tools used in the quantitative phases of the study. This process involved the creation of the texts

used in the research, and also involved the students.

In the quantitative phase involving the students, this study used a single-group,

quasi-experimental design, utilizing a single group of students in a pre-/post design which,

according to McMillian and Schumacher (2010), is helpful in education research because it is

often impossible to create random assignment of students. Therefore, in this study, the students

were not randomly assigned to groups, and the original setting - the classroom and the summer

targeted services context - was preserved as much as possible, given the limitations that the

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COVID-19 pandemic placed on the original plans outlined for the district summer targeted

services program.

By combining qualitative and quantitative data, the researcher augmented the quantitative

data obtained from the students by including the perspectives of the practitioners. This aided in

the development of a more thorough understanding of the relationship between the texts chosen

for a reading comprehension intervention and how the students actually engaged with them. This

fuller understanding could not be obtained through the use of only one method or the other. For

the purpose of this study, the researcher leaned on Johnson, Onwuegbuzie, & Turner’s (2007)

definition of mixed methods:

research . . . in which a researcher . . . combines elements of qualitative and quantitative

research approaches (e.g. use of qualitative and quantitative viewpoints, data collection,

analysis, inference techniques) for the broad purposes of breadth and depth of

understanding and collaboration (as cited in McMillan & Schumacher, 2010, p. 396).

A deeper discussion of the methodology for this study takes place by discussing the qualitative

and quantitative phases separately. To better understand the methodology, however, a discussion

of the participants and research setting was warranted.

Research Setting and Participants

Research Setting

The setting for this research study was a small, first-tier suburban district in Minnesota,

with a student population of approximately 4,100. The district was chosen for three reasons.

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First, it is the district in which this researcher works as a district administrator. Secondly, this

district has a partnership with the large research university which is developing iSTART-Early,

the web-based reading strategy tutor. This research study helped to inform research on that tool.

Finally, because this study was also focused on essential text characteristics appropriate for

ethnically, linguistically and economically-challenged students, this district provided the

population necessary to carry out the research.

While small, the district is extremely diverse, with no one federal race category that

encompasses a wide majority of students. There are four elementary schools in this district that

serve a very ethnically, culturally, racially, and socio-economically diverse student body. At the

time this study took place, approximately 70% of the district’s elementary students were students

of color. The demographics follow in Table 3.1.

Table 3.1. District Demographics as of June, 2020

Federal Race Category

Percentage of District Students

American Indian

1.05%

Asian

5.45%

Black, Non-Hispanic

13.02%

Hawaiian/Pacific Islander

0.22%

Hispanic/Latino

39.71%

Two or More Races

10.37%

White

30.17%

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Of the elementary students in the district, 60.62% qualify for free- or reduced-price lunch (FRP),

with the number qualifying for free lunch approximately four times the number qualifying for

reduced-price lunch. English Learners (EL) comprise 33.1% of the elementary students in this

district, and 15.33% of the student body qualify for special education services.

The demographics for the district’s third and fourth grade cohorts are quite similar to the

overall district demographics. Table 3.2 below outlines the demographics for the district’s third

and fourth grade students.

Table 3.2. Demographics of Third and Fourth Grade Students as of June, 2020

Federal Race Category

Percentage of District Students

American Indian

0.88%

Asian

5.96%

Black, Non-Hispanic

14.91%

Hawaiian/Pacific Islander

0.35%

Hispanic/Latino

39.30%

Two or More Races

11.05%

White

37.54%

63.86% of the students in this grade band qualify for free- or reduced-priced lunch; 35.96% are

English Learners (EL), and 17.02% of the students in this grade band qualify for special

education services.

The large research university that is involved with developing the online comprehension

intervention tutoring tool, iSTART-Early, has partnered with this district in the past, largely

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because of the demographics of the students and the opportunity to conduct research that

contributes to the larger body of research on reading achievement of various demographic

groups. As discussed in Chapter Two, reading achievement continues to be largely predicted

along the lines of race and socioeconomic status, and thus research that focuses on achievement

of different demographic groups continues to be warranted.

The district’s reading achievement continues to be a persistent issue and, like the state

and the nation in general, continues to be largely predicted along the lines of race and

socioeconomic status. In 2019, elementary reading proficiency on the state standardized test at

grades 3 and 4 in the district was 40.7%, with a 30.5% proficiency gap between White students

and students of color. English language learners had the largest gap at 45.6 percentage points:

only 10.2% of the EL students were proficient, compared with 55.8% of the non-EL students.

With regard to socioeconomic status, 30.2% of the students qualifying for free- or reduced-price

lunch were proficient, compared with 61.9% of the non-FRP students, showing a 31.5 percentage

point gap. The smallest gap was realized in the area of special education, with a 29.1%

proficiency gap between students qualifying for special education services compared with their

general education peers: 15.6% of students on IEPs were proficient in reading compared with

44.7% proficiency for those students not identified for special education services (Minnesota

Report Card, 2020).

The research for this study took place during summer targeted services, known more

commonly as summer school. In this district, students are identified for summer targeted services

based upon achievement data in both math and reading, and are invited to participate in the

targeted services summer program. Summer targeted services are not mandatory in this district;

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therefore, parent consent for participation is required. Parents can opt their child(ren) out of

summer targeted services.

As a result of this “opt-out” system, the number of students participating in the summer

targeted services program from any one school are not necessarily a direct proportion of the total

number of students in that building, by race, ethnicity, socioeconomic status, or identified service

needs (e.g. special education or English Language [EL] services). A summer targeted services

coordinator, who is an in-district elementary teacher, was hired to work through the logistics of

the elementary summer programming and, in partnership with the classroom teachers,

communicated with families of those identified students in the spring, inviting their child(ren) to

participate in summer targeted services. This individual communication was especially important

in 2020, given the upheaval this district experienced as a result of a highly contagious virus.

Interruption to the Research Setting

The COVID-19 pandemic caused schools in this state to cease all face-to-face learning in

March of 2020, and turn to distance learning for the remainder of the school year. This was an

immense shift to educational practices in the district, as most elementary teachers had very little

experience in teaching from a distance. Prior to distance learning, the ratio of devices to students

was not one to one, and a large number of families in the district did not have devices suitable for

student learning in the home. Because the district did not have enough devices for every

elementary student, the district made plans to get a device to every household that needed one,

which meant that some students within one household shared a device for learning. Further, the

district identified households for which reliable access to the Internet, or any access to the

Internet, was an issue, providing hotspots it had on hand. Additionally, the district ordered as

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many additional hotspots as was available from vendors. This type of technology was in great

demand across the state and country, and much of the technology needed for remote learning was

backordered. Many households in the district had limited or no connectivity to the Internet.

Prior to the COVID-19 pandemic and the shift to distance learning, the district had 532

students in grades K-7 registered for the 2020 summer targeted services program. However,

because of the pandemic, this district, like all districts in the state, had to revise their traditional

summer targeted services programs. The traditional elementary summer targeted services

program for the participating district for this study was five weeks in length, four days a week,

6.5 hours a day (which included breakfast, lunch, and recess). This district revised its traditional

model, creating a choice of elementary summer programming. The first choice offered was a

fully-online elementary program where teachers would be instructing and students would be

learning in a synchronous setting, meaning that the students would be online interacting with the

teacher and each other live through video conferencing (in this case, Google Meet) as a group.

This type of learning is the opposite of an asynchronous learning environment, where students

are engaging in online learning at different times with no instructor present, sometimes watching

pre-recorded videos of the teacher facilitating the lesson, interacting with students through

discussion boards or contributing their comments in others’ documents.

The second choice offered was an in-person option which could accommodate 14

classrooms of nine students each in grades K-4, to comply with mandated social distancing. The

district prioritized certain students for the in-person model of summer targeted services; the

coordinator of the program looked at those students for whom life circumstances, such as limited

internet connectivity, or lack of engagement in the distance learning from March through early

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June, caused a greater interruption of their learning. The coordinator also obtained lists of those

students who did not engage in any online learning and just received physical learning materials

during the distance learning period, lists that were updated weekly by the elementary school

staff. She contacted each family individually to ascertain their preference.

A further change was in the length of the summer program. The program in both formats

was shortened to three weeks, rather than the typical duration in this district of five weeks. The

school day itself was shortened as well, from the typical 6.5 hour day to a four-hour day, which

included breakfast, a take-home lunch, recess, and a strong focus on socio-emotional learning for

the first hour of the day. However, the number of days a week remained consistent: a Monday

through Thursday format. Once these plans were finalized, the district summer targeted services

coordinator contacted parents and notified them of the changes in order to gauge their interest in

an online targeted services program versus an in-person summer program and to finalize

registrations.

Logistics and instruction for the two programs differed in several ways. Online

instruction was synchronous, meaning students and teachers were online at the same time for the

duration of each day. Students saw each other virtually; there were breaks built in, but no

breakfast was served. For the in-person program, there were up to nine students to a teacher, and

there were no support staff in the classrooms. Students were able to move about the room,

interacting with physical materials such as books and math manipulatives, and they were able to

interact with each other. In-person students received backpacks and their own school supplies,

which mitigated the need to share materials. In-person classrooms had instructional technology

at their fingertips, such as Smartboards, and teachers played calming background music during

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periods of independent practice. Students had a scheduled recess each day with one class outside

at a time.

The modified summer targeted services environment was not something students were

accustomed to experiencing in school; furthermore, the students had not been in school

physically for three months. Stickers on hallway floors helped students maintain proper distance

needed for social distancing when outside of the classroom. Desks in classrooms were placed at

least six feet apart. Staff were given face shields to wear. A mask mandate was declared in the

state during the second week of the program, and the district required staff to shift to wearing

masks indoors at all times, and masks worn by students were strongly encouraged, but not

required. However, students were asked to wear masks when in less than a six-foot proximity to

another person, and adults in the buildings worked with students to help them wear the masks

properly. The state mask mandate declared by the governor presented a new challenge for

in-person instruction, as it was impossible for students to see teachers’ mouths as they talked.

Additionally, voices were more muffled, many students had a hard time keeping masks on, and

the masks presented a distraction when students were wearing them.

The change to in-person and virtual summer targeted services forced the researcher to

choose which group of students were to be studied, as the two environments would provide

vastly different learning experiences for the students. Therefore, for purposes of this study, the

researcher chose to utilize the in-person summer targeted services program in order to physically

observe the students interacting with the texts. The demographic breakdown of the 2020

in-person summer targeted services program participants is described below.

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Overall and In-Person Student Participation in Summer Targeted Services

The district elementary summer targeted services program registered 255 students to

participate in both elementary summer programs (distance-learning and in-person). Students

identified for inclusion in this study were students participating in the district summer targeted

services program who had been identified, through district standardized assessment data, as

reading below grade level. Data for identification included a student’s overall Rasch Unit (RIT

score) on the fall Northwest Education Association (NWEA) Measures of Academic Progress

(MAP) reading assessment. Students whose RIT scores were below grade level mean on the fall

assessment were identified for inclusion in the summer targeted services program. Grade 4

students were identified through the use of results from both the MAP reading assessment and

preliminary results of the Minnesota Comprehensive Assessment (MCA-III) reading assessment

that is required beginning in spring of grade 3, but for which official results are not available

until late summer of the year in which it is given. Students who scored in the ranges of partially

meets or does not meet on the MCA-III were identified for inclusion in the summer targeted

services program.

Because of the COVID-19 pandemic, it was determined by the district that further

prioritization of students had to take place, due to limited space for in-person learning. First

priority for in-person summer targeted services went to English learners, students who were

designated as free- and reduced-price lunch students, and students who had been flagged by

teachers, administrators, and/or families as having struggled in distance learning. Participating in

summer targeted services programs in the participating district is not mandatory, meaning that

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families may choose to have their children participate or not participate. Because of the

COVID-19 pandemic, the district offered a choice of in-person participation or distance-learning.

47.06% of the enrolled summer targeted services students participated in in-person learning.

Table 3.3 breaks down the enrollment by federal ethnic/racial designation, Limited English

Proficiency, and Free- and Reduced-Price status:

Table 3.3. Demographics of Student Participants in Summer Targeted Services

Federal Category

# of Participants

Percent of Total

American Indian or Alaska Native

.39

Asian

7.06

Black/African American

13.33

Hispanic/Latino

152

59.61

Native Hawaiian or Pacific Islander

.78

Two or More Races

5.10

White

13.72

Limited English Proficiency (LEP)

153

60.0%

Free- and Reduced-Price Status (FRP)

198

77.6%

Because this research study was part of larger, national research that will lead to the

creation of an online comprehension intervention tutoring tool for third and fourth grade

students, this study focused solely on students in grades 3 and 4; therefore additional analysis of

the data was warranted for those two grades specifically. Of the 255 total participants in the

summer targeted services program, 55 students were in grade 3 and 33 students were in grade 4.

Summer targeted services enrollment data specific to grade 3 and 4 was as follows:

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● Grade 3: of the 33 total students registered for both in-person and

distance-learning, four students dropped, and 14 of 29 remaining participated in

the on-site program, for a 48.3% on-site participation

● Grade 4: of the 55 total students registered, 11 students dropped, and 18 of 44

remaining students participated in the on-site program, for a 40.9% on-site

participation

As a result of these numbers, there were three classrooms of students in grade 3 (one was a

combined grades 2 and 3 classroom due to space constraints) and two classrooms of students in

grade 4. Table 3.4 below delineates the participation in summer targeted services for these two

grades.

Table 3.4. Grade 3 and 4 Students’ Participation in On-Site Programming

Grade

# of Participants in

Person

# of Total Enrollment

% of Total Enrollment*

40.9

48.3

* Four on-site drops constituted 10.68% of total enrollment

The research for this study made use of in-person participation only, as the researcher

wanted to physically observe the students interacting with texts, and wanted to interview the

students in person at the end of the quantitative phase of the study. Further, the researcher had

more control over the environment in which the student would be interacting with the online text.

Finally, the in-person environment provided the only opportunity for students to engage in

science texts that had been written based on the qualitative data provided by the teacher focus

groups with regard to essential characteristics of informational texts - in this case, texts written

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about science topics aligned to third and fourth grade state science standards. Because the

students were attending school in person, the district technology department was able to batch

upload the Qualtrics tool created for this study onto each computer assigned to the participating

student.

In order to conduct this study, several steps were taken in preparation. First, this

researcher contacted the summer targeted services coordinator. Through conversation, she

explained the study and what effect, if any, it would have on teachers’ plans; she also obtained

the names of the teachers who were going to be teaching students in grades 3 and 4. Next, she

contacted those teachers and obtained permission to conduct the study in their classrooms,

explaining her methodology and timeline. All teachers eagerly granted their permission. The

third step included contacting district technology staff to ensure that the Qualtrics tool could be

loaded on to student devices, and that students would be using the same device every day (which,

of course, they were because of the limited sharing of materials due to COVID-19), and obtained

confirmation that the district technology staff would load the texts onto the specific

Chromebooks to which individual students were assigned and that students were using in the

in-person environment. The final step was to communicate with the teachers and finalize a

schedule whereby the research could take place with no disruption to the teacher or classroom

schedule. This research would take place within two of the three weeks of summer targeted

services, after the teacher established a community of learners and students settled into in-person

learning, something they had not engaged in since mid-March.

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Demographics of In-Person Student Participation in Summer Targeted Services

There were 255 elementary students registered for summer targeted services in the

district in 2020. Of those 255 students, 120 of them, or 47.06%, opted for in-person learning,

which is less than half of the total elementary students enrolled. From that pool of 120 students,

17 were dropped; either they never attended or were dropped from the roster for various reasons

once summer targeted services began.

Table 3.5 below shows the demographic breakdown of the total number of students

participating in the district in-person elementary summer targeted services program.

Table 3.5. Demographics of In-Person Student Participants in Summer Targeted Services, June,

2020

Federal Category

# of Participants

In Person

% of Total in

Person Enrollment

% of Total

Enrollment

(both Distance

and In-Person)

American Indian or Alaska

Native

Asian

5.83%

2.75

Black/African American

13.33%

6.27

Hispanic/Latino

64.17%

30.20

Native Hawaiian or Pacific

Islander

Two or More Races

1.67%

.78

White

15.0

7.06

Limited English Proficiency

(LEP)

63.3%

29.8%

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Free- and Reduced-Price

Status

103

85.8%

40.4%

Human Subject Review

Institutional Review Board

For the purposes of this study, three Institutional Review Board (IRB) approvals were

required. The first IRB was with a large research university that will utilize the data and results

from this study in their federally-funded research project to develop the final comprehension

intervention for use with third and fourth grade readers. The district in which this study took

place had an existing IRB with the large research university. However, because the data and

results of this study will be used in the larger research project, this researcher was required to

obtain IRB approval with the large research university, which was obtained after the required

training with that institution. This IRB dovetailed with the approved IRB obtained by the large

research institution for future creation of the final online comprehension tutoring tool. The

second IRB approval was with the school district itself. The third IRB approval was through the

university in which this researcher was earning her doctorate in education.

Because this research study was an iterative mixed-methods study, it is best to discuss the

methodology used for data collection in two phases. The first phase, helping to inform the first

research question, concentrated on text creation.

Study 1: Data Collection with Teachers To Inform Text Creation

Stated previously, this was a mixed-methods study utilizing design-based implementation

research (DBIR). Therefore, data collection followed iterative cycles, beginning simultaneously

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with the gathering of qualitative data from the teacher participants and the creation of an initial

corpus of texts that would be used to guide the discussion. This discussion, and the creation of

the texts themselves, contributed to the exploration of not only the first research question of this

study, but also of the first sub-question for this study:

What are essential text characteristics (length, readability, structure, cohesion, topics) for

the selection of informational texts that can be used for teaching reading comprehension

strategies, such as paraphrasing, self-explanation, summarization, and question asking, in

a digital format?

It was imperative to the researcher that she begin this research with a strong understanding of

what teachers and literacy experts believe are important characteristics of texts used in literacy

instruction. Qualitative research, according to Cresswell and Cresswell (2018), “is an approach

for exploring and understanding the meaning individuals or groups ascribe to a social or human

problem” (p. 4).

To assist in answering the first research question, this mixed-methods approach provided

evidence, utilizing quantitative data from the creation of texts to gather qualitative focus group

data from the practitioners themselves - the teachers and literacy experts in the district. Their

work relies on high-quality intervention and their work will be more deeply informed by

understanding how those interventions work with students in order to create sustainable change

in practice and, ultimately, in student reading achievement. The voice and expertise of this cadre

of teachers were needed to guide the creation of the texts that would ultimately be used with the

students who participated in this study. The set of short texts that a team of researchers created

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for the focus to read prior to meeting was necessary to ground the discussion in common texts

that all could discuss.

Teacher Participants in the Research Study

Design-based implementation (DBIR) research includes involvement of all those who

will be involved in implementation. Thus, it was imperative to gather qualitative data from the

teacher practitioner perspective on informational texts to be used with students. This researcher,

therefore, sought to bring a group of teachers together from the district in which this study was

conducted to form a focus group.

Specific criteria for participation in this study required any participating teacher to have a

background and school role related to literacy and instruction, to be between the ages of 18 and

75, to be an employee of the district in which the study took place, and to currently be providing

classroom instruction or reading intervention to children in grades three or four, or providing

literacy coaching to teachers. The researcher, through email communication, invited all

qualifying current grades 3 and 4 teachers, elementary instructional coaches, and elementary

reading interventionists in the district to be part of the focus group. This researcher was looking

to recruit approximately 8-12 members. Participation in the focus group was voluntary, and was

communicated very clearly as such. The problem that would be discussed during the focus group

meeting was the low reading achievement of the students in the district, and the particular focus

was on comprehension of informational text and characteristics of informational text that can

enhance or impede comprehension, given the review of the literature outlining the need for

explicit reading instruction using informational text.

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A total of eight staff volunteered to be part of this focus group: seven staff identified as

female and one staff member identified as male. The eight volunteers were then sent a Google

Form with questions that were created to ascertain demographic information, level of education

obtained, and number of years of service, as well as their role in the district. To reiterate, the

adult participants for the teacher focus group consisted of teachers, reading interventionists, and

literacy experts in elementary schools in the district.

One teacher focus group participant identified as a person of color and Hispanic. The

other seven participants identified as White. All participants had been teaching in the district for

at least three years. Three of the focus group participants were fluent in the Spanish language,

with one focus group participant being a native Spanish speaker. The teachers were verified as

teachers of record by the researcher through contact with the district’s Human Resources

Department. Further, all participants were teachers the researcher knew well and with whom she

interacted on a regular basis.

Prior to the first virtual meeting, the researcher sent, via email, initial questions with

regard to demographics, years in education, and educational attainment of those who were

participating in the teacher focus group. The results of this questionnaire are found in Appendix

A. The use of email was appropriate for this part of data gathering, because the use of email is

commonplace in the district for communication that is important, but not urgent. All

communication to the focus group members prior to the first meeting was done via email. The

work of the teacher focus group would concentrate on characteristics of texts, helping to answer

the first research question, What are the essential characteristics of informational texts that can

be used for training reading comprehension strategies in order to improve the reading

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comprehension skills of diverse third and fourth grade students? The group provided data which

was used to create informational texts that were ultimately used by the student participants in this

study. In order to gather that focus group data, however, an initial corpus of texts were created to

be read and used in the focus group discussion.

Focus Group Materials

In preparation for the work of the focus group, a set of short texts were created by a

group of writers hired by the large research university which is developing iSTART-Early. For

the purposes of this study, the texts created were informational texts focusing on science

concepts taught at grades 3 and 4. These science concepts were identified and chosen by the

researcher, who is a district curriculum administrator with 25 years of experience working with

state and local standards. These concepts also aligned with the 2019 state academic standards in

Science. An example of such a standard in third grade is the following:

3L.4.2.1.1 Obtain information from various types of media to support an argument that

plants and animals have internal and external structures that function to support survival,

growth, behavior, and reproduction . . . Examples of structures may include thorns, stems,

roots, colored petals, heart, stomach, lungs, brain and skin. Examples of media may

include electronic sources (Minnesota Department of Education, 2019, p. 15).

Once the standards-aligned concepts were identified, the commissioned writers then began

creating an initial corpus of expository texts based upon what was deemed essential in terms of

content, themes, structures, and interest. There were six general, standards-aligned scientific

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themes outlined, with approximately 9-12 texts written under each theme, for a total of 67 texts.

All 67 texts written were analyzed through the use of a Natural Language Processor (NLP) tool.

Natural Language Processing (NLP) Analysis of Texts

To further explore both the first research question, What are the essential characteristics

of informational texts that can be used for training reading comprehension strategies in order to

improve the reading comprehension skills of diverse third and fourth grade students and to

continue to explore the first sub-question, “What are essential text characteristics (length,

readability, structure, cohesion, topics) for the selection of informational texts that can be used

for teaching reading comprehension strategies, such as paraphrasing, self-explanation,

summarization, and question asking, in a digital format?” a set of texts with different levels that

were appropriate for this study were created. To do this, a Natural Language Processing (NLP)

tool with pre-populated indices was used. The tool used was the Coh-Metrix Common Core Text

Ease and Readability Assessor, or T.E.R.A. (Jackson, Allen, & McNamara, 2016), a

computational tool that uses natural language processing to produce indices of the linguistic and

connected discourse representations of a text. Written text is considered discourse because its

ideas are unified, it has purpose, and is connected logically (van Dijk & Kintsch, 1983).

The Coh-Metrix T.E.R.A. analyzes a text on five components: narrativity, syntactic

simplicity, referential cohesion, deep cohesion, and word concreteness (Jackson, Allen, &

McNamara, 2016). The Coh-Metrix T.E.R.A. tool informs writers (and teachers) of which

components of a text are less cohesive, so that writers can revise the texts to make the reading

easier, and teachers can work with students to help them recognize parts of texts that are less

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cohesive and to build skills to overcome the obstacles that are naturally found in less cohesive

texts. In addition, T.E.R.A. utilizes Flesch-Kincaid Grade Level Readability formula to identify a

Flesch-Kincaid score (FK), which is a single dimension of text difficulty relative to grade level

or the reading level of the student. This score can be very useful when assigning texts to students

with varying reading levels (Graesser, McNamara, & Kulikowich, 2011; Jackson, Allen, &

McNamara, 2016). The Flesch-Kincaid Reading Ease score is determined by sentence length and

word length (numbers of letters in the words).

The Coh-Metrix T.E.R.A. calculates a number of linguistic indices related to various

aspects of language that can be used to determine the quality, readability, or other specific

properties of a written or spoken text. The system analyzes multiple levels and factors of texts in

order to provide a multi-dimensional perspective of the text. The Coh-Metrix T.E.R.A. selects a

set of those indices relevant for classroom texts. To illustrate, Coh-Metrix measures simple

indices such as word frequency and sentence length as well as more complex indices, such as

cohesion, and syntactic simplicity and complexity. Cohesion refers to the way the words within a

sentence, and sentences themselves tie together (Jackson, et al., 2016). Syntactic simplicity and

complexity refers to numbers of clauses, numbers of words in sentences, and the number of

words used before the main verb in the sentence. The lower these numbers, the higher the

Coh-Metrix score, and the easier the text is to read (Jackson, et al., 2016).

Coh-Metrix has been used to analyze texts for multiple educational tutoring systems and

for a variety of purposes (McNamara et al., 2014). Though there are a multitude of indices

produced by this tool, not all were relevant to this study. All indices relevant to reading

comprehension are listed in Appendix B, but for the purposes of this study, six were determined

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by the Principal Investigator of the iSTART-Early project and the university researchers to be

appropriate for use. They include narrativity, syntactic simplicity, referential cohesion, deep

cohesion, word concreteness, and the Flesch-Kincaid reading ease score (RDFRE), to allow for

the eventual adaptability of the web-based comprehension intervention tool. The data on the

complexity of each text used for this study is outlined in Appendix C.

The Coh-Metrix tool provided information on all of the texts in order to determine which

of the corpus of texts were appropriate for this study. Of the 67 texts written, 23 were ultimately

chosen to bring to the focus group, based upon having a Flesch-Kincaid Grade Level Readability

score of <6.0, meaning that all texts were at or below a fifth grade reading level. Those 23 texts

were sent to the focus group ahead of the focus group meeting. The participants of the focus

group were asked to read through the short texts in preparation for the meeting.

Focus Group Discussion

Prior to the group meeting, the researcher prepared questions (see Appendix D) to help

facilitate the discussion. Those questions formed the foundation of the focus group conversation,

with additional questions being asked based on the context of the discussion. The group

members had widely varying educational experiences and backgrounds; therefore, it was

important to the researcher that the conversation felt organic and that the members could add to

and build upon one another’s thoughts. The discussion was focused on the texts with which

students typically engage in the classroom.

Because of the COVID-19 pandemic, the focus group took place virtually, using Google

Meets. The meeting lasted approximately 65 minutes and was recorded. Additionally the

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researcher took observational notes as the focus group conversation unfolded. The researcher

acted as facilitator.

Members of this group worked together on identifying the core parameters for

informational text development and selection. Creating and using a set of guiding questions for

discussion, and keeping questions open-ended, invited the group members to build off of each

others’ thoughts. Leaving room for spontaneous follow-up questions based on answers given

provided a better understanding as to how the teachers and literacy experts viewed texts and

instruction, and what they valued in the texts themselves. The focus group helped to formulate

the parameters that encapsulated the essential characteristics of informational texts: content,

themes, text structures with regard syntactic structure (e.g. sentence length and placement of

words within a sentence), the interests of the students, and the developmental appropriateness of

such texts with regard to third and fourth graders. Scientific themes for the texts themselves were

determined in tandem with text characteristics.

Knowing the curriculum and the diversity of the population of students in the district,

including their ethnicity, socioeconomic status and native language, the focus group confirmed

the texts’ alignment to grade level standards that had previously been chosen by the researcher,

and also whether the topics of the texts were engaging to students in the third and fourth grade

age group, based on the group’s prior experiences with the variety of students in that age group.

After the meeting ended, the recording was transcribed and coded for broad categories

and themes. The focus group meeting was recorded on Google Meet, a transcription was created

from that recording, and notes were taken during the discussion. The qualitative data collected as

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a result of the group discussion was coded authentically for themes. No themes were identified

by the researcher prior to coding.

The researcher identified overarching categories of the focus group responses specifically

with regard to feedback on the created texts. This information was sent to the team ultimately

responsible for creating the comprehension intervention tool, and was also sent to the team of

writers responsible for creating the texts for this study. The cadre of writers utilized the feedback

and made ample revisions to the texts. hence the iterative nature of this phase of qualitative

research.

Once revision was done, the texts were again scored using the Coh-Metrix Common Core

Text Ease and Readability Assessor (T.E.R.A., Jackson, Allen, & McNamara, 2016). The

decision was made by the larger research university to choose the topics of animals, outer space,

human body, and geological catastrophes. Once the topics were identified, the two texts with the

lowest Flesch-Kincaid scores per topic were chosen to be tested by the student population, for a

total of eight texts. The range of readability of those eight texts was 2.7 (second grade, seventh

month) to 5.5 (fifth grade, fifth month). See Appendix C for a detailed analysis of the eight

texts.

The eight texts were loaded into Qualtrics, which is an online tool used for many

purposes, including surveys, evaluations, and higher education research. They were presented to

the students in order from easiest to most difficult. However, before the students interacted with

the texts, it was paramount to collect data from the students to better understand the students'

attitude toward reading in general, and their basic understanding of grade level science concepts.

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This data would be triangulated with the data collected from the interaction with the texts in

order to help answer not only the main research question but the sub-questions as well.

Study 2: Data Collection with Students To Inform Text Development

The main objective of this research study was to identify essential characteristics of texts

that can be used to train reading comprehension strategies in order to improve the reading

comprehension of a diverse population of third and fourth grade students. To guide that research,

a third sub-question was created:

● What are additional considerations when selecting appropriate texts for (a) a

racially and ethnically diverse population of third and fourth grade students and/or

(b) students who read below grade level?

The term diverse, like many words in the English language, has multiple meanings. For the

purposes of this study, the researcher used the Cambridge Dictionary’s first definition of the

term: “including many different types of people or things” (diverse, n.d.). This research study

focused on students of color (SoC) and English Language Learners (ELs) who were below grade

level in reading, as their reading achievement is continually lower than those of their White,

native English-speaking peers (National Center for Education Statistics, 2019; Minnesota

Department of Education, 2020). The students who participated in this research study are

discussed in the next section.

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Student Participants in the Research Study

The iSTART-Early intervention tool, once created, will focus on comprehension

intervention for students in grades 3 and 4. Because this study’s results contributed to the corpus

of research that informed the ultimate creation of iSTART-Early, the students participating in this

study were required to be in grades 3 or 4. There were two classes of grade 3 students, two

classes of grade 4 students, and one class of grades 2 and 3 students combined, which was due to

the limits to class size. Children with significant cognitive disabilities, sensory impairments

(blind/visually impaired or deaf/hard of hearing), or children who did not have sufficient English

language skills (below WIDA Level 3) to be able to engage with English texts and respond to

instructions given in English were excluded from the study. All student participants were

identified by the district as achieving below grade level proficiency in reading at grades 3 and 4.

This researcher visited every classroom, introduced herself and the purpose of the study,

and handed out the Informed Consent to Participate forms, which were written in English and

translated into Spanish. Of those 33 students, 19 obtained parental consent to participate in this

study, for an initial 57.6% participation rate. The demographic breakdown of students is shown

in Table 3.6 below.

Table 3.6. Research Study Student Participant Demographics

Federal Category

Grade 3

Grade 4

Gender

Male

Female

Ethnicity

Asian

Black/

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African American

Hispanic

EL Status

Free/

Reduced-

Price Lunch Status

Free

Reduced

None

Throughout the duration of the on-site research, student absenteeism was an issue. While

the number of students originally providing consent to participate was 19, that number slowly

dwindled throughout the week. Data collected for the purposes of this study was not consistent

across the entire population of students, with only 11 students attending the final day of the data

collection to interview on their experiences in the study. As this was a mixed-methods study

utilizing design-based implementation research (DBIR), data collection followed iterative cycles,

and both teacher data and student data was needed. It was important to understand the role

student efficacy as it relates to reading, as research continues to show that reading self-efficacy is

both a contributor to and a predictor of successful reading comprehension (Guthrie, et al., 2007;

Ortlieb & Schotz, 2020; Solheim, 2011). Therefore, this study used two tools to gain a deeper

understanding of what the participating students believed of themselves when it came to reading.

The first tool used was a reading attitude survey.

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Elementary Reading Attitude Survey Data Collection

Students’ attitude toward reading has an effect on reading achievement (McKenna,

Conradi, Lawrence, Jang, & Meyer, 2012; McKenna, et al., 1995; McKenna & Kear, 1990;

Petscher, 2010; Smith, 1990, Varuzza, et al., 2014; Wade, 2012; Walberg & Tsai, 1985). Further,

a review of the literature showed that there is a difference in reading attitude based on gender and

language, two important areas of interest for this study (Akbari, et al., 2017; Logan & Johnston,

2009; Martínez, et al., 2008; McKenna, et al., 2012; Mohd-Asraf & Abdullah, 2016). Therefore,

it was prudent to collect data on the participating students’ attitudes toward reading.

To collect reading attitude data, the researcher administered to each participating student

the Elementary Reading Attitude Survey (ERAS, McKenna & Kear, 1990; 1999), which is a tool

that measures both recreational and academic reading attitudes. This instrument was chosen for

this study for several reasons. First, it has a large normative frame of reference; it is valid and

reliable, with reliability coefficients ranging from .74 to .89; of the 18 coefficients computed, 16

were at least .80 (Martinez, Aricak & Jewell, 2008; McKenna, Kear & Ellsworth, 1995;

McKenna & Kear, 1990). The ERAS is a 20-item pictorial rating scale which uses a Likert-type

scale of four possible responses, called nodes. The pictorial format uses the image of the cartoon

character Garfield the Cat, appealing to younger students, for the nodes. All items have a short,

simply-worded question about reading, which is followed by four pictures of Garfield ranging

from very happy to very angry, which pictorially represent feelings in the range from very

positive to very negative. Each mode is then assigned 1, 2, 3 or 4 points, with a 1 indicating the

most negative and a 4 indicating the most positive. The use of an even number of nodes

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eliminates the possibility of a neutral, or non-committal response (MeKenna, Kear & Ellsworth,

1995). The survey takes approximately ten minutes to administer.

The 20 items are broken into two 10-item subscales measuring recreational reading and

academic reading attitudes. Therefore, each participating student received three scores: one for

recreational reading, one for academic reading, and one for total reading attitude. The assessment

provides general characterizations of reading attitude on those two dimensions (recreational and

academic) as well as a total reading attitude score. The scores were also reported as percentages.

The data was analyzed to find mean and standard deviation, in order to gain

understanding of the significance between the students’ attitudes toward the two types of

reading. As the review of the literature shows that girls have a more positive attitude toward

reading than do boys (Logan & Johnston, 2009; Martínez, et al., 2008; McKenna, et al., 2012;

Mohd-Asrat & Abdullah, 2016), this data was further disaggregated by gender. Once the

researcher administered the Elementary Reading Attitude Survey, she came back to the

classrooms on a different day to gather data on general science knowledge.

General Science Knowledge Data Collection

The researcher determined that a base understanding of student grade level science

knowledge was warranted. Due to time constraints with the students because of the altered

summer targeted services program day, and the suspension of the state standardized testing in the

spring, the decision was made to assess the students on their knowledge of grade level science

standards using a modified yet appropriate version of the fourth grade NAEP Science

Assessment (National Assessment for Educational Progress, 2009, see Appendix E), which was

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created by the research team at the large research university overseeing the iSTART-Early

research. Questions on this pre-assessment correlated with the themes of the texts students read.

There were eight questions on the assessment, and students earned one point for each correct

response. The scores were reported as percentages, and analyzed to find mean and standard

deviation.

Again, the assessment took little time to administer. However, some students struggled

with reading the assessment. Since the goal of the assessment was an overall understanding of

students’ science knowledge, and not an assessment of reading skill, both teachers and the

researcher helped students who were struggling to read the assessment, which is not uncommon.

Of the 17 students who took the science assessment, four needed help reading some of the items.

This totaled 23.5% of the students taking the assessment. As is discussed in Chapter 5, this

finding has implications for future research and practice in the classroom.

The disaggregated data from both the ERAS and the science assessment were used

alongside the analysis of the students’ paraphrasing results, to better understand the students’

comprehension of the texts. To gather the paraphrasing data, it was next necessary to have the

students read the texts that were created for this study and use a strategy to paraphrase sentences

that would help the researcher better understand the students’ comprehension.

Data Collection on Text Reading and Paraphrasing

The central research question for this study focused on essential characteristics of

informational texts that can be used for training reading comprehension strategies in order to

improve the reading comprehension of diverse third and fourth grade students. That question is

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further guided by a sub-question focusing on specific text characteristics, including length,

readability, structure, cohesion, and topics that can be used for teaching reading strategies. To

gain a deeper understanding of the role of text characteristics in successful reading

comprehension, students engaged in reading and paraphrasing the texts created for this study.

The eight revised texts from the original corpus of 23 were loaded into Qualtrics, which

is an online tool used for many purposes, including surveys, evaluations, and higher education

research. This tool in particular was used because it could somewhat simulate the experience that

the ultimate web-based tutoring tool, once developed, will provide. As mentioned previously the

texts were loaded from easiest to most difficult; this is an important point to emphasize, as no

student got through all eight texts. The third and fourth grade student participants read these texts

during the summer targeted services day and paraphrased predetermined target sentences

throughout each text. The students typed their paraphrases into the Qualtrics tool at

predetermined times throughout each text. The sentences to be paraphrased were chosen by the

Principal Investigator for the iSTART-Early project, who is a nationally recognized expert in

reading comprehension, cognition, linguistics, and learning.

Prior to the students actually reading and paraphrasing the texts, the students needed to

learn a paraphrasing strategy. Because of the COVID-19 pandemic and resulting modification of

the summer targeted services program, this researcher had limited time with the students to teach

them a paraphrasing strategy. Therefore, the researchers at the large university created a short,

student-friendly instructional video that students individually watched on their computer and

could access at will throughout this portion of the research study.

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The video was four minutes, eight seconds in length and used what Roehler and Duffy

(1984) explained as direct explanations of comprehension processes. The video explained, in

student-friendly language, what paraphrasing was and listed four strategies that one can use to

paraphrase. Further, the video provided modeling of each of the strategies and provided wait

time so students could think about the sentences and practice. This wait time provided the

students time to think about words they could use, prior to the narrator continuing the

explanation of the strategy. This researcher, along with the staff at the large university, deemed

that the length and the pace of the instructional video was appropriate for students this age.

After watching the video, the students then began to read subsets of the texts developed

and engaged in paraphrasing specific target sentences throughout each text. Understanding the

students’ engagement in the tasks was warranted, as the Construction-Integration (C-I) model of

reading illustrates that the act reading is a relationship between the reader, text, context and

situation (C-I; Kintsch & van Dijk, 1978; Kintsch, 1983; Snow, 2002). Therefore, observation of

the students actually reading and paraphrasing was critical to this study.

The researcher, using a modified observation form (Kendeou & McMaster, 2016, see

Appendix F), informally observed students watching the instructional video and reading and

paraphrasing the texts. This observation form provided quantitative data on the number of

observations made regarding four tasks in which the students engaged. The tasks identified for

this study included reading, paraphrasing, engaging in a vocabulary task (such as trying to figure

out the meaning of a word), or “other” - an act that did not have anything to do with the texts

themselves, including watching the instructional video. This quantitative data was analyzed to

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find mean and standard deviation, and to gain understanding of the significance between

different tasks in which students were engaged.

Additionally, qualitative observational notes were taken on each student during each

session. The researcher took narrative notes on the behaviors of the students, including

frustration and how the student worked through that frustration, engagement, or off-task

behaviors. The quantitative data provided the researcher data on the students’ time spent on

various tasks; the qualitative observational data collected provided the researcher with real-time

narrative data on student behaviors, perceived attitudes, struggles, and engagement with the

tasks.

Observation of students engaged in reading and paraphrasing the texts took place over the

course of a week, spending approximately one hour at a time in each classroom at a time during

the students’ literacy block. During this time, those students not participating in the study were

engaged in other reading tasks, most often independent reading - either online or with a printed

book. This schedule provided the most cohesive environment for all students - on the surface, all

students looked engaged in a similar activity, which this researcher deemed to be important to the

overall experiences of the students. At the end of the study, participating students received their

choice of a pencil and eraser as a reward for their efforts.

During the reading and paraphrasing of the texts themselves, students were asked to rate

each text after they read it, as students typically like some texts more than others. To rate the

text, a short, student-friendly survey tool was created and placed at the end of each text. This tool

included a short phrase and an accompanying emoticon. This tool provided information on what

students thought about each text they read, and what they thought about paraphrasing. Students

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were asked to rate the text for ease of reading and interest level (if they liked reading the text),

and ease of paraphrasing and interest level (whether they liked paraphrasing the sentences). To

do this, the following questions were asked:

● Did you like reading the text passage?

● How easy was it to read the text passage?

● Did you like paraphrasing the sentences?

● How easy was it to paraphrase the sentences?

Ratings were displayed on the screen both in written form and pictorially: for text ratings,

a green happy face stood for “I liked it!”; a yellow emotionless face stood for “It was okay.”; and

a red sad face stood for “I didn’t like it.” For paraphrase ratings, a green happy face stood for “It

was easy!”; a yellow emotionless face stood for “It was okay.”; and a red sad face stood for “It

was hard.” Students chose the icon that best matched their opinion. An analysis of the answers to

these questions provided additional information with regard to students’ interests, as ultimately

the web-based comprehension intervention tool, iSTART-Early, will need to be populated with

informational texts that match students interests, thus providing the opportunity for greater

motivation to read.

Next, the paraphrases themselves were analyzed in order to better understand the

students’ comprehension of the texts. The paraphrases produced by the students were scored

using a modified version of a rubric developed by McNamara and colleagues (2007a, see

Appendix G). This approach correlated with the first generative strategy used in the first module

of iSTART-Early, which is paraphrasing. This strategy provided information on how well the

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students comprehended the texts. A rubric was used to score the paraphrases, and the raters were

trained on the rubrics.

The paraphrases themselves were first filtered for any responses that were irrelevant, too

short, or direct copies or clause reversals of the target sentences. Remaining paraphrases were

dichotomously coded for the presence of eight different factors: paraphrase presence, lexical

similarity, syntactic similarity, semantic similarity, elaboration, inaccuracy, and other content.

Finally, paraphrases were scored on a scale of 0-2 for overall quality: 0 indicating a poor

paraphrase, 1 indicating the presence of paraphrase strategies but a need for improvement, and a

2 indicating a high quality paraphrase. Two researchers coded all responses separately, and then

met to create inter-rater reliability, coming to consensus on each code in order to determine final

scores.

Finally, every student who participated in the study was individually interviewed by the

researcher, in person, at the end of the quantitative phase of the study. The researcher asked the

same three questions of each student participant, and recorded their answers on a form. The three

questions are as follows (asked in order):

● Do you remember what paraphrasing is?

● How did you figure out how to paraphrase the sentences?

● Do you think paraphrasing helped you to read better? Why?

The length of each interview depended upon how well the student elaborated on each answer.

There were no follow-up questions. This researcher analyzed the qualitative data of each

response to provide additional information with regard to the impact of the study on each

student’s attitude toward their comprehension, their experience paraphrasing with an online

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science text, and their reading self-efficacy. Their explanations were analyzed to determine

overall themes in the use and effectiveness of paraphrasing in this setting, and its impact on their

identity as a reader in general.

Data Analysis

This study was designed to study text characteristics that were essential for use in reading

strategy instruction, specifically strategy training that will involve the creation of a strong

comprehension tutoring tool for third and fourth grade students struggling in reading. This

research study aimed to answer the question, What are the essential characteristics of

informational texts that can be used for training reading comprehension strategies in order to

improve the reading comprehension skills of diverse third and fourth grade students? This

question is further informed by asking the following sub-questions:

● What are essential text characteristics (length, readability, structure, cohesion,

topics) for the selection of informational texts that can be used for teaching

reading comprehension strategies, such as paraphrasing, self-explanation,

summarization, and question asking in a digital format?

● What are additional considerations when selecting appropriate texts for (a) a

racially and ethnically diverse population of third and fourth grade students and/or

(b) students who read below grade level?

To understand the role of informational texts used in comprehension intervention,

specifically with regard to the paraphrasing strategy used in this mixed-methods, iterative study,

it was important to gather and analyze multiple points of qualitative and quantitative data at

different points throughout the study, beginning with the texts themselves. Through the use of

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nationally-recognized and research-based readability tools, texts were created and underwent an

iterative process of quantitative analysis to ensure proper readability for students.

Qualitative data was obtained from practitioner (teacher) focus group conversations and

analyzed for broad themes and categories that were brought back to the text writers in order to

revise the student texts and to create the corpus of texts that were included in this study and used

by students to read and paraphrase. More qualitative data was collected from the participating

students at the end of the study and is discussed below.

A broad understanding of the students themselves required obtaining quantitative data

on the students prior to their engagement in the texts and the paraphrasing activity. A short

science pre-assessment, using a modified but appropriate version of the fourth grade NAEP

Science Assessment (National Assessment for Educational Progress, 2009, see Appendix E)

provided data on students’ basic science knowledge. It was scored and analyzed to find mean and

standard deviation. The questions on this pre-assessment correlated with the themes of the texts

students read and paraphrased. The Elementary Reading Attitude Survey (ERAS, McKenna &

Kear, 1990; 1999) was administered to students that provided data on reading attitude, which

research shows has an effect on reading achievement (McKenna, et al., 1995; Petscher, 2010;

Smith, 1990, Varuzza, et al., 2014; Wade, 2012; Walberg & Tsai, 1985). The survey measured

recreational and academic reading attitude separately, and also provided a total reading score.

This data was analyzed for reliability coefficient, and was also analyzed for mean and standard

deviation.

Observational data was gathered while students read the short texts and engaged in a

paraphrasing strategy in order to gauge their engagement in the reading and paraphrasing tasks.

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The observational data collected was both quantitative and qualitative. First, the system was

loaded onto each student computer, and students read the texts online, stopping to paraphrase

sentences. After each text was read, students answered a short set of questions about their

attitude toward the text and the act of paraphrasing. Using a modified observation form

(Kendeou & McMaster, 2016, see Appendix F), the researcher quantitatively observed the

students in four areas: reading, paraphrasing, engaging in some sort of a vocabulary activity

(such as trying to figure out the meaning of a word), or some other activity. This quantitative

data was analyzed to find mean and standard deviation, and to gain understanding of the

significance between the different tasks in which students were engaged. The researcher also

took narrative notes on the behaviors of the students, including frustration, engagement, or

off-task behaviors. This qualitative data was analyzed alongside the quantitative data from the

observation form to glean a deeper understanding of the student behavior in the four areas, such

as how a student worked through frustration when trying to figure out the meaning of a word.

The paraphrases themselves were scored using a coding rubric (see Appendix G).

Paraphrases were scored based on five criteria: whether or not the paraphrase was too short; a

copy/paste; a clause reversal; garbage, meaning it was gibberish; or irrelevant, meaning it had no

connection to the text. This methodology provided quantitative data from the results of students

engaged in paraphrasing short science texts and was analyzed for the length and quality of each

paraphrase, which correlated to the students’ understanding of and comprehension of the text.

Data was also obtained on how many texts students read and paraphrased.

The last data obtained was through a short, three-question interview with the final

participating students remaining in the summer targeted services program on their experience

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with paraphrasing, which provided qualitative data on each student’s experience and

understanding of paraphrasing, and how they felt as a reader as a result of the exercise. While

short, the responses were still coded for themes. No codes were identified prior to the analysis;

rather, they were identified authentically as a result of student answers and analyzed student by

student.

All of this data were triangulated in order to identify emerging patterns and themes, such

as the relationship between the qualitative data (e.g. whether or not the student liked the texts and

paraphrasing, and whether or not they thought paraphrasing made them a better reader) and the

quantitative data (e.g. paraphrasing scores, science assessment scores, and reading attitude

survey) in order to understand if the texts were appropriate for the web-based comprehension

intervention tool. The researcher used the data not only to help answer the research questions,

but also to understand the relationship between the results of this study and the review of the

literature to determine recommendations for future practice and research. Data obtained through

this study, including paraphrasing scores, science assessment scores, and reading attitude survey

results, were also analyzed and used within the larger study protocol.

For all data collection involving students, each student was given a numerical

identification, to which all data, both qualitative and quantitative, was assigned. This provided

the researcher with the ability to analyze the data at both a group and individual level, taking into

account student demographics, such as gender, race/ethnicity, language, grade level, and

socioeconomic status.

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Conclusion

The purpose of this chapter was to review and provide the rationale for the methods used

in this study, which was a mixed-methods research study to explore the role of informational

texts and specific components of reading comprehension while reading digitally. The

methodology chosen for this study delved into the impact of informational texts on reading

comprehension skills, and their essential characteristics with specific regard to comprehension

intervention in an online format for students in grades 3 and 4 who are at risk of reading

difficulties or already struggling in reading comprehension. This researcher examined

characteristics of informational texts that can lead to greater engagement in and comprehension

success with the reading content created for an online comprehension intervention, and taught

and used the paraphrasing strategy to determine that comprehension success.

A review of the literature detailed the fact that these two grades are a critical time in a

student’s literacy development, especially as demands on learning new content through reading

increase. Further, a detailed review of the literature confirmed that there is a continued,

pervasive, and large achievement gap between students of color, students of limited

socioeconomic means, and students for whom English is not their dominant language and their

White, middle class peers.

This study was part of a larger, federally-funded study to develop an online, automated

comprehension strategy tutor for students in grades 3 and 4, called the Interactive Strategy

Training for Active Reading and Thinking for Young Developing Readers, or iSTART-Early.

This tutor will ultimately support both teachers and students in the classroom, as teachers will be

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able to assign texts and monitor students’ comprehension progress. Therefore, this study focused

on the text characteristics of informative texts that will ultimately populate this tool, and how

students interfaced with the informative texts in an online format.

A detailed description of the participants and setting of this study, and a detailed

description of the creation of the texts used in the study was warranted for this chapter, as this

study was conducted in a very diverse school district with a large population of students of color,

students living in poverty, and English Language learners; additionally, the district had a large

percentage of students scoring partially proficient on the standards or not meeting standards, and

the district has a large achievement gap between their students of color and English Language

learners and their White, middle-class peers.

Finally, and unexpectedly, this chapter outlined what the effects that the COVID-19

pandemic, an unparalleled event in American education, and an unanticipated event with regard

to this research, had on the study itself. A thorough analysis of demographic data, teacher and

literacy expert focus group data, and student reading data was undertaken in order to identify

emerging themes. Chapter Four provides an in-depth analysis of the data as it relates to results.

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CHAPTER FOUR: ANALYSIS AND RESULTS

Our understanding of the human brain can be dramatically accelerated if we collect and share

research data on an exponentially wider scale.

-Tan Le

Introduction

The majority of students in grades 3 and 4, not only in the United States but in the district

in which this study took place, are not proficient readers as measured by national and state

standardized assessments (National Center for Education Statistics, 2019; Minnesota Department

of Education, 2020). These statistics are alarming, as this grade level band has been identified as

a critically important time period in young readers’ lives. They are being asked to learn content

from increasingly complex informational and expository texts, yet their exposure to and

instruction in these non-fiction texts has lagged (Beerwinkle, et al., 2018; Castles, Rastle, &

Nation, 2018; Chall, et al., 1990; Duke, 2000; Jeong, et. al., 2010; Strong, 2020). Further, as was

established previously through a review of the literature, there is an elusive and persistent gap in

reading achievement between White, middle-class students and students of color, students from

low socioeconomic families, and students for whom English is not their first language. The

researcher, herself being a former English language arts teacher and K-12 literacy director with

over 25 years in education, has witnessed firsthand students struggling to understand what they

are reading and has dedicated her work as an educator to eliminate reading achievement

disparities which are predictable across federal categories.

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One of the ways this researcher has tried to increase reading achievement for students has

been to seek and foster relationships with research institutions. She had the opportunity to

collaborate with a large research university to provide data that would aid in the eventual

creation of a web-based comprehension intervention, called iSTART-Early. This study was

designed to answer the following question: What are the essential characteristics of

informational texts that can be used for training reading comprehension strategies in order to

improve the reading comprehension skills of diverse third and fourth grade students?

Further, the main research question was guided by the following sub-questions:

● What are essential text characteristics (length, readability, structure, cohesion,

topics) for the selection of informational texts that can be used for teaching

reading comprehension strategies, such as paraphrasing, self-explanation,

summarization, and question asking, in a digital format?

● What are additional considerations when selecting appropriate texts for (a) a

racially and ethnically diverse population of third and fourth grade students and/or

(b) students who read below grade level?

This chapter presents the findings of the Design-based implementation research (DBIR)

and mixed methods research study designed to answer the research questions. Design-based

implementation research includes the active involvement of those who will ultimately be

implementing the strategy intervention which, for the purpose of this study, are third and fourth

grade teachers and their students. Data were collected in iterative phases. First, data collected

from the teachers were analyzed, and informed the creation of expository science texts that were

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read by students. The data collected from the students were analyzed to answer the research

questions.

The central question, What are the essential characteristics of informational texts that

can be used for training reading comprehension strategies in order to improve the reading

comprehension skills of diverse third and fourth grade students? was answered through multiple

stages of research in this study. The first phase began with the initial creation of a corpus of texts

prepared for the teacher focus group discussion. This work was done through collaboration with

this researcher and researchers at the large research university. The data collected from the focus

group were used to revise the initial corpus of texts in order to create a final set of texts for use

by the students in this study. Below is a discussion of the findings of this phase of the research.

Study 1: Data Analysis To Inform Text Creation

In the first phase of the study, the researcher obtained qualitative data from a focus group

made up of teachers and literacy experts on their experience with and opinions regarding

informational texts appropriate for use in grades three and four for strategy training. The focus

group members worked on identifying the core parameters for informational text development

and selection. This group read informational texts created specifically for this study that aligned

with state grade-level science standards. Members of the focus group provided feedback on the

texts, including their appropriate use with third and fourth grade students. Data from a

quantitative analysis of the initial set of texts were used to create the final corpus of eight texts

used with students in this study.

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Natural Language Processing (NLP) Analysis of Texts

The first stage of this study required that texts be created to populate a tool students

would use to read and show comprehension of the texts. These texts were created through an

iterative process. First, this researcher and several university researchers came together to

identify broad science themes that could be used to create texts aligned to state standards for

third and fourth grade. This researcher had strong knowledge of the state science standards and

was able to guide the university researchers through the standards to build understanding. Once

the topics were identified, writers created 67 initial texts based upon the identified science

themes. These writers were hired based upon their previous experience in writing, their previous

experience in a school setting with elementary students, or a combination of both experiences.

The initial corpus of texts written were analyzed by work count, Flesch-Kinkaid (FK)

scores, and Lexile range, as the developers of those texts knew that the texts would change as a

result of feedback. Those with FK scores greater than a score 6.0 were removed, as they would

have been too difficult for the students at these grade levels to read. This left a corpus of 23 texts,

which were presented to a focus group with eight members consisting of teachers, reading

interventionists, and literacy specialists. The group was asked to read the texts prior to the

convening of a virtual meeting to discuss the texts, and were given a week to read them. All of

the texts were short - approximately 400-650 words each. The virtual meeting took place via

video conferencing, in this case Google Meet, which was the district’s approved method of video

conferencing. Additional analysis of the 23 texts occurred after the focus group feedback. The

text titles and data on the 23 texts presented to the focus group are found in Table 4.1 below.

148

Table 4.1. Text Titles and Characteristics

Text Title

Word Count

Lexile Range

Flesch-Kincaid Score

Zoos & Humane

Treatment

363

610-800

5.9

Bioluminescence

310

410-600

5.3

Ostriches

358

410-600

3.7

Sloths

387

610-800

5.4

Starfish

397

410-600

3.8

Platypus

329

410-600

3.5

Avalanches

359

610-800

5.6

Quicksand

317

610-800

5.3

Wildfires

237

610-800

5.1

Flooding

384

810-1000

5.0

Using 10% of Brain

312

610-800

5.5

Eating Turkey

208

610-800

5.2

Eating Healthy

399

410-600

3.8

Blood

388

410-600

3.9

GroupThink

237

410-600

3.5

Venus

352

810-1000

6.0

Pluto

403

610-800

5.6

Meteors

372

610-800

4.8

The Universe

285

410-600

4.9

A Visit to Mars

361

410-600

2.8

How a Star is Born

243

410-600

2.8

149

Lightning

344

610-800

5.2

Magnets

231

610-800

5.3

Focus Group Qualitative Data Analysis

Because meeting as a group was not possible due to the COVID-19 pandemic, the

researcher convened the focus group via Google Meet. This video conferencing tool offers a

service whereby the meeting can be recorded; a copy of that recording is sent to the organizer of

the meet within a few hours after the meeting has ended. All teachers who volunteered to

participate were present in the meeting, they agreed to be recorded, and the meeting lasted

slightly over one hour.

During that meeting, participants discussed what they noticed in and about the texts. The

researcher had pre-planned questions (see Appendix D) to be used as conversation starters, but

additional questions were asked as a follow-up depending on the conversation that ensued, to

continue the engagement in the topic about grade level texts. This researcher recorded the

Google Meet and obtained a recording of it that she then transcribed. The transcription of the

meeting was analyzed for the emergence of overarching themes and categories, which were then

categorized. Table 4.2 below outlines the thematic categories, with the number of mentions for

each theme and percentage of total mentions for each theme, in descending order.

Table 4.2. Teacher Focus Group Themes

related to topic)

3.209

8.696

Total:

36.898

100

Paraphrase Numerical Coding.

The second phase took place once the filtering was completed. The remaining

paraphrases were dichotomously coded (using 0 or 1) for the presence of eight different factors:

paraphrase presence, lexical similarity, syntactic similarity, semantic similarity, elaboration,

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inaccuracy, or other content. For the categories of paraphrase presence, lexical similarity,

syntactic similarity, semantic similarity, and elaboration, a score of 1 meant that the particular

factor was present in the paraphrase, and a 0 meant that the particular factor was not present. For

inaccuracy and other content, a score of 0 meant a higher quality paraphrase, in that there was

either no inaccuracy or other content. Once the individual factors were scored, the paraphrases

were given an overall score on a scale of 0-2 for quality: 0 indicating a poor paraphrase, 1

indicating the presence of paraphrase strategies but a need for improvement, and a 2 indicating a

high quality paraphrase.

The third phase of scoring involved the creation of inter-rater reliability. Two researchers

from two different research institutions coded all paraphrases separately. They then met to

discuss their results in order to establish inter-rater reliability. They did so by resolving all

disagreements and differences and coming to consensus on each code in order to determine final

scores for each paraphrase generated by students. The paraphrase quality data are discussed in

the next section.

Paraphrase Quality Data.

The two researchers scored each paraphrase separately and came to consensus on each of

the paraphrase quality scores. This paraphrase quality data set is shown in Tables 4.15 below.

Table 4.15. Paraphrase Quality Score Data

Paraphrase Quality Score

Number of Paraphrases

Percentage of Paraphrases

12.834%

33.690%

186

16.578%

9 (paraphrases filtered out)

36.898%

Total

187

100%

This researcher disaggregated the paraphrase quality data by individual text, as the texts

were populated into Qualtrics in order of least to most difficult. This data set is shown in Table

4.16 below.

Table 4.16. Paraphrase Quality Data by Text

Text

Number and

Title

# of

Paraphrases

Scoring 2

# of

Paraphrases

Scoring 1

# of

Paraphrases

Scoring 0

# of

Paraphrases

Filtered

Total

Paraphrases

How A Star

Is Born

Eating

Healthy

A Visit to

Mars

Wildfires

Blood

Ostriches

Starfish

187

Because the texts were presented to students in order of easiest to most difficult, this

researcher predicted that the students would have the most success on the first text. As predicted,

Text 1, “How a Star is Born,” had the highest number of paraphrases generated (N=52), and the

highest number paraphrases earning a score of 2, 1, or 0 (N=35). Total paraphrases generated for

each text declined with each subsequent text, which is also predicted, given that the texts

increased in difficulty and many students stopped paraphrasing after the third text. An additional

five students stopped paraphrasing after the fourth text, and two students paraphrased seven

texts.

However, when looking at the percentages of paraphrases earning a score of 2, 1, or 0, “A

Visit to Mars,” which was the third text presented to students, had 71% of the total paraphrases

earning a score of 2, 1, 0, which was the highest percentage of the seven texts paraphrased by

students. “How a Star is Born,” the first text in the series, had 67% of its total paraphrases

earning a score of 2, 1, or 0. When analyzing the paraphrase quality by score (not filtered out),

“Wildfires,” which was Text 4, had the highest percentage of paraphrases earning a quality score

of 2, at 53%.

Interestingly, the two most difficult texts that students paraphrased, which were Texts 6

(“Ostriches”), and 7 (“Starfish”), generated 20 paraphrases total. However, half of those

paraphrases earned a score of 2 or 1. Additionally, two earned a paraphrase quality score of 2,

which is 20% of the total paraphrases for those texts, and eight earned a score of 1, which is 40%

of the total paraphrases generated for those two texts.

As the researcher continued to disaggregate data, it was important to analyze the student

behaviors with regard to paraphrase generation. Several interesting observations with regard to

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student paraphrase responses were noticed. First, as time went on, many students stopped trying

to create paraphrases. Some just started typing in nonsense, but many would just retype the

sentence verbatim (or change only a word or two). There were two students in particular that got

farther than their peers in paraphrasing; one completed 19 paraphrases and one completed 34 -

but for the later half of their responses, they were just retyping the sentences. They were able to

produce more answers because their typing did not get in the way, as it did for others.

There were two other students, however, who also completed 19 paraphrases and 34

paraphrases, and their paraphrase data was of higher quality than the other two students who

completed just as many. Utilizing the qualitative observational data gathered while students were

watching the instructional video, reading the texts, and paraphrasing the predetermined

sentences, the researcher observed that one of these two students watched the video more than

two times. The other student whose paraphrases were of higher quality worked through four texts

rather quickly and wanted to stop for the day on the first day of paraphrasing; however on the

next day that student began the task again.

There were two student participants in this study who did not submit even the first set of

paraphrases into Qualtrics. Therefore, Qualtrics was unable to capture data on those two

students. Each of the remaining 13 students’ paraphrase quality data are illustrated in Table 4.17

below.

Table 4.17. Paraphrase Quality Data By Student

Student

Grade

Gender

Total

Paraphrases

# Scoring 2

# Scoring 1

# Scoring 0

# Filtered

10001

189

10002

10003

10004

10005

10010

10012

10013

10014

10015

10016

10017

10018

Totals

187

The paraphrase quality data were further analyzed by grade level and gender. Because of

dwindling numbers in the in-person summer school targeted services program, the remaining

student participants were 100% English language learners (ELs), and all but one qualified for

free- or reduced-price lunch; there was no need for the data to be analyzed by those particular

strands. Therefore, the researcher next analyzed the data by gender first. This data set is

presented in Table 4.18 below.

Table 4.18. Paraphrase Quality Data by Gender

Gender

(% of

Total)

Total

Paraphrases

(%)

# Scoring 2

(%)

# Scoring

1(%)

# Scoring 0

(%)

# Filtered

(%)

Female

141 (75.4%)

16 (51.6%)

49 (76.6%)

16 (69.6%)

60 (87.0%)

190

(69.2%)

Male

(30.8%)

46 (24.6%)

15 (48.4%)

15 (23.4%)

7 (30.4%)

9 (13.0%)

Mean:

Female: 23.5

Male: 11.5

Female: 1.78

Male: 2.5

Female: 5.44

Male: 3.75

Female: 1.78

Male: 1.75

Female: 6.67

Male: 2.25

Female student participants made up 69% of the students on which the researcher was

able to gather paraphrase quality data. It would be logical, then, to assume that the girls would

generate more paraphrases, which they did. However, they outperformed the boys’ generation of

paraphrases slightly based on their numbers. Girls generated 75.4% of all paraphrases; the mean

paraphrase generation number for female participants was 23.5. Male student participants made

up 30.8% of the population, but they generated only 24.6% of all paraphrases. Mean paraphrase

generation number for male student participants was 11.5.

When looking at the paraphrase quality data, however, interesting observations were

made. Girls did not generate paraphrase quality scores of 2 commensurate with their numbers of

paraphrases generated. The female participants in this study generated 16 paraphrases that earned

a quality score of 2, which is 51.6% of all paraphrases earning that score. However, that number

constituted only 11.3% of the female paraphrases overall. The male participants generated 15

paraphrases earning a 2, or 48.4% of the total paraphrases earning that score. However, that

number constitutes 32.6%, or nearly one-third of the total paraphrases the male students

produced. They generated less paraphrases, which was predicted, given the fact that they only

made up approximately one-third of the student participants; however, they generated nearly half

of the paraphrases earning a quality score of 2.

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The female student participants earned a paraphrase quality score of 1 on 49 paraphrases,

which was 76.6% of the total paraphrases earning that score. Additionally, that number

constitutes 34.8% of all paraphrases generated by the girls. Their percentage of paraphrases

generated that earned a score of 1 (76.6%) is just slightly more than the percentage of total

paraphrases generated by the girls (75.4%). However, females made up only slightly more than

two-thirds of the total student participants in this study. Male student participants scored a 1 on

15 paraphrases, which was 23.4% of the total paraphrases earning this score; however, that

number constituted 32.6% of all paraphrases generated by the boys. Their percentage of

paraphrases generated that earned this score (23.4%) is nearly even with the percentage of total

paraphrases generated by the boys (24.6%). Girls outperformed the boys in paraphrases earning a

quality score of 1.

The female participants earned a paraphrase quality score of 0 on 16 paraphrases. This

number constitutes 69.6% of the 23 total paraphrases earning a score of 0, which is only 0.4% off

from the total percentage of female participants generating paraphrases in this study (69.2%).

Further, that number constitutes 11.3% of all paraphrases they generated. In this category, the

girls earned a score of 0 which is commensurate with their percentage of participation. The same

can be said about the performance of the male student participants earning a paraphrase quality

score of 0. The boys earned a quality score of 0 on 7 paraphrases, which is 30.4% of the total

paraphrases earning that score. The boys earned a score of 0, which is commensurate with their

percentage of participation. This number constituted 15.2% of the total paraphrases they

generated.

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With regard to the final category, the number of paraphrases that had been previously

filtered and therefore unscorable, the male student participants generated far less paraphrases that

were filtered than their female counterparts. The total number of paraphrases generated by the

male student participants was 9, or 13.0% of the total number of paraphrases filtered. This

percentage is over 17 percentage points lower than the percentage of male student participants

generating paraphrases in this study. Further, the number of paraphrases generated by males that

were filtered out contstituted 19.6% of all paraphrases they generated. Female student

participants, on the other hand, generated 60 paraphrases that were previously filtered out. This

number represents 87.0% of all paraphrases filtered prior to scoring, and is nearly18 percentage

points higher than the percentage of girls who generated paraphrases for this study. Further, that

number is 42.6% of all paraphrases the girls generated.

Overall, while females generated over three times as many paraphrases than males in this

study, 65.2% of the paraphrases that the males produced scored a 2 or a 1 for paraphrase quality,

compared to 46.1% of the paraphrases generated by the females earning those scores.

Conversely, females had a much higher number of paraphrases earning a score of 0 (69.6%) or

being filtered out prior to scoring (87%), than did the males’ paraphrases that earned those scores

(30.4% and 13%, respectively). While the number of paraphrases the males generated was lower

than that of the females, their paraphrases overall were stronger.

The paraphrase quality data was also disaggregated by grade level. That data set is found

in Table 4.19 below.

Table 4.19. Paraphrase Quality Data by Grade Level

193

Grade

Level

(% of

Total)

Total

Paraphrases

(%)

# Scoring 2

(%)

# Scoring

1(%)

# Scoring 0

(%)

# Filtered

(%)

Grade 3

(38.5%)

60 (32.1%)

2 (6.5%)

10 (15.6%)

10 (43.5%)

38 (55.1%)

Grade 4

(61.5%)

127 (67.9%)

29 (93.5%)

54 (84.4%)

13 (56.5%)

31 (44.9%)

Mean:

Gr. 3: 12.0

Gr. 4: 15.9

Gr. 3: 0.4

Gr. 4: 3.6

Gr. 3: 2.0

Gr. 4: 6.7

Gr. 3: 2.0

Gr. 4: 1.6

Gr. 3: 7.6

Gr. 5: 3.9

When disaggregated data by grade level, the paraphrase quality data uncovered few surprises.

Students in third grade struggled more with the work. Grade 3 students wrote fewer paraphrases,

and had more paraphrases filtered out. The percentage of paraphrases falling in each group (e.g.

total paraphrases, total paraphrases filtered out) was not commensurate with the participation of

grade 3 students, which was 38.5% of the total student participation. The closest came in the

number of paraphrases generated, with the grade 3 students generating 32.1% of the paraphrases.

The third grade students had fewer paraphrases that scored a 2 or a 1; however, they did have

more paraphrases that scored a 0.

Overall, while nearly 13% of the paraphrases scored a 0, and nearly 37% of the

paraphrases had been previously filtered out, over 50% of the paraphrases earned a score of 1 or

2. This data point meant that the paraphrase strategy was present in over half of the paraphrases

generated by the students. Conversely, this data point also reveals the struggle that students had

in reading and paraphrasing the texts. Considering the fact that these students had previously

194

been identified as below grade-level readers, and pre-assessment data revealed gaps in students’

basic science knowledge, this paraphrase quality data revealed both problem and promise.

Comparison of Paraphrase Data to Text Indices Data

The researcher next compared the paraphrase data to the data gathered on the reading

indices on the texts used. Doing this analysis provided additional information on the nuances of

each text with regard to the Text Ease and Readability (T.E.R.A.) components of narrativity,

syntactic similarity, word concreteness, referential cohesion, and deep cohesion (for an

explanation of these components, see Table 4.3 presented previously in this chapter). As would

be expected, Text 1, “How a Star is Born,” generated the most paraphrases (N=57), as it was the

easiest text presented to students. It had the second-highest narrativity score (63), the

second-highest deep cohesion score (90), a high syntactic simplicity score (91), and strong word

concreteness and referential cohesion scores (75 and 74, respectively). However, while it had the

highest number of paraphrases earning a score of 2, it did not have the highest percentage of

paraphrases earning a score of 2. The text with the highest percentage of paraphrases earning a

score of 2 was “A Visit to Mars,” which was the third text presented to students.

An interesting finding was revealed with regard to Texts 3 (“A Visit to Mars”) and 4

“Wildfires”) when analyzing individual paraphrase scores for these two texts. Text 3, “A Visit to

Mars” had a deep cohesion score of 24, which was the lowest of the eight texts. Text 4,

“Wildfires” had a deep cohesion score of 99, which was highest of the eight texts. The two texts

combined had a total of 60 paraphrases generated - 35 for “A Visit to Mars” and 25 for

“Wildfires,” a difference of 10. Of the 35 paraphrases completed for “A Visit to Mars,” 25

195

earned a paraphrase score of 2, 1, or 0, which comprised 71.4% of the corpus of paraphrases

generated for this text. Text 4, “Wildfires,” on the other hand, had 25 total paraphrases, 15 of

which earned a score of 2, 1, or 0. That number accounts for 60% of the total number of

paraphrases generated for “Wildfires.” The paraphrase quality data for these two texts are found

in Table 4.20 below.

Table 4.20. Paraphrase Quality Data for “A Visit to Mars” and “Wildfires”

Text

# of Paraphrases

Scoring 2

# of Paraphrases

Scoring 1

# of Paraphrases

Scoring 0

Paraphrases

Filtered Out

A Visit to

Mars

(N=35)

Wildfires

(N=25)

The deep cohesion scores of the two texts differed by 75, which is the largest difference

between scores in any component category. However, the overall paraphrase quality data did not

fully reflect that wide difference, which means that other differences in the components

(narrativity, syntactic simplicity, word concreteness, and referential cohesion) were factors. The

T.E.R.A. component scores for these two texts are found in Table 4.21 below.

Table 4.21. T.E.R.A. Component Scores for “A Visit to Mars” and Wildfires”

Text

Flesch-

Kincaid

Score

Narrativity

Syntactic

Similarity

Word

Concreteness

Referential

Cohesion

Deep

Cohesion

Mars

3.0

196

Wildfires

5.1

Text 4, “Wildfires,” had three T.E.R.A. component scores which were higher than those for

“Mars.” Further, “Mars” had a higher narrativity score than “Wildfires,” and the narrative genre

is generally easier to read than expository text (Beck & Kucan, 2002; Jackson, et al., 2016);

Perfetti, 2007). Yet, while “Mars” had more paraphrases, “Wildfires” had a higher number of

paraphrases earning the highest quality score. “Mars” had three paraphrases that earned a quality

score of 2, which is 12% of the paraphrases for that text earning a score and not filtered out,

which was the second lowest percentage of the seven texts paraphrased by students. After

completing the comparative analysis of the paraphrase quality data to the text component data,

the researcher then did an analysis of paraphrase data to the students’ pre-assessment data.

Comparison of Paraphrase Data to Pre-Assessment Data

Paraphrase Data and Science Pre-Assessment Data.

To further guide an understanding of the essential characteristics of texts needed for a

reading comprehension strategy intervention tool, the researcher compared the paraphrase data

with each student’s pre-assessment data. First, it was important to this researcher to compare the

paraphrase quality data of each student to their science pre-assessment scores to determine any

correlation or predictable patterns. Table 4.22 below outlines the students’ paraphrase scores of

0, 1, and 2, and their science pre-assessment scores.

Table 4.22. Comparison of Students’ Paraphrase Quality Scores to Science Pre-Assessment

Student

Number

Total

Paraphrases

% of

Paraphrases

% of

Paraphrases

% of

Paraphrases

# of

Paraphrases

Science

Pre-Assessment

197

Scoring 2 (#)

Scoring 1 (#)

Scoring 0 (#)

Previously

Filtered Out

Percentage

10001

50% (2)

75%

10002

47.4% (9)

52.6% (10)

62.5%

10003

25% (1)

50% (2)

25% (1)

25%

10004

28.6% (4)

14.3% (2)

50% (7)

87.5%

10005

11.1% (1)

44.4% (4)

50%

10010

5.3% (1)

25%

10012

5.3% (1)

47/4% (9)

37.5%

10013

22.2% (2)

37.5%

10014

11.8% (4)

73.5% (25)

2.9% (1)

75%

10015

14.7% (5)

32.4% (11)

11.8% (4)

75%

10016

35.8% (5)

25%

10017

50% (2)

25% (1)

50%

10018

74% (3)

25% (1)

75%

Next, the researcher grouped the paraphrase data by science pre-assessment score. That set of

data is found in Table 4.23 below.

Table 4.23. Paraphrase Data by Science Pre-Assessment Score Percentage

Science

Pre-

Assessment

Percentage

Student

Number

(Gender)

Total # of

Paraphrases

Scored

Total # of

Paraphrases

Scoring a 2

Total # of

Paraphrases

Scoring a 1

Total # of

Paraphrases

Scoring a 0

# of

Paraphrases

Previously

Filtered Out

Total # of

Paraphrases

Scored (Not

Filtered)

Below 50%

10003

(F)

10010

(F)

198

10012

(F)

10013

(M)

10016

(F)

Total Below

50%

50% - 74%

10002

(M)

10005

(F)

10017

(M)

Total

50%-74%

75%-100%

10001

(F)

10004

(M)

10014

(F)

10015

(F)

10018

(F)

Total

75%-100%

Only one student with a science pre-assessment score of less than 50% had any paraphrase

quality score of 2, but those students with a science pre-assessment score of less than 50%

collectively scored a paraphrase quality score of 1 on 12 paraphrases. Students scoring 75% and

199

higher on the science pre-assessment collectively earned a quality score of 2 on 18 paraphrases,

and a quality score of 1 on 40 paraphrases. Interestingly, the students could be grouped based on

the number of paraphrases completed; there were five groups of students who had the same

number of paraphrases (19, 34, 14, 4, and 9, respectively). The researcher deemed that a further

analysis was warranted on their scores within the grouping, both individually and collectively by

score.

Three students completed 19 paraphrases: Students 10002, 10010, and 10012. Student

10002, however, had quite different scores on the paraphrase data and the science pre-assessment

data than the other two students. With regard to the paraphrase data, Student 10002 had nine

paraphrases that scored a 2, 10 paraphrases that scored a 1, and no paraphrases that scored a 0 or

were filtered out.

Conversely, neither Student 10010 nor Student 10012 had any paraphrases that earned a

quality score of 2. Those two students collectively had five of their paraphrases which scored a 1,

and seven paraphrases which scored a 0. Student 10010 had 18 paraphrases that were filtered

out, and one paraphrase that earned a score of 1. Student 10012 had nine paraphrases that were

filtered out, one paraphrase that earned a score of 1, and nine paraphrases that earned a score of

With regard to the science pre-assessment data, Student 10002 scored 5 out of 8, or

62.5% on the science pre-assessment, whereas student 10010 scored 2 out of 8, or 25%; and

10012 scored 3 out of 8, or 37.5%, on the science pre-assessment. Student 10010 was one of

three students who scored the lowest on the science pre-assessment, and Student 10012 was one

of two students who had the second lowest scores. It is interesting to note that, although student

200

10002 earned a lower science pre-assessment score than five other of their classmates, this

student had the highest number of paraphrases earning a quality score of 2, had no paraphrase

score of 0, or had any paraphrases filtered out.

Two students, 10014 and 10015, completed 34 paraphrases. They earned a paraphrase

quality score of 2 on a similar number of paraphrases (4 and 5, respectively), but their other

paraphrase quality scores varied rather considerably. Student 10014 earned a paraphrase score of

1 on 25 of their paraphrases, compared to 11 for Student 10015, although it must be noted that

these two students had the highest number of paraphrases of all the students that earned a quality

score of 1. Further, Student 10015 had 14 paraphrases filtered out, compared to just four for

Student 10014. They collectively earned a score of 0 on five paraphrases; Student 10014 earned

that score on only one of their paraphrases, whereas student 10015 earned that score on four of

their paraphrases. Their science pre-assessment scores, on the other hand, were exactly the same

at 75%.

Two students, 10004 and 10016, completed 14 paraphrases, yet their science

pre-assessment scores had the largest difference (87.5% and 25%, respectively). It is well worth

noting that their paraphrase quality scores also differed, although the differences did not fall

within a predictable pattern. Student 10004, who had a science pre-assessment score of 87.5%,

generated four paraphrases with a quality score of 2, compared to zero for Student 10016.

Further, Student 10004 had only one paraphrase filtered out, whereas Student 10016 had nine

paraphrases filtered out. However, Student 10004 had only one paraphrase that earned a quality

score of 1, and had seven paraphrases that earned a quality score of 0. Student 10016 had five

201

paraphrases that earned a quality score of 1, and had no paraphrases that earned a quality score of

Four students, 10001, 10003, 10017 and 10018, completed four paraphrases, and again,

their science pre-assessment scores varied. However, their paraphrases did not fall within a

predictable pattern. Student 10003 earned the lowest science pre-assessment score, which was

25%. However, this student had one paraphrase that earned a quality score of 2, two that earned a

quality score of 1, one paraphrase that earned a quality score of 0, and none that were filtered.

Student 10017 earned a score of 50%. This student had two paraphrases earning a quality score

of 2, one paraphrase that earned a quality score of 1, and one that was filtered out. Two students,

10001 and 10018, scored 75% on their science pre-assessment. Student 10001 earned a quality

score of 2 on two of their paraphrases, and two paraphrases were filtered out. Student 10018 had

three paraphrases that earned a quality score of 2, and none were filtered out.

Two students completed nine paraphrases, Student 10005 and Student 10013, yet their

science pre-assessment scores varied by one question: Student 10005 earned a score of 50%, and

Student 10013 earned a score of 37.5%. Student 10005 had higher paraphrase quality scores than

did Student 10013: this student had one paraphrase that earned a quality score of 2, four that

earned a quality score of 1, and four that were filtered out. Student 10013 had seven paraphrases

filtered out, two paraphrases that earned a quality score of 1, and none that earned a quality score

of 2 or 0.

Following the analysis of paraphrase quality scores to science pre-assessment scores, the

researcher conducted a comparison of each student’s paraphrase data to their reading attitude

survey data.

202

Paraphrase Data and Elementary Reading Attitude Survey Data.

Each student’s paraphrase data were compared to their Elementary Reading Attitude Survey

(ERAS) scores. As previously established through a review of the literature, that reading attitude

can affect reading performance (McKenna & Kear, 1990; Petscher, 2010; Walberg & Tsai, 1985).

Therefore, the reading attitude survey data were compared with students’ paraphrase data to

identify emerging patterns or trends. The students’ paraphrase data, coupled with their reading

attitude scores, are found in Table 4.24 below.

Table 4.24. Comparison of Students’ Paraphrase Data to ERAS Scores

Student

Number

Total

Paraphrases

Scored

% of

Paraphrases

Scoring 2

(#)

% of

Paraphrases

Scoring 1 (#)

% of

Paraphrases

Scoring 0 (#)

# of

Paraphrases

Previously

Filtered Out

Rec.

Reading

Attitude

Score/%

Acad.

Reading

Attitude

Score/%

Total

Reading

Attitude

Score/%

10001

50% (2)

32/84th

32/79th

67/83rd

10002

47.4% (9)

52.6% (10)

28/41st

26/46th

43/41st

10003

25% (1)

50% (2)

25% (1)

28/38th

34/83rd

62/64th

10004

28.6% (4)

14.3% (2)

50% (7)

31/60th

28/58th

59/59th

10005

11.1% (1)

44.4% (4)

31/57th

32/74th

63/67th

10010

5.3% (1)

29/45th

28/52nd

57/48th

10012

5.3% (1)

47/4% (9)

37/90th

35/88th

72/91st

10013

22.2% (2)

17/1st

22/22nd

39/6th

10014

11.8% (4)

73.5% (25)

2.9% (1)

36/88th

34/87th

70/89th

10015

14.7% (5)

32.4% (11)

11.8% (4)

33/72nd

31/75th

64/75th

10016

35.8% (5)

34/78th

37/95th

71/91st

10017

50% (2)

25% (1)

26/26th

28/58th

54/41st

10018

74% (3)

25% (1)

32/66th

24/35th

56/48th

203

Next the researcher grouped the paraphrase data by ERAS total reading score percentile

groups. That set of data can be found in Table 4.25 below.

Table 4.25. Paraphrase Data by Elementary Reading Attitude Survey Total Reading Percentile

Percentile

Group

Student

Number

Total # of

Paraphrases

Total # of

Paraphrases

Scoring a 2

Total # of

Paraphrases

Scoring a 1

Total # of

Paraphrases

Scoring a 0

# of

Paraphrases

Previously

Filtered Out

Total # of

Paraphrases

Scored (Not

Filtered)

Below

50th%

10002

10010

10013

10017

10018

Total

Below

50th%

51st-

75th%

10003

10004

10005

10015

Total

51st-

75th%

76th-

99th%

10001

10012

10014

10016

204

Total

76th-

99th%

When disaggregating the data by the elementary reading attitude total score and grouping by

percentile group, the data fell into predictable patterns in two areas: total number of paraphrases

and total number of paraphrases scored (not previously filtered out). The group scoring at or

below the 50th percentile on their total reading attitude survey score had the least number of total

paraphrases and the least number of paraphrases scored and not filtered out. The group scoring

between the 76th - 99th percentile on their total reading attitude survey score had the highest

number of total paraphrases and the greatest number of paraphrases scored and not previously

filtered out. The data on the number of paraphrases filtered out, however, did not fall within a

predictable pattern. The students in the group with the highest ERAS percentiles (76th - 99th)

had 24 paraphrases filtered out, which number was the middle of the three groups.

The researcher noticed very interesting dichotomies when analyzing the paraphrase data

to the elementary reading attitude survey data. The first was with Student 10012. This student

had the second highest academic survey score and the highest total reading attitude survey score.

This student generated 19 paraphrases, which was in the top four of all students. However, this

student’s paraphrases were of low quality, with none scoring a 2, only one scoring a 1, nine

scoring a 9, and nine filtered out.

The second observation involved student 10016. This student had the highest academic

survey score and the second highest total reading attitude survey score. This student generated 14

205

paraphrases. However, while none of the student’s paraphrases scored a zero, none scored a 2,

five scored a 1, and nine were filtered out.

The analysis of student 10002 was also notable. The student’s academic survey score was

26, which is three points lower than the mean academic score of the group, and their total survey

score was 54, which is over four points lower than the mean total score of the group. But this

student outperformed all other students in paraphrase quality, with nine paraphrases scoring a 2,

ten paraphrases scoring a 1, and none that scored a zero or were filtered out.

The next data which were analyzed were the student text perception and paraphrase

perception data. These were the data points provided by the students at the end of each text,

when they were asked to rate the text itself and to rate the work of paraphrasing the

predetermined sentences. These data are explored in detail in the next section.

Student Perceptions of Text and Paraphrase Difficulty

Questions were populated in Qualtrics at the end of each text, requiring students to rate

the text itself and the act of paraphrasing the sentences. Ratings were displayed on the screen

both in written form and pictorially: for text ratings, a green happy face stood for “I liked it!”; a

yellow emotionless face stood for “It was okay”; and a red sad face stood for “I didn’t like it.”

For paraphrase ratings, a green happy face stood for “It was easy!”; a yellow emotionless face

stood for “It was okay”; and a red sad face stood for “It was hard.” Students chose the icon that

best matched their opinion. The Qualtrics tool was created in such a way that a student could not

move on to the next text until they rated both the text and the act of paraphrasing sentences. This

text and paraphrase perception data provided the researcher a better understanding of what the

206

students thought about the texts that increased in difficulty, and their thoughts as they

paraphrased increasingly difficult sentences. Students provided a total of 40 ratings each for text

perception and paraphrase perception. Overall text and paraphrase perception data are found in

Appendix K.

There were very few students who indicated that they disliked a passage, even the four

students who completed only one passage. For all eight texts combined, there were only three

ratings of “dislike”; interestingly both of the texts that received that rating were on the topic of

space: “How A Star Is Born” and “A Visit To Mars.” However, those two texts also received two

of the highest percentage of ratings indicating the students “really liked” them, 54% and 57%,

respectively. With regard to the difficulty of the passages, there were four students who indicated

that a text was “hard,” and three texts earned at least one of those ratings, including “How A

Star Is Born” and “A Visit To Mars.” However, those same two texts were rated overall the

easiest to read, with 54% and 57% of the responses, respectively.

Looking at the data by text and student, the rating of “dislike” with regard to the text did

not correlate with the rating of “hard” with regard to paraphrasing the sentences. Further, it is

important to remember that fewer students completed the latter texts as the texts increased in

difficulty. Text and paraphrase perception data by individual student and individual text are

found in Table 4. 26 below. No student read or paraphrased the last text in the set; therefore,

“n/a” was used in the individual tables for any student who did not read or paraphrase the

particular text.

Table 4.26. Text and Paraphrase Perception Data by Student and Individual Text

Text 1: A Star is Born

207

Student #

Liked text?

Easy to read?

Liked Paraphrasing?

Easy to Paraphrase?

10001 (gr 4, F)

ReallyLIked

Easy

Really Like

Easy

10002 (gr 4, M)

Really liked

Easy

Really like

okay

10003 (gr 3, F)

Okay

Hard

Really liked

hard

10004 (gr. 4,M)

Really liked

easy

It was okay

easy

10005 (gr 3, F)

Okay

Really liked

okay

10010 (gr 3, F)

Didn’t like

Okay

It was okay

okay

10012 (gr 3, F)

Okay

easy

It was okay

okay

10013 (gr 3, M)

Didn’t like

hard

It was okay

okay

10014 (gr 4, F)

Really liked

easy

Really liked

easy

10015 (gr 4, F)

Really liked

okay

Really liked

okay

10016 (gr 4, F)

Really liked

okay

Really liked

okay

10017 (gr 4, M)

Okay

easy

Really liked

easy

10018 (gr 4, F)

Really liked

easy

It was okay

okay

Text 2: Eating Healthy

Student #

Liked text?

Easy to read?

Liked Paraphrasing?

Easy to Paraphrase?

10001 (gr 4, F)

n/a

10002 (gr 4, M)

Really liked

Okay

Really like

easy

10003 (gr 3, F)

n/a

10004 (gr. 4,M)

Really liked

easy

Really liked

easy

10005 (gr 3, F)

Okay

Really liked

okay

10010 (gr 3, F)

okay

hard

It was okay

okay

10012 (gr 3, F)

Okay

okay

It was okay

okay

10013 (gr 3, M)

Really liked

easy

Really liked

okay

10014 (gr 4, F)

Really liked

easy

Really liked

easy

208

10015 (gr 4, F)

okay

Really liked

okay

10016 (gr 4, F)

Really liked

okay

Really liked

okay

10017 (gr 4, M)

n/a

10018 (gr 4, F)

n/a

Text 3: A Visit to Mars

Student #

Liked text?

Easy to read?

Liked Paraphrasing?

Easy to Paraphrase?

10001 (gr 4, F)

n/a

10002 (gr 4, M)

Really liked

easy

Really like

okay

10003 (gr 3, F)

n/a

10004 (gr. 4, M)

Really liked

easy

Really liked

easy

10005 (gr 3, F)

n/a

10010 (gr 3, F)

Didn’t like

hard

It was okay

okay

10012 (gr 3, F)

Okay

okay

Didn’t like

okay

10013 (gr 3, M)

n/a

10014 (gr 4, F)

Really liked

easy

Really liked

easy

10015 (gr 4, F)

okay

easy

okay

10016 (gr 4, F)

Really liked

okay

Really liked

okay

10017 (gr 4, M)

n/a

10018 (gr 4, F)

n/a

Text 4: Wildfires

Student #

Liked text?

Easy to read?

Liked Paraphrasing?

Easy to Paraphrase?

10001 (gr 4, F)

n/a

10002 (gr 4, M)

Really liked

easy

okay

10003 (gr 3, F)

n/a

209

10004 (gr. 4, M)

n/a

10005 (gr 3, F)

n/a

10010 (gr 3, F)

okay

hard

It was okay

okay

10012 (gr 3, F)

Okay

okay

Really liked

okay

10013 (gr 3, M)

n/a

10014 (gr 4, F)

Really liked

easy

Really liked

easy

10015 (gr 4, F)

okay

10016 (gr 4, F)

n/a

10017 (gr 4, M)

n/a

10018 (gr 4, F)

n/a

Text 5: Blood

Student #

Liked text?

Easy to read?

Liked Paraphrasing?

Easy to Paraphrase?

10001 (gr 4, F)

n/a

10002 (gr 4, M)

n/a

10003 (gr 3, F)

n/a

10004 (gr. 4, M)

n/a

10005 (gr 3, F)

n/a

10010 (gr 3, F)

n/a

10012 (gr 3, F)

n/a

10013 (gr 3, M)

n/a

10014 (gr 4, F)

Really liked

easy

Really liked

easy

10015 (gr 4, F)

Really liked

okay

10016 (gr 4, F)

n/a

10017 (gr 4, M)

n/a

10018 (gr 4, F)

n/a

210

Text 6: Ostriches

Student #

Liked text?

Easy to read?

Liked Paraphrasing?

Easy to Paraphrase?

10001 (gr 4, F)

n/a

10002 (gr 4, M)

n/a

10003 (gr 3, F)

n/a

10004 (gr. 4, M)

n/a

10005 (gr 3, F)

n/a

10010 (gr 3, F)

n/a

10012 (gr 3, F)

n/a

10013 (gr 3, M)

n/a

10014 (gr 4, F)

Really liked

easy

Really liked

easy

10015 (gr 4, F)

okay

10016 (gr 4, F)

n/a

10017 (gr 4, M)

n/a

10018 (gr 4, F)

n/a

Text 7: Starfish

Student #

Liked text?

Easy to read?

Liked Paraphrasing?

Easy to Paraphrase?

10001 (gr 4, F)

n/a

10002 (gr 4, M)

n/a

10003 (gr 3, F)

n/a

10004 (gr. 4, M)

n/a

10005 (gr 3, F)

n/a

10010 (gr 3, F)

n/a

10012 (gr 3, F)

n/a

10013 (gr 3, M)

n/a

10014 (gr 4, F)

Really liked

easy

Really liked

easy

211

10015 (gr 4, F)

okay

10016 (gr 4, F)

n/a

10017 (gr 4, M)

n/a

10018 (gr 4, F)

n/a

There were some interesting findings when looking at the data by student. The researcher

compared students who completed a similar number of paraphrases. Four students completed

four paraphrases and only got through one text. All of the paraphrases created by Student 10003

earned a score - one earned a score of 2, two earned a score of 1, one earned a score of zero, and

none were filtered out. However, this student found the text hard to read and the paraphrases

hard to create. Further, although Student 10003 found the text and paraphrase creation hard, they

gave the highest ratings to both the text and the activity of paraphrasing. Student 10001 as well

gave the highest rating possible to both the text and the act of paraphrasing. It was very

interesting that this student completed only one text. Students 10017 and 10018 had nearly equal

yet opposite ratings of the text and paraphrasing; Student 10017 thought the text was just “okay”

but thought it was easy to read; they really liked paraphrasing and thought creating them was

easy. Student 10018 really liked the text and thought it was easy; however, this student gave

ratings of “okay” to the paraphrase activity. They thought that creating the paraphrases was just

okay, and thought that the difficulty of creating them was just okay as well.

Two students completed 19 paraphrases. Nine of the paraphrases created by 10002 earned

a score of 2, ten scored a 1, and none scored a 0 or were filtered out. This student gave the rating

of “really liked” to all of the texts they read, and gave a “really like” rating to the act of

212

paraphrasing for three of the four texts. However, the student rated the ease of paraphrasing as

only “okay” three out of four times. Student 10012 had no paraphrases that scored a 2, one

paraphrase that scored a 1, nine paraphrases that earned a score of 0, and nine were filtered out.

This student rated the act of paraphrasing as “really liked” for only one text. Every other rating

given by this student, whether it was for their liking of the text, the ease of the text, or the ease of

paraphrasing, was “okay.”

Students 10014 and 10015 completed the most texts and created the most paraphrases (34

paraphrases each). They had a similar number of paraphrases that scored a 2 (4 and 5,

respectively). However, Student 10014 had 25 paraphrases that scored a 1, and only four that

were filtered out. This student gave the highest ratings possible to every text, rating all texts and

the acts of paraphrasing as “really liked.” Student 10015, on the other hand, had 11 paraphrases

that scored a 1, and 14 paraphrases that were filtered out. This student rated their liking of the

text and the ease of the text “okay” 12 out of 14 times, equaling 87.5% of the text ratings. The

student also rated their liking of the paraphrase activity and the ease of paraphrasing “okay” 12

of 14 times, again equaling 87.5% of the paraphrase ratings.

Once the text perception ratings and paraphrase ratings were disaggregated by text, the

researcher further analyzed the data by gender. This data set is presented in Table 4.27 below.

Table 4.27. Text and Paraphrase Perception Data By Gender

Text Rating (N=40)

Gender

Number

Really

Liked (%)

Number

Okay (%)

Number

Disliked

(%)

Number

Easy

(%)

Number

Okay (%)

Number

Hard

(%)

Total

Ratings

Male

8 (80%)

1 (10%)

8 (80%)

1 (10%)

213

Female

(46.7%)

14 (46.7%)

(6.7%)

11 (36.7%)

(50%)

4 (13.3%)

Total

22 (55%)

15 (35%)

3 (10%)

19 (47.5%)

16 (40%)

5 (12.5%)

Total

Ratings

Really

Liked (%)

Total

Ratings

Okay

(%)

Total

Ratings

Disliked

(%)

Total

Ratings

Easy

(%)

Total

Ratings

Okay

(%)

Total

Ratings

Hard

( %)

Male

36.4

6.7

33.3

42.1

6.3

Female

63.6

93.3

66.7

57.9

93.7

Paraphrase Rating (N=40)

Gender

Number

Really

Liked (%)

Number

Okay (%)

Number

Disliked

(%)

Number

Easy

(%)

Number

Okay (%)

Number

Hard (%)

Total

Ratings

Male

7 (70%)

3 (30%)

0 (0%)

5 (50%)

0 (0%)

Female

(56.7%)

(40%)

(3.3%)

(30%)

20 (66.7%)

(3.3%)

Total

24 (60%)

15 (37.5%)

1 (2.5%)

14 (35%)

25 (62.5%)

1 (2.5%)

Total

Ratings

Really

Liked (%)

Total

Ratings

Okay

(%)

Total

Ratings

Disliked

(% )

Total

Ratings

Easy

(%)

Total

Ratings

Okay

(%)

Total

Ratings

Hard

( %)

Male

29.2

35.7

Female

70.8

100

64.3

Female student participants provided more ratings because the two students who had the

most paraphrases were female. They completed more texts. When analyzing the ratings, it would

then make sense that the overall number of ratings would be higher for females. A deeper

analysis was warranted into each of the genders’ individual ratings. The male students as a group

liked both the texts and the paraphrase activity more than the female students did as a group.

214

Male students’ ratings of “really liked” was 80%, compared to only 46.7% of the female text

ratings. Additionally, female students had lower ratings for the ease of the texts: While 80% of

the male student ratings were “easy,” only 36.7% of the female students’ ratings were “easy.”

This is a significant difference; there was a difference of only three ratings between males and

females here, but females had three times the number of overall ratings than males. The findings

are somewhat surprising given that females at both grade levels had higher academic reading

attitude scores than did the males (see Appendix I). While the sample size is small, these findings

do corroborate the research favoring male academic reading attitude.

A similar finding was made for the ease of paraphrasing. Male students’ ratings of “really

liked” was 70%, compared to 56.7% of the female paraphrase ratings. Again, female students

had lower ratings for the ease of paraphrasing: 30% of the female student ratings on paraphrasing

were “easy,” compared with 50% of male students’ paraphrase ratings.

Female students gave a rating of “okay” four times as often as the male students for the

paraphrase activity. When rating the texts, there were 31 ratings of “okay” for whether the

students liked the text and the ease of the text; female students accounted for 29 of those 31

ratings, or 93.5%. Female students also had more ratings of “hard” for both the text and

paraphrase perceptions, and more ratings of “dislike” for the texts and the act of paraphrasing.

Overall, the text perceptions and paraphrase perceptions were positive. Of the 80 total

text perception ratings (40 for how the students liked the text and 40 for the ease of the text),

only 8, or 10%, were negative (that the student disliked the text or found it hard). Similarly with

the paraphrase perception ratings: of the 80 total ratings provided by the students, only two were

negative, or 0.25%. Conversely, 41 of the 80 ratings for text perception, or 51.2%, were very

215

positive (the students really liked the text and they found it easy). Paraphrase perception ratings

were similarly positive. 38 of the 80 ratings for paraphrase perception, or 47.5%, were very

positive.

Analysis of Text and Paraphrase Perception Data with Paraphrase Quality Data

When looking at the text and paraphrase perception data alongside the paraphrase quality

data, there were some predictable patterns. The text perception responses decreased with every

subsequent text until Text 5, “Blood.” At that point, there were only two students left who were

reading and paraphrasing the texts, and they both stopped with “Starfish,” so the last three texts

had the same number of ratings. This researcher wanted to see how the text and paraphrase

perception data compared to the paraphrase quality data. This correlation of data can be found in

Table 4.28 below.

Table 4.28. Comparison of Text and Paraphrase Perception Data to Paraphrase Quality Data

Text #: Text Name

Paraphrase Quality Score N=52 (%)

Text 1:

How A Star is

Born

# Scoring 2

# Scoring 1

# Scoring 0

# Filtered

12 (23.1%)

16 (30.8%)

7 (13.4%)

17 (32.7%)

Text Perception Data N=13 (%)

# Really Liked

# Okay

# Disliked

7 (53.8%)

4 (30.8%)

2 (15.4%)

Paraphrase Perception Data N=13 (%)

# Really Liked

# Okay

# Disliked

8 (61.5%)

5 (38.5%)

0 (0%)

Text 2:

Eating Healthy

Paraphrase Quality Score N=45 (%)

# Scoring 2

# Scoring 1

# Scoring 0

# Filtered

216

6 (13.3%)

15( 33.3%)

6 (13.3%)

18 (40.0%)

Text Perception Data N=9 (%)

# Really Liked

# Okay

# Disliked

5 (55.6%)

4 (44.5%)

0 (0%)

Paraphrase Perception Data N=9 (%)

# Really Liked

# Okay

# Disliked

7 (77.8%)

2 (22.2%)

0 (0%)

Text 3:

A Visit to Mars

Paraphrase Quality Score N=35 (%)

# Scoring 2

# Scoring 1

# Scoring 0

# Filtered

3 (8.6%)

13 (37.1%)

9 (25.7%)

20 (28.6%)

Text Perception Data N=7 (%)

# Really Liked

# Okay

# Disliked

4 (57.1%)

2 (28.6%)

1 (14.3%)

Paraphrase Perception Data N=7 (%)

# Really Liked

# Okay

# Disliked

4 (57.1%)

2 (28.6%)

1 (14.3%)

Text 4:

Wildfires

Paraphrase Quality Score N=25 (%)

# Scoring 2

# Scoring 1

# Scoring 0

# Filtered

8 (32.0%)

6 (24.0%)

1 (4.0%)

10 (40.0%)

Text Perception Data N=5 (%)

# Really Liked

# Okay

# Disliked

2 (40.0%)

3 (60.0%)

0 (0%)

Paraphrase Perception Data N=5 (%)

# Really Liked

# Okay

# Disliked

2 (40.0%)

3 (60.0%)

0 (0%)

Text 5:

Blood

Paraphrase Quality Score N=10 (%)

217

# Scoring 2

# Scoring 1

# Scoring 0

# Filtered

1 (10%)

4 (40.0%)

1 (10.0%)

4 (40.0%)

Text Perception Data N=2 (%)

# Really Liked

# Okay

# Disliked

2 (100%)

0 (0%)

Paraphrase Perception Data N=2 (%)

# Really Liked

# Okay

# Disliked

1 (50.0%)

0 (0%)

Text 6:

Ostriches

Paraphrase Quality Score N=10 (%)

# Scoring 2

# Scoring 1

# Scoring 0

# Filtered

0 (0%)

4 (40.0)

0 (0%)

6 (60.0%)

Text Perception Data N=2 (%)

# Really Liked

# Okay

# Disliked

1 (50.0%)

0 (0%)

Paraphrase Perception Data N=2 (%)

# Really Liked

# Okay

# Disliked

1 (50.0%)

0 (0%)

Text 7:

Starfish

Paraphrase Quality Score N=10 (%)

# Scoring 2

# Scoring 1

# Scoring 0

# Filtered

2 (20.0%)

4 (40.0%)

0 (0%)

4 (40.0%)

Text Perception Data N=2 (%)

# Really Liked

# Okay

# Disliked

1 (50.0%)

0 (0%)

Paraphrase Perception Data N=2 (%)

# Really Liked

# Okay

# Disliked

1 (50.0%)

0 (0%)

218

Given that only two students completed the last three texts, the researcher first focused on

the four other texts that were completed by more students. The first text, “How a Star is Born,”

had the highest number of paraphrases and the highest number of perception responses, which is

predictable given it was the first text. It was also the least difficult text, with a Flesch-Kincaid

level of 2.7 (grade 2, seventh month), and strong T.E.R.A. component scores, including 91 for

syntactic simplicity and 90 for deep cohesion. However, this text had neither the highest

percentage of paraphrases scored of the first four texts, nor the lowest percentage of paraphrases

filtered out. Interestingly, “How a Star is Born” also did not have the highest text perception

ratings or the highest paraphrase perception ratings of the first four texts.

Again, the interesting findings came with Text 3, “A Visit to Mars,” and Text 4,

“Wildfires.” Text 3, “A Visit to Mars,” had the lowest number of paraphrase quality scores

earning a 2 of this corpus of four texts, and it was the only text that earned a “dislike” rating

from a student for the paraphrase perception. Although it was the third text presented to students,

with a Flesch-Kincaid score of 3.0 (third grade, zero month), it was a hard text for students.

“Wildfires,” on the other hand, while a text less liked and harder to paraphrase according to the

perception data, had more paraphrase quality scores of 2 than “A Visit to Mars” (8 versus 3,

respectively). “Wildfires” had a high T.E.R.A. component score for syntactic simplicity (90), and

a word concreteness score of 74, which refers to the use of concrete nouns (those things one can

hear, see, taste, smell, touch). It also had the highest deep cohesion component score. This

analysis aligns with the review of literature on text structure and text features (Duke, 2000;

McNamara, et al., 2011; Santoro, et. al, 2016).

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When comparing the text and paraphrase perception data with the paraphrase quality data

by gender, there were few surprises. Males had more favorable perceptions of the texts and the

paraphrasing, and their paraphrases, while fewer in number, were of higher quality than those

generated by the females. This finding aligns with the review of the literature in that texts that

students find interesting across different cultures and experiences, that reflects the students in the

classroom and draws upon their backgrounds and languages, and with which the students can

identify, has a positive impact on reading achievement and on readers’ self esteem (Barber, et al.,

2018; Ebe, 2010; Ladson-Billings, 1995; Kourea, Gibson, & Werunga, 2017; Tatum, 2006,

Troyer, et al., 2019). See Table 4.26 for a breakdown of text and paraphrase perception data by

text and gender.

It was important to this researcher to gather qualitative data from the students after they

had completed the tasks of reading and paraphrasing the texts presented to them in the Qualtrics

tool. Because the students participating in this study were struggling readers and all remaining

participants were English language learners, this researcher wanted to gain a better

understanding of what the students remembered about the paraphrase strategy and their reading

efficacy as a result of the activity. The data were gathered through a short, one-on-one guided

conversation with each student. The analysis of this qualitative data is provided below.

Qualitative Student Interview Data

After the students completed their text reading and paraphrasing, the researcher

interviewed each student who was still present in the summer targeted services program about

their experience with paraphrasing. Absenteeism continued to be an issue; 11 students were

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present for this interview, 10 females and one male. Three questions were created: a what

question, a how question, and a why question. The what question would address the students’

understanding of paraphrasing; the how question addressed their mental processes while

paraphrasing, and the why question addressed their reading efficacy. The three questions are as

follows, in the order asked by the researcher:

● Question 1: Do you remember what paraphrasing is?

● Question 2: How did you figure out how to paraphrase the sentences?

● Question 3: Do you think paraphrasing helped you to read better? Why?

Of the 11 students interviewed, four, or 36.4%, could not describe the paraphrasing

strategy. This was an interesting finding by the researcher, as the students had spent time over

two days working through the activity of reading and paraphrasing the texts in Qualtrics. One

student stated at first that they could not remember, but subsequently described the strategy.

Seven students, or 63.6%, could articulate how to paraphrase. One female student in particular

described paraphrasing quite well, utilizing one of the strategies taught in the instructional video,

which was substituting words: “if there’s like a word that you don’t know, you could … put it in

a new word, like if it was like ‘perfect’ you could say...is ‘perfect’ like ‘great’? It is, so instead of

saying ‘perfect’ you can say ‘great’.”

The most interesting finding came with the answers to the why question. Every single

student responded that paraphrasing helped them become a better reader. Three of the 11

students, or 27%, explained that it helped them make more sense of the text. Six of the 11

students, or 54.5%, explained that paraphrasing helped them with words, whether it was putting

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others’ words into their own words, making the words smaller, or reading and understanding

words better. Student responses to the three interview questions can be found in Appendix L.

Conclusion

As was established at the beginning of this chapter, the majority of students in grades 3

and 4 in the district in which this study took place are not proficient grade level readers. This is

an issue that must be addressed and eradicated, because this grade level band is a critically

important time period in the life of a student. They are expected to learn content from

increasingly complex informational and expository texts that are much more complex in

structure, vocabulary, and content. Additionally, more and more reading is taking place digitally.

However, as was established from a review of the literature, students’ exposure to, and direct

reading instruction using informational texts, and reading in an online format, is not adequate to

ensure students’ success as readers and learners. Further, as was established previously through a

review of the literature, there is an elusive and persistent gap in reading achievement between

White, middle-class students and students of color, students from low socioeconomic families,

and students for whom English is not their first language. Chapter 5 synthesizes the results of

this study and provides recommendations for future research. The chapter outlines the many

limitations of this study that were unforeseen to the researcher when designing this study.

Finally, and for this researcher most importantly, Chapter 5 discusses implications and

possibilities for classroom instruction.

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CHAPTER FIVE: DISCUSSION, RECOMMENDATIONS, AND IMPLICATIONS

If we teach children today as we taught yesterday, then we rob our children of tomorrow.

-John Dewey

Introduction

The research that took place during the course of this study was born from my desire to

better understand the role of the text and its characteristics in students’ comprehension. Further, I

wanted to better understand the struggle students from different backgrounds and lived

experiences face when “reading to learn.” Finally, I was keenly interested in how students

interact with text in an online format, as new literacies continue to evolve and technology is

changing the way we learn. While research on online and digital reading has been part of the

literature for the past several decades, it is still in its relative genesis because, as Baron (2017)

eloquently states, “digital technology is still in its relative infancy. We know it can be an

incredibly useful educational tool, but we need much more research before we can draw firm

conclusions” (para. 6). The more digital technology evolves, the more it finds its way into our

teaching and learning, and as a district administrator overseeing teaching and learning, I need to

bring the most effective programs, pedagogy, and resources to my district in order to help

students navigate and comprehend the texts they are reading.

As stated in Chapter One, comprehension is the ultimate goal of reading. It is being able

to both understand text and make new meaning from it. Therefore, scaffolding and support for

comprehension early on is critical to later success as a reader, as a communicator, and as a

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critical thinker. Strong readers read more often, and the amount and the variety of reading in

which they engage directly contributes to their academic achievement skills and their ability to

obtain a good education (Cunningham & Stanovich, 1997; Rapp, van den Broek, McMaster,

Kendeou, & Espin, 2007; Sparks, 2014). Unfortunately, as the reading struggle for many students

persists year after year, the capacity of some students to learn and deeply understand new and

more complex content and topics dwindles. Additionally, poor reading skills can lead to less

motivation to read, which may in turn lead to less time reading and less development of

comprehension skills (Cain & Oakhill, 2011; Guthrie, 2015; Troyer, Kim, Hale, Wantchekon, &

Armstrong, 2019). As a researcher, district leader and educator, I am plagued by the persistent

fact that a majority of students in the district in which this study took place cannot comprehend

grade level text. This trajectory must change, and at a pace not yet realized.

It is for all the reasons mentioned above that I conducted this mixed-methods study,

which was designed to answer the question, What are the essential characteristics of

informational texts that can be used for training reading comprehension strategies in order to

improve the reading comprehension skills of diverse third and fourth grade students? I wanted to

better understand how educators could ensure that the texts used for strategy instruction were

appropriate to the task, the environment, and the child. As the nature of texts continually change

in a digital world, and as we continue to serve an increasingly diverse population of students in

our public schools, the question was further guided by the following sub-questions:

● What are essential text characteristics (length, readability, structure, cohesion,

topics) for the selection of informational texts that can be used for teaching

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reading comprehension strategies, such as paraphrasing, self-explanation,

summarization, and question asking, in a digital format?

● What are additional considerations when selecting appropriate texts for (a) a

racially and ethnically diverse population of third and fourth grade students and/or

(b) students who read below grade level?

To answer the questions, I used a design-based implementation and mixed-methods

approach for research. Because of the iterative nature of this research study, I collected

qualitative and quantitative data from both practitioners and students. The data collection

methods of a focus group, student reading attitude inventory, observational notes, paraphrasing

quality data, and short student interviews were used to explore answers to the above questions.

The data shed light on basic background knowledge of the students with regard to grade level

science topics, their attitudes toward reading, and how well they were able to paraphrase short

texts that they read. It was important for me as a researcher to include the voice of the educators

and the experiences of the students. These are the voices of the practitioners and the ones for

whom the research will ultimately benefit. Design-based implementation research (DBIR) can be

tested and refined in the classroom where the real differences are found.

The results from this study provided interesting information for future research and

classroom implementation. This chapter presents a discussion of the findings and conclusions

from the research, focusing on each research question. It discusses overarching themes that

emerged from data collection and analysis, and connects those learnings to the extant literature.

Several delimitations and unforeseen limitations to the research design and process both existed

and presented themselves while conducting this research, and are discussed in detail. This

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chapter further discusses how this study informed the larger research university study for the

creation of the iSTART-Early online comprehension intervention tutoring tool.

Recommendations for future research are offered, especially with regard to

comprehension and vocabulary instruction; gender, grade and informational text; teacher

preparation and the influence of gender; reading intervention; and the use of online text and

digital tools in teaching reading. Beyond recommendations for research, however, the current

research must also inform practice. As I am not only the researcher, but also a public school

district administrator overseeing curriculum and instruction, I offer implications for classroom

practice as they align to current and future research. Finally, I also offer my reflections and

myriad learnings that emerged throughout the process of conducting this study.

Discussion of the Findings

As was established firmly through the review of the literature for this research study,

reading comprehension is complex and is the interaction of a reader’s cognitive processes on the

text, such as background knowledge, goals and purposes for reading a text (such as for academic

or recreational purposes), and text structure (Castles, Rastle, & Nation, 2018; Pearson &

Cervetti, 2015). Further, a focus on situation, which is an expansion of the idea of context, brings

into play a sociocultural element, which includes an implied or stated task for reading (Fox &

Alexander, 2017; Hartman, Morskin, & Zheng, 2010), and can include such elements as attitude

or motivation, self-efficacy, and content knowledge. The construction integration (C-I) model

(Kintsch & van Kijk, 1978; Kintsch, 1983; Snow, 2002) provided the structure for this research

study in that I was trying to gain a greater understanding of reading comprehension through a

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more balanced view of identified struggling readers and informational texts they were being

asked to read in the context of summer targeted services. The C-I model provided me with the

framework of understanding when analyzing my findings, as it uses both bottom-up processes,

such as what foundational skills were needed to understand unfamiliar words, and top-down

processes, such as prior knowledge. Further, it helped me to better understand how the students

were showing their comprehension of the texts presented to them through a web-based format.

Essential Characteristics of Informational Texts

The main question guiding this research study focused on essential text characteristics of

informational texts needed in the selection of texts for use in an online reading comprehension

strategy tutoring tool for struggling students in grades three and four. Expository and

informational texts have structures that need to be taught while teaching reading; they have

increasingly complex structures and require more demanding processing skills in order to

comprehend them (McNamara,et al., 2011; Santoro, Baker, Fien, Smith, & Chard, 2016). They

have, as Duke (2000) pointed out, strong noun and verb constructions and text structures that are

unique, such as graphs and diagrams. These are all essential text components students can begin

to learn early on in school. If they do so, this knowledge will lead to strong reading

comprehension later because, as McNamara et al. (2011) emphasize, using knowledge to

comprehend depends in part on the text genre and text features.

For the purposes of this study, a focus group of current teachers and literacy experts was

gathered; they read texts created for this study to identify core parameters for informational text

development and selection. The results of the focus group discussion on essential characteristics

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of texts revealed a number of themes that were used to create texts for this study. The theme of

text structure had the highest number of mentions, followed by instructional pedagogy,

engagement and vocabulary. Interestingly, the themes of self-efficacy, motivation, and prior

knowledge, while identified as themes throughout the discussion, had the lowest number of

explicit mentions by the focus group. While conducting the review of the literature, however, I

found that prior knowledge was a critical component of successful reading comprehension; a

solid knowledge base of content, vocabulary and text structure helps students navigate

increasingly complex texts that are used in schools to teach content and to build new knowledge

(Afflerback, 1990; Bailey & Heritage, 2008; Goodman, et al., 2017; Kendeou & O’Brien, 2017;

Kendeou & O’Brien, 2016; Nagy, et al, 2012; Pearson & Billman, 2016; Rupley, 1075;

Willingham, 2017; Willingham, 2006). The fact that these themes had the lowest number of

mentions tells me that we can and should provide more professional learning for teachers on the

importance of these themes in successful reading comprehension.

When creating the texts, structure was a central focus, once determination of the topics

was complete. The texts used for this study were short, with a mean word count of 351.7 and a

mean paragraph count of 6.3. The texts had low Flesch-Kincaid (FK) scores, with the mean FK

level at 4.3 (fourth grade, third month). No text had a Flesch-Kincaid level higher than a 5.5

(fifth grade, fifth month), and all students in the study stopped reading and paraphrasing prior to

reading that text. The first three texts had a mean FK level of 3.1 (third grade, first month). The

informational science texts used for this study were then analyzed using the Coh-Metrix Text

East and Readability Assessor (T.E.R.A.), and when analyzing both the paraphrase quality data

and text and paraphrase perception data, I found the components of the Coh-Metrix T.E.R.A. for

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each text to be invaluable. The texts themselves were presented to the students in order of easiest

to most difficult, based on five T.E.R.A. text dimensions: narrativity, syntactic similarity, word

concreteness, referential cohesion, deep cohesion. Additionally, the Flesch-Kincaid (FK)

readability score of each text was also used as a determinant of ease. Of these components,

generally, the most widely known by staff in the schools is the FK score. However, the other five

are extremely important for practitioners to understand, as informational text has structures that

differ from purely narrative texts, such as short stories and novels, and a student’s

comprehension of a text is influenced by the structure that is used to convey the information

(Kendeou & Van den Broek, 2007; McNamara, et al., 2011).

The Coh-Metrix analysis of the texts used in this study revealed that while the texts were

expository, which is a genre that is generally more difficult to process, comprehend and

remember, they were cohesive, syntactically simple, and had relatively high word concreteness.

Further, the texts had Flesch-Kincaid scores that were appropriate for the grade levels of students

participating in this study. Given this analysis, the texts were appropriate for use in an online

format by the students participating in this study. However, both qualitative and quantitative data

revealed that students struggled to read them.

When analyzing the paraphrase data and looking at the nuances of each text with regard

to Coh-Metrix T.E.R.A. data analysis, no one component was found to be a prime factor in the

ability of students to paraphrase the texts. In fact, the component scores that may have predicted

higher paraphrase scores, such as a higher narrativity component score or a high deep cohesion

score, did not positively correlate to higher paraphrase scores. I analyzed the students’

paraphrase scores coupled with the component scores of the reading indices, and I found that a

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less difficult or complex text structure itself was not enough to ensure student success. The

students needed exposure to many different text structures in order to build their capacity to

navigate through them. The students struggled with all of the texts presented to them, regardless

of the structure.

These findings were of great interest to me as both a teacher and administrator, as they

confirm the review of the literature with regard to the influence of text structure in

comprehension (see Duke, 2000; Kendeou & Van den Broek, 2007; McNamara, et al., 2011).

Successful student comprehension of the texts did not fall within the predictable pattern of

easiest to most difficult text. There were, not surprisingly, nuances in the students’ success with

the texts, which can be partly illustrated by the differences in the structural components of each

text. However, the findings of this study corroborate what the literature continually affirms: the

need for students to be exposed to, and explicitly taught, myriad informational text structures and

syntax as well as the content (Duke, 2000; Greenleaf & Valencia, 2016; Jeong, Gaffney & Choi,

2010; Kendeou & Van den Broek, 2007; Lipson, 1982; McNamara, et al., 2011; Ness, 2011;

Santoro, et al., 2016). Further, the literature affirms the need for students to learn new

information, including text structure and syntax, correctly at the outset in order to mitigate the

need to correct inaccurate information later on (Afflerbach, 1990; Goodman, et al., 2017;

Kendeou & O’Brien, 2016; Lipson, 1982).

When the text structure is more difficult for or less familiar to the reader, motivation and

engagement in the subject matter or content of the text play an important role in helping students

navigate more complex texts. Therefore, it was important to analyze the data collected on the

students’ perceptions of the texts they were reading and paraphrasing. This was particularly

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important given the fact that the students had rather limited knowledge of grade level science

concepts, illustrated by a mean percentage score of 49.26% on the science pre-assessment.

Motivation and Engagement With Digital Text

Motivation and engagement play a large role in student success with reading

comprehension (Barber, et al., 2018; Christ & Sharma, 2018; Christenson, 2012; De Naeghel, et

al., 2012; Guthrie, 2015; Guthrie & Cox, 2001; Guthrie & Wigfield, 2000; Guthrie, et al., 2010;

Resley & Christenson, 2012; Skinner & Pitzer, 2012; Troyer, et al., 2019; Unrau & Quirk, 2014;

Varuzza, et al., 2014; Wigfield, et al., 2008). Further, technology can provide help or hindrance

for students, depending on how they have been taught to navigate the environment (Dalton &

Proctor, 2008; Leu, et al., 2013). The qualitative observational data I gathered aligned with the

review of the literature. When analyzing the observational data collected while students were

engaged in particular tasks, I was able to focus on the behaviors of the students. There were

several elements that the data analysis revealed that appeared to affect students’ motivation and

engagement.

Student Engagement in Watching, Reading, and Paraphrasing.

The first activity that the students engaged in was the short instructional video on

paraphrasing, and it appeared that video was an engaging medium for the students. It was noted

that all students but one were intently watching the video, and the one who was distracted was

able to be quickly redirected. Some students watched it more than one time before they began to

read. The qualitative observational data reflected their engagement; the indicator of “Other” on

the student observational form for text reading and responding (see Table 4.13) had the highest

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single mean percentage of all engagement indicators. This finding was not surprising, as it took

students over four minutes to watch the instructional video one time and during this time it was

noted that only one student was distracted and redirected two times. The students seemed

comfortable and familiar with the format.

Second, engagement and motivation were affected by the act of reading and

paraphrasing. Initially, the students appeared eager to begin reading and paraphrasing, and began

this activity within a reasonable amount of time. However, some students began showing signs

of disengagement nearly right away. For the most part, students were easily redirected to the task

of reading and paraphrasing, as there were few minor distractions in the classrooms themselves.

Analysis of the observational data showed that students spent approximately half of their time

actively engaged in reading and paraphrasing. This finding was not surprising; watching the

instructional video on paraphrasing took time. Also, students also engaged in other activities

related to reading and paraphrasing, such as using a search engine to check the spelling of a

word.

There were other mitigating factors that affected the engagement and motivation of the

students. During the reading of the passages, many students struggled with vocabulary. While the

amount of text displayed at one time on the screen was relatively small, I observed that there

were, at times, more difficult words displayed on the screen that were not defined for the

students until after they had to paraphrase a sentence that included the more difficult vocabulary.

Those students who were more adept in technology skills utilized Spellcheck and a search engine

to both help them understand what a word meant or how to spell it correctly. Some students

simply asked me for help in defining a word. The qualitative observational data showed that

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many students appeared to concentrate very intently on attempting to spell words correctly,

which was something I did not anticipate observing. It is presumed that the desire to spell words

correctly also slowed them down in their paraphrasing.

Another skill that led to a decrease in the rate of paraphrasing had nothing to do with the

reading of the passage, but affected the creation of paraphrases and again, it was something I did

not anticipate. Nearly all students were not adept in using a keyboard. They appeared to exert

considerable time and effort looking for the right key on the keyboard, which again slowed the

process of paraphrasing considerably. Students who struggled to type while they were reading

the texts appeared to become less engaged in the texts. Two students in the study could not

complete even one text; they simply gave up on the task and asked to be done. Their work was

not captured in the Qualtrics tool.

Texts as Factors in Engagement and Motivation

I analyzed the Coh-Metrix components of each text compared to the students’ perceptions

of the text to gauge a better understanding of engagement. The texts were presented to the

students in the Qualtrics tool in order from least to most difficult. However, the nuances in text

components, such as narrativity (how a text is more or less narrative in nature) and deep

cohesion, (how well the ideas and information of the whole text are connected) may have been a

factor in the unpredictability of paraphrase quality, other than the first text presented. “How a

Star is Born,” the first text presented to the students, had the highest number of paraphrases and

the highest number of text and paraphrase perceptions. More students completed that text than

any other. It was the first text and the first time students engaged in the task of reading and

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paraphrasing. When looking at the possibility that this was a text students really liked, the text

received two of the three total ratings of “didn’t like”among all texts, and 46% rated it “okay” or

“didn’t like,” which was somewhat in keeping with the ratings of all the texts, although it did

receive two-thirds of the rating of “didn’t like.” Furthermore, given the fact that this text was

considered the easiest of the texts, it was somewhat surprising that this text did not have the

highest percentage of paraphrases scored of the first four texts, or the lowest percentage of

paraphrases filtered out, something that may have been predicted given its relative ease. This

finding seemed to validate the literature emphasizing the need for texts that students like and

want to read.

This study focused on characteristics of texts that could be used in an online

comprehension intervention. Therefore, I wanted to see the role that technology possibly played

in student success. Technology is rapidly changing, and is changing the way students interact

with texts. Focusing on the first sub-question was vital to better understand how the students

interacted and struggled with the texts in an online format, what were reasons for their

experiences, and what factors of being a diverse learner in terms of language, ethnicity, and

socioeconomic status played a role in their success and/or struggle to comprehend.

Essential Text Characteristics in a Digital Environment

The first sub-question guiding this research focused on texts presented to students in an

online format, as the research was informing a larger research project to create an online

comprehension strategy tutoring tool for struggling students in grades three and four. The

question, What are essential text characteristics (length, readability, structure, cohesion, topics)

for the selection of informational texts that can be used for teaching reading comprehension

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strategies, such as paraphrasing, self-explanation, summarization, and question asking, in a

digital format?, aimed to inform the role of technology in the student experience.

As mentioned previously, technology continues to change how we interact with text;

therefore, literacy continues to evolve (Hartman, et al., 2010; Leu, et al., 2015; Leu, et al., 2013).

Additionally, technology has changed the way we acquire and read information - from

240-character news “articles”, blog posts and text messaging to using the Internet to find and

process information (Goldman, et al., 2012; Leu, et al., 2015). Technology has also enabled

classrooms to utilize programs and other software to provide students with the opportunity for

independence, additional practice, and different formats in which to learn (Dalton & Proctor,

2008; Hooshyar, 2016). However, students must be taught how to use the technology. The term

digital divide defines the inequitable access to computers, the Internet, and other technologies.

This inequitable access results in inequitable technology skills that are needed for online reading.

While some students in this study understood how to access a search engine (a more

advanced online skill), most had extreme difficulty typing (a basic technology skill), which

slowed them down considerably. Some students typed with just one finger, hunting and pecking

to find the correct key to press. Others typed with two fingers; they were a bit faster in

construction of their paraphrases, but not much faster. I observed one student, however, who was

quite familiar with a keyboard. This student was able to complete more texts and generated a

high number of paraphrases. Not all of their paraphrases were of high quality; however, the

student used less cognitive load in the act of typing than did others who were struggling in their

typing.

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While technology brings exciting opportunities, access to technology is quite limited for

many students, especially those from lower socioeconomic means and low-income students of

color (Auxier & Anderson, 2020). This lack of opportunity continues to disenfranchise already

marginalized students, and my observations of the students interacting with the technology

confirmed the review of the literature on the digital divide. Nearly all struggled with technology.

Diversity of Students in Grades Three and Four

The second sub-question for this research study focused on the students themselves, by

asking, What are additional considerations when selecting appropriate texts for (a) a racially

and ethnically diverse population of third and fourth grade students and/or (b) students who read

below grade level? The students who initially obtained permission to participate in this study

were all in third and fourth grade, the target grades for this research, and all had been identified

by the district as reading below grade level. All but two students qualified for free- or

reduced-price lunch, and all were students of color. Furthermore, all but two students were

English language learners (ELs). Research cited previously (Hoff, 2013; Neuman & Celano,

2001; Neuman & Moland, 2019) pointed out that the literacy achievement gap between these

populations of underserved students and their White, middle-class peers begins in kindergarten

and continues to persist as they matriculate through the grades. Culture and ethnicity play a

central role in engagement and motivation (Bingham & Okagaki, 2012). Research cited

previously (Allington, 2014; Lindsay, 2013; Luo, et al., 2019; McQuillan & Au, 200; Neuman &

Celano, 2001; Neuman & Moland, 2016) cites the need for students of color and low

socioeconomic students to have easy access to books, as access to resources and quality reading

time positively affect reading comprehension, growth, and achievement. The more students read,

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the more they are building prior knowledge, including vocabulary and exposure to structure and

syntax, and the more they are able to apply that knowledge to new texts in order to comprehend

them (Afflerbach, 1990; Kendeou & O’Brien, 2017; Kendeou & O’Brien, 2016; Pearson &

Billman, 2016; Rupley, 1075; Wharton-McDonald & Erickson, 2017; Willingham, 2017;

Willingham, 2006). However, students from low-income families and multilingual learners, often

from low-income families, face challenges in procuring the types of resources needed to build

language and literacy skills. These challenges affect their ability to build the foundational

concepts and knowledge needed to grow in reading success and achievement, including

academic vocabulary (Allington, 2014; Pribesh, Gavigan, & Dickinson, 2011; Townsend, et al,

2020).

My observations of the struggles the students experienced while participating in the

reading and paraphrasing of texts validated the research uncovered through the review of the

literature. As I analyzed my qualitative observational notes, I found many students trying, often

unsuccessfully, to decode a word or figure out its meaning. They were having difficulty, and yet

the literature confirms that both decoding skills and comprehension skills contribute to reading

comprehension performance (Kendeou, et al., 2009; Shanahan & Shanahan, 2008; Storch &

Whitehurst, 2002). Further, EL students have smaller English vocabularies, which will affect

their ability to comprehend a text, and those gaps widen with age (Graves, 2015; Hart & Risley,

1005; Hoff, 2013; White, Graves, & Slater, 1990). This finding from the review of the literature

was evident in this study: students in grade 4 generated over twice the number of paraphrases as

did their third grade counterparts, with over ten times the number of paraphrases earning the

highest score and less paraphrases filtered out.

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Because the amount of prior knowledge that a student has on a particular subject has such

influence on comprehension of that subject-area text, it was important to gain an understanding

of the students’ background knowledge in grade-level science concepts. When analyzing the

students’ scores on the science pre-assessment, it became clear that students had limited

knowledge of basic grade-level science concepts. In looking at the data, the students who had the

highest science pre-assessment scores (75-100%) also had the highest total number of

paraphrases, and the highest number of paraphrases earning scores of 2 or 1. This group also had

the lowest number of paraphrases that were previously filtered out. Conversely, while the group

of students scoring below 50% on the science pre-assessment had a greater number of total

paraphrases than the group of students scoring from 50%-74% on the science assessment, they

had the lowest number of paraphrases earning a score of 2 or 1 and the highest number of

paraphrases that were previously filtered out. This finding is in line with the review of the

research on prior knowledge and warrants continued research on the effects and successful ways

of building background knowledge of young learners as they continue on their reading journey.

I found that the lack of prior knowledge of science concepts was evidenced also by the

students’ struggle with vocabulary, and this contributed to the students’ struggle with

comprehension and paraphrasing. Knowledge of content-specific vocabulary is crucial to

navigating unfamiliar informational texts in an academic setting (Bailey & Heritage, 2008; Nagy,

et al., 2012), especially for English learners (Graves, 2015; Hart & Risley, 1995; Hoff, 2013;

White, et al., 1990) and this study confirmed the evidence found in the literature: Vocabulary was

one of the biggest obstacles the students encountered when trying to comprehend the texts. This

finding is unsurprising for a few reasons. First, the score of the narrativity component of the

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Coh-Metrix T.E.R.A. analysis was the lowest score of all dimensions. Low narrativity

component scores are common with expository texts, which typically have a lower narrativity

component (Jackson, et al., 2016) and which have more complex structures and vocabulary that

need to be understood to make meaning (Duke, 2000; Nagy, et al., 2012). Texts that score high in

narrativity may have a relatively large number of more common words and more verbs, which

help students make connections (Jackson, et al., 2016).

Second, both the quantitative and qualitative data gathered in this study revealed the

students’ struggle with the words they were reading, yet strong comprehension skills are linked

to a wide vocabulary and strong understanding of syntax (Anderson & Freebody, 1981; August

& Shanahan, 2006; Chall & Jacobs, 2003; Hoff, 2013; McKenna & Dougherty Stahl, 2015;

Rupley & Nichols, 2005; Stahl & Fairbanks, 1986; Wharton-McDonald & Erickson, 2017). As

the texts presented to the students in this study became more difficult, fewer students completed

them and, for those who did complete them, the number of paraphrases earning higher scores

dwindled as well. This finding confirms the review of the literature which emphasized that a

primary grade focus on foundational reading skills, a greater use of narrative texts, less focus on

comprehension and text structure (especially with informational texts), and less explicit

meaning-making strategy instruction, puts students at a disadvantage (Beerwinkle, et al., 2018;

Chall & Jacobs, 2003;Chall, et al., 1990; Duke, 2000, Jeong, et al., 2010; Strong, 2020).

As mentioned earlier, while conducting observations, I noticed that the text on the screen

that students were asked to paraphrase was presented to them prior to more difficult vocabulary

being defined. In short, the definitions of vocabulary words were presented after the paraphrase

was captured by Qualtrics. This sequence neither helped the students make meaning nor helped

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them create quality paraphrases. Some students were pointing at the computer screen, trying to

sound out words, asking me what words meant, and even using a search engine. While their

limited vocabulary hindered comprehension of the texts presented to them, it was both

fascinating and encouraging to observe them actively trying to problem solve to continue with

the text. At least initially, most students appeared to be motivated to continue.

Observing this motivation to continue was not lost on me. Engagement and motivation is

more of a concern for students of color (Fredricks, Blumenfeld, & Paris, 2004; Rumberger, 1987;

Rumberger, 1995) and, as stated previously, the students participating in this research study were

all students of color. Furthermore, they were identified by the district as below-grade level

readers, using state and local assessment data. Therefore, it was essential to capture the students’

general attitudes towards reading.

The Elementary Reading Attitude Survey (ERAS; McKenna & Kear, 1990; 1999) was

used to gather data on the students’ recreational reading and academic reading attitudes, and

provided an overall reading attitude score. The review of the literature revealed that attitude

impacts reading achievement (McKenna & Kear, 1990; Petscher, 2010; Walberg & Tsai, 1985),

and when analyzing the paraphrase quality data with the ERAS data, findings were predictable in

the total number of paraphrases generated and total number of paraphrases scored (not filtered

out). The group of students scoring between the 76th - 99th percentile on the total reading

attitude survey score generated the highest number of paraphrases and had the lowest number of

paraphrases filtered out, which validates the review of the literature on the positive impact of

reading attitude on comprehension.

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Disaggregating the data by gender uncovered some very interesting findings. First, girls

had higher Elementary Reading Attitude Survey (ERAS) scores across the board, including

academic reading scores, than did the boys. This was somewhat surprising, given the general

view that boys tend to like non-fiction texts more than girls. While the boys in this study had

lower reading attitude scores than the girls in both grades 3 and 4, they gave higher text

perception ratings to the texts used than did the females, and while they generated fewer

paraphrases, their paraphrases were of higher quality than those generated by the females.

The girls in grade 4 also outperformed the boys on the science pre-assessment, which is

interesting, because it is in keeping with their academic reading attitude at that grade level: there

was also a five point difference between girls and boys in their academic reading attitude scores

in fourth grade. Although boys made up only 30.8% of the students participating in reading and

paraphrasing of texts, they generated nearly 50% of the paraphrases earning a quality score of 2.

Overall, while boys had lower ERAS scores, lower science pre-assessment scores, and lower

numbers of paraphrases, their paraphrase quality was stronger, which translated into better

comprehension of the texts. These findings suggest a potential dissociation between attitudes and

interest: While the boys had lower academic reading attitude scores than the girls, they were

more interested, and ultimately more successful, in navigating the science texts. Thus, when

contemplating informational texts used with third and fourth graders, it would be wise to

consider interests by gender at that age. When analyzing the findings I could not help but wonder

whether other texts related to the same topics would have been more interesting for the girls.

While the boys gave higher text perception ratings to the texts than did the girls, the text

topics were of overall interest to all students as evidenced by their ratings of the texts. Of the 40

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ratings given on whether or not the students liked the texts, 55% were “really liked” and another

37.5% were “okay.” There were only three ratings of “didn’t like,” constituting 7.5% of the total

ratings. These findings are encouraging; the review of the literature showed that interest

contributes to comprehension (Barber, et al., 2018; Ebe, 2010; Ladson-Billings, 1995; Kourea,

Gibson, & Werunga, 2017; Tatum, 2006, Troyer, et al., 2019), and the texts overall received

positive ratings, which is a factor of text selection for all instructional purposes, but especially

for use with reading comprehension intervention instruction. Populating an intervention tool that

students will access independently with texts that match their interest will aid in the engagement

with the intervention.

Of the 187 total paraphrases that students generated, 31 earned a 2, the highest score,

which equals 16.6% of the total number of paraphrases. Further, 64 paraphrases, or 34.2% of the

total number, earned a paraphrase quality score of 1. Adding these two groups together, 95

paraphrases scored a 1 or 2, which is 50.8%, or slightly over half of all paraphrases generated.

This was a promising number, despite the struggles the students displayed when reading and

paraphrasing the texts.

Both the qualitative and quantitative data confirmed that all of the students did indeed

struggle to read and comprehend the texts presented to them in Qualtrics. However, they also

engaged in behaviors, such as watching the instructional video more than once, sounding out

words, and using a search engine. In my over 25 years in education, I have encountered teachers,

administrators, and other staff who continually view English learners (ELs), students of color,

and students from low socioeconomic families from a deficit lens - that they are somehow unable

to learn at levels of their White, middle class peers. I argue that these preconceived notions

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perpetuate the reading achievement gap that continues to persist. Furthermore, I argue that the

students in this study were trying hard to be successful.

The belief in students and their efficacy must take a more prominent role in schools,

especially for students who are experiencing structural racism within impoverished communities,

continued negative stereotypes, and systemic racism in their schooling (Reynolds, Sneva, &

Beehler, 2010; Tatum, 2006; Thomas, 2018). Watching the students reading and paraphrasing

texts for this study confirmed to me that prior knowledge and lived experiences are less likely to

be prominent in many of the instructional materials and assessments used in our classrooms

(McCullough, 2013). It is as important for students to make personal connections to their school

experiences and learning as it is to provide students with new experiences and learning (Bishop,

1990; Christ & Sharma, 2018; Tatum, 2006). Additionally, it is imperative that we see them as

capable, resilient, determined learners. The students in this study engaged in behaviors that

showed their determination to succeed. Observing them engaging in this type of

problem-solving, especially utilizing online resources such as search engines, holds great

promise for future research. This view of students is not limited to the grade level students who

participated in this study. We must hold this view of promise for all students, beginning with our

youngest learners. This study, however, focused on third and fourth grade and used specific texts,

which delimitations will be discussed in the next section.

Delimitations to the Research Design

Delimitations to this particular research study are based upon the online reading strategy

tool that will be ultimately created and for which this study provided initial data. This research

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helped to inform a larger study funded by the Institute for Educational Sciences (IES), which is

being conducted in conjunction with a partnership between two highly-respected research

universities in the United States. This partnership was developed to create a comprehension

strategy tutoring tool that will be ultimately created for third and fourth grade students across the

United States who are struggling with reading comprehension. The tutoring tool will focus

specifically on the comprehension of informational, expository texts, based upon the research

that shows early elementary literacy instruction focuses little on informational texts (Beerwinkle,

et al., 2018; Duke, 2000, Jeong, et al., 2010; Strong, 2020), yet beginning in fourth grade there is

a marked increase of informational texts used to learn content (Castles, Rastle, & Nation, 2018;

Goldman, Snow, & Vaughn, 2016; Guthrie, et al., 2004; Sweet & Snow, 2003). Therefore,

because of the scope of the larger study, the cohort of students participating in this study were

limited to third and fourth grade students. While limiting, this factor helped to focus on two

important grade levels in a student’s academic and literacy trajectory.

A second delimitation was that the texts were limited to expository texts. In the case of

this study, texts focusing specifically on grade level science concepts as determined by the state

science standards. This is an important focus, however, because science is a subject that is

language-rich, requiring students to develop strong background knowledge and academic

language (Nagy, et al., 2012; Townsend, et al., 2020). I chose to use science texts for this study

because limited time has been given to science instruction in the elementary grades and this

provided another avenue for students to read about science topics. The iSTART-Early

comprehension intervention strategy tutoring tool, currently being created by researchers at the

large university with which my district partnered, will focus on expository text, and it will

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require a large bank of accessible expository texts for students to read, including texts that

continually expose students to science concepts, among others. This will be a very useful tool for

students and teachers.

I was excited for the scope of the i-START-Early research and my contribution to it,

given my background as a strong literacy educator and my position as a district administrator

overseeing K-12 literacy. Further, there was a strong partnership between the district and the

large research university for the past several years, with the district agreeing to be part of

research that focused on the creation of an intervention tool for inference in the primary grades.

My research study was helping to inform texts which would be populated in the iSTART-Early

comprehension intervention tutoring tool, and served research already in progress. When initially

designing this research, neither I nor anyone on the university’s research team could possibly

imagine what would face us beginning in the spring of 2020.

Limitations to the Research Design

The COVID-19 pandemic disrupted the face of K-12 public education, not only in the

United States, but around the world, with 188 countries closing or severely limiting in-person

learning (Hebebci, Bertiz, & Alan, 2020) in the spring of 2020. The district in which this study

took place closed schools and hastily turned to distance learning. Further, the district altered its

summer targeted services program. All of these factors led to significant limitations in both

phases of this research study. The first limitation came with regard to the work of the focus

group.

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Limitations of Study 1

Focus Group Work. In the case of the district in which this study took place, all

pre-K-12 in-person student learning was suspended beginning on March 17, 2020 (March 15,

2020 personal communication). The district struggled to provide devices to families who needed

them, and reliable access to the Internet in the homes of many district families was a

considerable issue with regard to student learning. The district was able to purchase a limited

number of hotspots, but it was not enough to satisfy the widespread need of families. Those staff

not directly interacting with students on a daily basis, including literacy experts and district

administrators, shifted focus to the creation of math and literacy materials that could be either

picked up by families who did not have access to the Internet, or mailed or driven to their homes.

These materials were created weekly and took up a tremendous amount of time and energy to

produce and distribute.

End-of-year state-required and district-required standardized testing was suspended. This

meant that teachers attempted to assess locally in reading and math; district staff and the literacy

experts, among others, were charged with helping teachers create and administer assessments.

These efforts were not always successful because of mitigating factors, such as sporadic access

to students. The rapid switch to distance learning and all that it required, including the need for

preparation and the full teacher, student and family support limited the focus group in two areas:

first, it limited the number of people who were willing to volunteer to be on the focus group, and

it limited the ability of the focus group to convene more than one time.

Because the focus group could only meet one time, the number of texts initially included

for them to read and review was limited as well. The group was provided with 23 short texts to

read prior to meeting, and they provided feedback on those texts. Because of the inability to meet

again, I coded the feedback to identify themes that I then sent to the text writers. They

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communicated that this information was enough to create texts to be used for the study.

However, had the focus group been able to convene more than once, I believe that we could have

delved deeper into the themes initially identified to gain a better understanding of what were

important text characteristics to include for this tutoring tool.

Limitations of Study 2

The Summer Targeted Services Program. This study was planned to take place during

summer targeted services at the outset, which was an ideal time to focus on new ways of

teaching and learning. Further, because this study was helping to inform a larger study on

reading intervention, the students participating in summer targeted services were an ideal

population on which to focus. My original plan was to spend time with the students, teaching

them specific reading comprehension strategies and gathering a great deal of observational data

as part of this research. However, due to the continuation of the COVID-19 pandemic, the

traditional summer targeted services program was considerably altered in terms of the following:

the length of the summer program, the length of the day, and the format for learning, which now

was required to include both distance and in-person learning. This meant a significant decrease

in the number of students who attended in person.

The length of the summer targeted services program was reduced by 40%, from five

weeks to three weeks. However, the traditional number of days per week, which was four,

remained the same. The length of the day was reduced by one-third, from six hours to four hours.

Prior to 2020, the typical summer targeted services day started at 8:00 a.m. and ended at 2:00

p.m., with breakfast and lunch served on site, extensive academic programming, and recess.

Because of COVID-19, the hours were 8:00 a.m. until noon. These four hours included breakfast

and recess, but a take-home lunch was given to students as they left for the day.

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The format of learning was considerably altered as well. The time still included breakfast

and recess as in the past. However, 25% of the summer targeted services instructional time was

devoted to social-emotional learning. This meant a marked decrease in the time devoted to

academic learning, including time for structured literacy work. The abbreviated literacy time

frame meant that, for the purposes of methodology, only one reading strategy could be taught

and assessed to show comprehension of texts created for the purposes of this study.

The decision to provide parents choice of in-person or remote learning for their students

further caused me to choose how I was going to conduct my research. I chose to conduct this

study on the students who were participating in person, rather than remotely, as I had more

control over their physical environment. Working with students in this environment enabled me

to engage with the students physically, encouraging them to stay engaged and helping them with

questions or issues that arose. Also, this environment enabled me to observe students both

individually and collectively. I was, however, only able to work with one reading strategy.

Finally, choice itself provided limitations. Due to the severe restrictions placed on school

districts, the choice given to families with regard to delivery of instruction, and the fear many

families had of their students being in person, there were a considerably smaller number of

students who were available to participate in this study than had been originally planned. Social

distancing considerably restricted the numbers of students attending the summer targeted

services program in person. There was limited space available for in-person instruction. Physical

classrooms for the elementary program were limited to nine students, with desks spaced a

minimum of six feet apart. There were strong recommendations on mask usage.

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Many families chose to keep their children at home to participate in summer targeted

services remotely, and the decrease in in-person attendance was not consistent across

demographics, with decreases ranging from 49% (White participation) to 85% (students

identifying as two or more races). Students identifying as Hispanic/Latino had the highest

percentage of students participating overall in summer targeted services. Their in-person

numbers, although having decreased by 51% as a result of the choice of in-person or remote

services, was still the largest population attending summer targeted services in person. There

were few students who identified as Asian, White, and identifying as two or more races, which

meant a limited range of demographics of students participating in this study.

Comprehension Intervention Research Focus.

This study provided essential information for the eventual creation of the comprehension

intervention tool for students in grades 3 and 4, called iSTART-Early. This tool has a module

sequence that was designed similarly to its predecessor, iSTART, which was built for older

students of adolescent age and above. In iSTART-Early, there are five modules planned for the

tool. They incorporate six reading comprehension strategies (paraphrasing, comprehension

monitoring, question asking, elaboration, bridging, and summarizing). The five modules are as

follows:

● Ask It, which is an overview of comprehension monitoring and question asking;

● Reword It, which incorporates the paraphrasing strategy;

● Find It, which also works with paraphrasing;

● Explain It, which works on elaboration, bridging, question asking, and paraphrasing, and

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● Summarize It, which works on summarization and also includes work on finding the

main idea.

The modules are presented in sequential design, with the strategies building off one another.

Reword It, or paraphrasing, is the first module in which students generate responses (the Ask It

module requires only identification tasks).

Because of the COVID-19 pandemic, the researcher had limited time with the students.

Therefore, the team building the eventual comprehension intervention tool for third and fourth

grade, along with this researcher, made the decision to begin with the lowest level generative

strategy only, which is the paraphrasing strategy. Further, due to the little time I could be in front

of the students, the research team created a short paraphrasing strategy instruction video, which

each student accessed via their computer and a set of headphones. The video was a little over

four minutes long. I observed the students and recorded data as they watched the instructional

video.

The paraphrasing video contained modeling of the strategy, and the video could be

accessed over and over again during their time interacting with the texts. However, it was more

difficult to ascertain the level of understanding and learning of the paraphrasing strategy than it

would have been with live, direct instruction. Because of my experience as a teacher, I would

have preferred to use the gradual release of responsibility strategy through modeling, partnering,

and finally individual practice with the strategy to better assess student understanding. The

natural disconnect created between the student and the teacher as a result of the use of a video

may have impacted motivation, engagement, and ultimately the success of the paraphrasing.

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Student Participation Due to Absence.

The rapid spread of the virus during what was still an early phase in the pandemic

touched the families and the students who were part of this study. Even during the research phase

of this study, the recommendation of wearing face shields was first promoted and then rescinded.

Staff began the summer targeted services program by wearing face shields, which provided the

opportunity for students to see their teachers’ full faces when talking. Shortly into the summer

targeted services session, however, the recommendation of the use of face shields was replaced

with a recommendation for the use of face masks, by all teachers and students. Young students

were still learning how to wear a mask, and despite their best efforts, it was hard for many young

students to wear the masks properly; the masks also were observed to be somewhat of a

distraction to students who were not used to them. The virus spread very rapidly in the early

summer, and sickness and positive COVID diagnoses of students and/or family members

required a number of students who were attending in person to be absent from in-person

learning, with some of the students, including some of those participating in this research study,

not returning at all.

The absences were more numerous than was typical in a summer targeted services

program in this district (personal communication, June, 2020). Students who began the study

were absent one or more times, or left the summer program altogether. Although 19 students

originally participated in this research study, complete data sets on only eleven students were

possible due to absences. Teachers did not know, from day to day, who would be coming back to

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school. As the researcher, I was in constant contact with the teachers of the participating

students, and they kept me informed as to the status of the students.

Researcher and Teacher.

I would be remiss not to include the biases that I as a former teacher carry with me that

could have influenced the interpretation of the results of this study. The abbreviated time spent

with students required a change in delivery of instruction on paraphrasing. I was unable to build

strong connections with the students and get to know them better as learners, scaffolding as

appropriate and gathering formative data on their understanding of the paraphrasing strategy.

Having worked in this diverse district for over six years, I understand the role that relationship

plays, especially with students of color.

Because of these limitations, which led to the small number of participants and an

abbreviated time frame, there is an inability to generalize the results of the study. However, the

data obtained from in-person observations, focus group discussion, and short student interviews

provided this researcher with information that helped the large research university in their

creation of iSTART-Early. That information will be shared in the next section. Further, it

provided recommendations for further research on reading comprehension pedagogy and the

selection of texts to utilize with students, as it is imperative that the trajectory for a child who is

struggling in reading be shifted. As has been amply supported by the literature, and observed

firsthand during this study, a child’s struggle to read can lead to a much larger struggle in

learning content. That fact alone was my purpose for research in the first place, and I was

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fortunate to be able to partner with a large research university in their creation of an online

comprehension tutoring tool that will ultimately help mitigate that struggle.

The Use of This Study in the Creation of the iSTART-Early Interface

Over the last several years, I was honored to have built a strong, collaborative partnership

between the school district used for this study and a major research university located in the

same metropolitan area. This was a partnership that initially focused on the role that inference

plays in successful reading comprehension in the younger grades. The major research university

had created online tools for improving inference-making in reading; a strategy known to increase

reading comprehension (Kendeou, McMaster, & Christ, 2016; Wanzek, et al., 2018).

The strong partnership between the district and the research university provided me the

opportunity to design a study that would help to inform their creation of a new online

comprehension intervention tool titled Interactive Strategy Training for Active Reading and

Thinking for young developing readers (iSTART-Early), designed specifically for students

during a very critical period in reading development: grades three and four. This tool is a version

of the Interactive Strategy Training for Active Reading and Thinking (iSTART) tool, which was

previously developed for older students. The iSTART-Early tool will focus on informational

texts, particularly science texts. Doing so will provide additional instruction and practice for

students who are struggling with the comprehension of more challenging science texts, thus

improving their comprehension and knowledge of the content. The iSTART-Early tool will focus

on the strategies of comprehension monitoring, paraphrasing, inference

(prediction/bridging/elaboration), question asking, explanation, and summarization by providing

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comprehension instruction and practice that is adaptive in nature and is supplemental to direct

instruction from the classroom teacher. For the purposes of this study, and due to the limited time

spent with students, the decision was made to focus on the paraphrasing strategy.

Paraphrasing is a strategy that can help a reader clarify the meaning of a text, whether it

is a sentence or a paragraph, and thus help improve understanding of main ideas and details in a

text (Hageman, et al., 2012; Nicola, Dascalu, Newton, Orcutt, & McNamara, submitted for

publication). Creating an online tool that would provide feedback to students regarding the

quality of their paraphrases, rather than just letting them know if they paraphrased or not, will

provide an additional layer of understanding for both the student and the classroom teacher.

Using a tool such as this will provide both the student and teacher clarity in how the student

paraphrased the text, such as using semantic similarity or elaboration. The larger research study

needed benchmark information from students to help make decisions on how to populate the

iSTART-Early intervention tool with texts.

The target population for iSTART-Early is students specifically in grades three and four;

therefore, obtaining paraphrases from students in those grades would help build a corpus of

paraphrases that could continue the research on iSTART-Early. This research study on essential

text characteristics provided that opportunity. This study faced significant limitations and

challenges due to the COVID-19 pandemic; however, it obtained a small but significant corpus

of paraphrases which were used in the next steps of iSTART-Early research (Nicula, et al.,

submitted for publication).

The paraphrases that students generated during summer targeted services were used to

create three algorithms designed to assess the quality of student paraphrases, which will then

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provide immediate feedback to the students when they are working in the iSTART-Early tool.

The original algorithm was built to analyze adult paraphrases, and the researchers tested it with

the paraphrases generated in this study to see if the algorithm worked on children’s responses.

The algorithm was successful on children’s responses. As a result of the paraphrases collected

during this study, analyses were made on those paraphrases that are able to be generalized across

different texts, levels of reading, and language (Nicula, et al., submitted for publication).

Along with the quantitative data collected, the qualitative data compiled through this

study can inform continued research in several different areas, including the behaviors of

students when reading and comprehending, as reading is a complex cognitive process. In the next

section I will discuss recommendations for future research.

Recommendations for Future Research

This study attempted to answer questions related to texts needed for an online reading

comprehension intervention that focused specifically on historically underserved struggling

readers in third and fourth grade. The topic is a significant one in public education, as some

students continue to struggle in proficient reading comprehension. The topic is a timely one as

well, given that digital literacies continue to change the landscape of reading. I will discuss

several recommendations for future research.

First, research on reading comprehension strategies in a general education classroom lag

behind the research on basic reading skills. Therefore, more implementation research is needed

to better understand the impact of teaching reading comprehension strategies. The literature is

replete with evidence that the use of informational text helps students build knowledge across a

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wide range of content areas and subject matter. However, the review of the literature also shows

that, especially in the primary grades, the explicit use of informational text to teach reading is

still minimal, despite the findings of Nell Duke over 20 years ago. Narrative text is still widely

used for read-alouds and explicit instruction in decoding and fluency. Informational texts,

though, can have complex structures that students must be taught to navigate, and the texts

require the student to utilize multiple comprehension strategies, which they also must be taught

to use when reading. Further, informational text provides students with rich, foundational and

content-specific vocabulary that can be connected to other subjects and other words, and the

texts provide readers with windows to the world they might not otherwise encounter. Conducting

studies that focus on explicit instruction in reading comprehension strategies and skills using

informational text, especially with younger students, would well serve to inform the body of

literature on reading comprehension.

Second, many students who are part of families with limited economic resources,

students of color, and students for whom English is not their first language continue to achieve

much lower than their White, middle class peers. This persistent achievement gap is caused by

factors that, despite best intentions, have not been eradicated. Not all students of color are

struggling readers, but many are, and we need continued research that focuses specifically on

how educators can and are connecting with and engaging struggling readers of color in the

classroom. Oftentimes, instruction and materials, including texts, are not inclusive of or

responsive to many students’ lived experiences and the assets that come with the varying

cultures, languages, genders, and races that are and can be enjoyed in classrooms of diverse

students. Many teachers bring their own class and experience-based beliefs to the classroom, and

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can often have lower expectations for English learners and other underserved students (Almasi,

et. al, 2010; Emdin, 2016; Jiménez, et al., 2015; Marx, 2000; Moje, 2000; Redding, 2019). A

deeper understanding by teachers of the affective factors that impact reading for students of all

demographics, languages, and lived experiences continue to be warranted. These affective

factors include attitude and motivation, and the role of texts that are culturally relevant, dispel

demographic stereotypes, and empower students to believe in themselves. When analyzing the

qualitative observational data in this study, I was struck by the initial eagerness of the students to

successfully complete the tasks of reading and paraphrasing; for some students that eagerness

waned considerably early on when they realized the task was hard for them. I was also struck by

the determination of some students to persist and problem-solve when they encountered

challenges in making meaning from the texts. Because the texts were presented to the students in

an online format, they had tools at their ready that may not be available when reading printed

text with no device nearby. When observing the students try to use search engines and Google to

help them, I could not help but wonder how teachers can leverage those skills in the classroom. I

also wondered what the teachers would need as far as professional learning to help leverage

those skills that their students have. Studies focusing on students’ reading stamina, persistence,

determination and engagement in informational text, particularly, is warranted, as is a better

understanding of teachers’ perceptions of their students’ assets.

Future research could also focus on the role technology can play in helping to eliminate

gaps between underserved students and their White, middle class peers. Using technology that is

interactive, such as hyperlinks to word definitions, text-to-speech capability, and automated

speech recognition (ASR) for reading response, may provide invaluable scaffolding for

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struggling readers who spend more effort trying to figure out a word than figuring out a main

idea. As I witnessed firsthand during this research study, if the students had been able to take

advantage of such advances in technology, I can only wonder how the results could have been

different. This is a burgeoning field for researchers. Additionally, exploration of the use of

graphics and gamification (such as the use of leveling up, badges, and tokens) and their effects

on engagement, motivation, and ultimately reading comprehension for struggling readers is a

burgeoning field of research to be explored.

With regard to student use of technology for literacy instruction, the well-quoted adage

in schools that “what gets assessed gets taught” must be considered. State assessments currently

do not assess online, digital reading comprehension, but only offline text skills in a computerized

format. The National Assessment of Educational Progress (NAEP) is still in development of a

new reading framework; therefore, this would be an area of research to provide

recommendations. Since research can and does often influence policy, future research showing

students’ variance in digital versus offline reading comprehension would be warranted. Districts

are under tremendous pressure to raise reading test scores that currently only assess offline skills

(Leu, et al., 2008), yet students are spending increasing amounts of time reading using new

literacies, such as social media, blog posts, and apps. As discussed through the review of the

literature, new literacies present challenges, especially for students who already struggle with

traditional print reading, in terms of fluency and critical reading habits (Dalton & Proctor, 2008).

Students need to engage in specific reading comprehension instruction using online and digital

resources. Whether or not states assess digital literacy skills, research on digital literacy

comprehension would serve to inform the body of literature and teachers in the classroom.

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Finally, I believe that this study should be replicated on a larger scale. Because of the

varied impacts of the COVID-19 pandemic and the small targeted sample, no finding could be

generalized. However, this study utilized design-based implementation research (DBIR), which

is a research framework that has been recommended for use with literacy (Mills, 2010). The

research design develops both theory and knowledge of students’ learning in the classroom, as

well as implementation of strong instructional practice (Fishman, et al., 2013). There was much

rich data and I was able to glean themes that I want to share with teachers and administrators in

my district to strengthen literacy instruction, especially in the grades leading up to those on

which this study focused. However, if this study could be replicated on a larger scale, with more

students and with more time, I believe we could learn much from the data and analysis that could

have far-reaching implications for future research and classroom practice.

Implications for Classroom Practice

I believe that research without implementation is just fun reading. My deep belief that

research should inform practice is the reason that I conducted a design-based implementation

(DBIR) research study. Designing and conducting a study using DBIR, no matter the limitations,

helped me to see my work as both a researcher and educational leader with fresh eyes, and I am

compelled to use the knowledge that I have gained to help improve classroom practice. Having

the results of research is one thing; seeing those results make a difference in the daily instruction

of teachers and the learning of students is what I believe is most important. I believe that my

research has several implications for classroom practice.

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There are wide disparities in and low levels of reading achievement in the district in

which this study took place. I have since moved to a different district, and the story is similar:

students of color, students of limited socioeconomic means, and English learners achieve at rates

much lower than their White, middle class counterparts. These realities in different districts

solidify my belief that implementation of the recommendations of reading research in classrooms

is absolutely necessary. “Most education research must be situated - framed locally by the

conditions of class, community, program, local history, gender, teacher, and many other factors

even while employing disciplined, trust-inducing approaches” (Shulman, 1999, p. 163). One of

the reasons for my second sub-question for the research, which focused on racially and ethnically

diverse third and fourth grade readers, was because I could not ignore class, gender, ethnicity,

culture, and socioeconomic influences in my research on texts, just as I cannot ignore these

factors in district decision-making. Not only as a researcher but as a district leader, I am delving

into what I have squarely learned about so far in my research on the history of comprehension,

the construction-integration model of comprehension, that takes into account the interstices of

reader, text, and context/event/experience. I am bringing what I have learned through this

research study to conversations during curriculum review cycles and to professional

development planning for teachers and building and district leaders.

This research study cemented both my agreement with and my commitment to the work.

In other words, research must inform practice and it is the obligation of educators and education

leaders to conduct it, and/or read it, and finally use it both in the classroom and when making

systemic decisions. Researchers, administrators, and classroom teachers need to understand what

works for students - and not just what works, but what works well so that the achievement

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disparities that continue to persist can be eradicated. To do this, we can and must create systems

that provide time to read research and plan how to implement what we learned from it.

The use of informational text with third and fourth grade readers made clear the

continued need to increase the use of informational text with early and intermediate readers. The

use of informational texts to teach comprehension skills proved successful albeit the small

number of participants. However, the results of this study aligned with the review of the

literature, once again confirming what many educators and researchers know: Reading

instruction with well selected informational texts is necessary. There are young children, much

like my son when he was younger, who love informational text and would choose to read it over

narrative text. Both types of texts are needed for sound literacy instruction at all grade levels.

The texts matter.

One effective instructional method using informational texts is to include them for

explicit reading strategy and skill instruction. Paraphrasing is an extremely important

comprehension skill. Students were engaged in the paraphrasing video used in this study, and

there were promising data on their creation of paraphrases. While this study focused only on

paraphrasing, using informational text to teach a variety of comprehension strategies (such as

comprehension monitoring, inference, question-asking, elaboration and summarizing) is

necessary, as these skills and strategies are needed to fully comprehend informational and

expository text.

Another sound idea is to use informational texts for read-alouds, including modeling of

think-alouds while the teacher is reading. Using informational text for read-alouds takes some

planning, especially with regard to connection across content areas and teachers’ use of

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think-alouds while they are reading, but the benefits are invaluable. If teachers use informational

text to explicitly teach reading comprehension skills and strategies, they are helping students

gain access to the world of key ideas and details. They are providing opportunities for focused

learning on concepts students may never have known before. Finally, the teachers are helping all

students build vocabularies and an understanding of text structure that helps to ensure students’

ability to traverse complex text structure without having to work mightily to figure out the

meaning of multiple words in a sentence, a struggle I observed the students grapple with in my

research.

Yet another way we can improve the achievement of students in the classroom is to take

advantage of changing technology. I will begin by discussing the Coh-Metrix Text Ease and

Readability Assessor, which is an online tool that is free for educators to use. Before I conducted

this study, I had no idea this tool existed, even though I was a classroom teacher for 13 years and

a building and program coordinator for another three years. It is an easy tool to use: all teachers

need to do is create an account. Once that is done, they can then enter a short passage into the

tool, which will create a profile of the text. The profile includes percentile comparisons to other

texts, and a description of the component dimensions of the text itself. Introducing this tool to

teachers would require some professional learning on their part, but frankly not a lot, and this

would be a great tool for teachers when they are planning for small group reading instruction.

A second way of taking advantage of technology is thoughtful planning for reading

instruction and intervention with the technology at the forefront of the planning for instruction.

The district in which this study took place, and now my new district, transformed into 1:1

districts as a result of the COVID-19 pandemic, meaning that every student, K-12, in the district

262

has a device for learning. This fact alone can and should transform how technology is used in the

classroom for literacy instruction. However, students need to be taught how to use the

technology. I am having this conversation with my district as we plan for fall re-opening. The

district I am currently working in, as did the district in which this research took place, became a

1:1 district because of the COVID-19 pandemic. Having all students back in person provides a

necessary opportunity to think through how we are utilizing technology in the classroom.

Thoughtful planning on the part of the teacher or the grade level team could provide students

with greater and more relevant opportunities to build students’ background knowledge on topics

being read and learned in school, and provide opportunities for integration across content areas.

While conducting my research, I observed students using a search engine to find answers.

Teachers can leverage what students can do with technology, such as using a search engine, to

find, read, and evaluate online texts. Teachers can then plan ways to assess their students’

understanding of the texts they are reading online.

Using technology as a tool for formative and summative assessment of students’

comprehension can be very beneficial for both students and teachers. As students read the texts

in this study, they paraphrased sentences, which were captured in Qualtrics. This was real-time

assessment data that teachers would have at their fingertips. The same can be said about the

ratings that the students gave to both the texts and the paraphrase ease. Qualtrics is used as a

survey tool in both the district where this study took place and also in my current district. It can

provide a real-time dashboard for teachers to see where their students are at and where they are

struggling. As I mentioned earlier, technology can level the playing field for those students

historically underserved in our schools. However, districts must provide online professional

263

development for teachers, as this type of planning has not traditionally been taught in teacher

preparation programs, the tools are newer, and many teachers are not yet familiar with the

endless possibilities that technology can provide for their instruction and student learning.

Finally, it is important to create assessments that are authentic to what it is they are

assessing. In this study, the students struggled to read the science pre-assessment. The goal of

that assessment was to gauge their understanding of science concepts, not their reading ability.

Therefore, both I and their teachers helped them to read the words. If we rely solely on reading

for assessment, such as the use of multiple-choice tests, we miss an opportunity to understand

what our students know.

Concluding Thoughts

I began teaching in 1995, starting out in elementary school and moving to the secondary

level. This experience provided me with a broad range of understanding of what students

experience as they go through their educational journey. In addition to teaching English

Language Arts and literacy, I taught social studies and math to general education students, many

of whom struggled to comprehend texts. It was my responsibility as a teacher to assess what my

students knew, understood, and could do with the content in front of them. The barrier to

comprehension of that content made assessment of their learning much more difficult. While I

focused a considerable amount of my undergraduate learning on literacy, I was more determined

than ever as an educator to continue my journey on helping students to read successfully. My

masters thesis focused on literacy, and this doctoral journey continues that focus, especially as

technology continues to morph at warp speed.

264

This research study cemented in my mind the importance of strong reading

comprehension instruction, beginning in the early years. From the review of the literature, my

observations of struggling readers, and the quantitative research I amassed during this study, I am

fully convinced that as educators our work must not only continue, but we must understand that

the early years in education are crucial to success later on in a student’s academic career.

Instruction in phonics and phonemic awareness, while foundational to reading success, must not

take the place of opportunities to build background knowledge, provide exposure to a wide body

of vocabulary, and create endless opportunities to show young students how they already

comprehend so much. We must build on the funds of knowledge, understanding, and the many

assets that students bring with them everyday to our schools and classrooms.

We must use every minute we have with our students efficiently. In order to help them

make connections in their learning, we must integrate literacy into science, social studies, and

math, and bring knowledge of the world into literacy learning, which means an increase in the

use of informational text in literacy instruction. Furthermore, we must bring students’ knowledge

of their experiences, and their funds of knowledge, into literacy instruction, and connect their

understanding of the world with new knowledge that they are amassing. We must carefully and

intentionally plan learning experiences for students that continue to build their knowledge and

understanding, that help them see themselves as capable and contributing. To do this, we must

intentionally choose materials that not only engage our students but continue to build their

knowledge of the world. The texts matter.

In order to provide opportunities for readers to work on areas of difficulty, we need to

continue to leverage the advantages of technology, and we can do this by teaching literacy skills

265

through printed and digital literacies. We can implement interventions using online, web-based

platforms to take advantage of automated speech recognition, instantaneous definitions of words,

and the ability to listen to the text while reading - all that can be done by an independent learner

while the teacher is working with other students. Utilizing technology in this way can continue to

build what the data in this study showed as important: background knowledge, strong

vocabularies, and strong skill in reading on a computer screen.

When former President Barack Obama spoke to members of the American Library

Association, he remarked, “Reading is the gateway skill that makes all other learning possible”

(Obama, 2005). His words were focused on the change in skills needed for a successful

American workforce in the 21st century - a shift predicated on the revolution of technology and

the global connection requiring strong literacy and communication skills. He called this economy

“the knowledge economy” (Obama, 2005, para.15), and at its center is the ability to read well.

His words, spoken in front of librarians, have been my mantra ever since becoming a teacher.

I believe wholeheartedly that all students can and want to learn, and I am confident that

this research will impact reading instruction in my district. I have been hired to guide the

trajectory of students and, although I am no longer in the classroom, I am responsible for

creating systems that will ensure all students are prepared for a successful life after they

graduate. I feel a personal call to action after having conducted this research that compels me to

continue on my literacy journey.

The third and fourth grade students with whom I interacted in the summer of 2020 will

graduate in 2028 and 2029. I will continue to carry their experiences and their faces with me as I

research and learn, and as I lead. My journey, really, has only just begun. I contemplate Dewey’s

266

words that began this final chapter. As a result of this dissertation journey, I am more equipped

and feel more confident than ever before to create a brighter future, a different tomorrow, for all

of my students, no matter where the journey takes me.

267

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312

APPENDIX A

Teacher Focus Group Demographic Survey Responses

Yrs in

Education

Yrs in

District

Yrs in

Current

Role

School

Grades

Taught

Age

group

Gender

Race/

Ethn.

Native

Language

Degree

Area of

licensure

Other areas in

which you are

licensed

1-3

R-

STEM

K-5

specialist/

coach

51-65

Female

White

English

Ed.

Specialist

or 6th

year

Elementary

Education

Middle School

Math

1-3

RDLS

K-5

specialist/

coach

21-30

Female

White

English

Masters

Degree

Elementary

Education

1-3

RDLS

Grade 3

41-50

Female

White

English

Ed.

Specialist

or 6th

year

K-12 ESL,

Other

K-12 Spanish,

K-12 Principal

4-10

K-5

specialist/

coach

31-40

Female

White

English

Masters

Degree

Elementary

Education,

K-12

Reading

4-10

Grade 4

31-40

Female

White

English

Masters

Degree

Elementary

Education,

K-12

Reading

specialist

15+

RDLS

Grade 4

51-65

Male

Two or

Races

Spanish

Doctorate

Elementary

Education,

Other

Elementary

Principal -

Administrative

License, K-9

Spanish

4-10

K-5

specialist/

coach

51-65

Female

White

English

Masters

Degree

Elementary

Education

4-10

R-

STEM

K-5

specialist/

coach

51-65

Female

White

English

Masters

Degree

Elementary

Education

N/A

313

APPENDIX B

Indices Relevant to Reading Comprehension

Lexical Sophistication

Psycholinguistic properties

Features related to word concreteness, familiarity, imagability, age of

acquisition, meaningfulness, hypernymy, polysemy, word neighborhood

effects, and word recognition norms

Academic Terms

Words and phrases common in academic discourse

Association Measures

Number of strong associations averaged across words

Syntactic Complexity

Clausal and Phrasal Complexity

Average number of words, structures, and dependents per clause or t-unit

Syntactic Sophistication

Frequency, type token ratio, attested items, and association strengths for

verb-argument constructions

Syntactic Similarity

Similarity between sentences in terms of POS tags and syntactic parses

Text Cohesion

Givenness

Semantic similarity between given and new text

Lexical Repetition

Type-token ratio

Temporal Cohesion

Repetition of tense and aspect

Causal Cohesion

Use of causal verbs and particles

Local Cohesion

Connectives

Frequency of connectives and conjunctions in the text

Lexical Overlap (sentence)

Word overlap between sentences

Semantic Overlap (sentence)

Semantic overlap between sentences

Global Cohesion

314

Lexical Overlap (paragraph)

Word overlap between paragraphs

Synonym Overlap (paragraph)

Overlap of words and synonymy between paragraphs

Semantic Overlap (paragraph)

Semantic overlap between paragraphs

Indices Relevant to Reading Comprehension (Continued)

Readability

RDFRE

Flesch-Kincaid Reading Ease Score

RDFKGL

Flesch-Kincaid Grade Level

RDL2

Second Language Readability Score

Syntactic Pattern Density

Noun Phrases

Incidence of noun phrases

Verb Phrases

Incidence of verb phrases

Prepositional Phrases

Incidence of prepositional phrases

Rhetorical Features

Amplifiers

Incidence of amplifiers (e.g. “very”)

Private verbs

Incidence of private verbs (e.g. “think”)

Hedges

Incidence of hedges (e.g. “maybe,” “likely”)

Connectives

Causal

Incidence of causal connectives

Logic

Incidence of logic connectives

Temporal

Incidence of temporal connectives

315

APPENDIX C

Summer Targeted Services Text Data

Title

Word

Count

Paragraphs

Sentences

FK Grade

Text (In

Order

Presented)

Narrativity

(percentile)

Syntactic

Simplicity

(percentile)

Word

Concreteness

(percentile)

Referential

Cohesion

(percentile)

Deep

Cohesion

(percentile)

How a Star

is Born

275

2.7

Eating

Healthy

384

3.7

Mars

375

3.0

Wildfires

254

5.1

Blood

361

4.3

100

Ostriches

390

4.0

Starfish

398

4.8

Avalanches

300

5.5

Mean

351.71

6.29

32.29

4.34

5.0

53.43

80.14

70.71

65.29

54.43

54.01

4.39

6.73

0.86

2.16

10.63

13.32

21.18

22.57

28.64

316

APPENDIX D

Focus Group Initial Questions

1. How long have you worked in [the district]? (Follow up: How long have you taught 3rd

or fourth grade?)

2. How has reading comprehension instruction changed, if at all, in [the district where this

study took place] since you have been here?

3. What do you notice about the types of texts students in third and fourth grade like to

read? (Follow up: Is this true for groups of students or just some? Elaborate.)

4. In thinking about the texts that your students in third and fourth grade read, what do you

think are beneficial characteristics of texts to include for reading comprehension

instruction? (Follow up: Why?)

5. Think in terms of length, readability, cohesion (how the text “flows”), and subject matter.

What is important with regard to all of this when picking texts for students to read?

6. What do you think of your colleague’s answer just now? Anything you would like to

add?

7. What gaps do you think exist in the kinds of texts that your students are reading in

school? Think specifically about science texts.

317

APPENDIX E

Science Assessment (Modified from NAEP)

1. The surface of the Moon is covered with craters. Most of these craters were formed by

A. eruptions of active volcanoes

B. the impact of many meteoroids

C. shifting rock on the Moon’s surface (“moonquakes”)

D. tidal forces caused by the Earth and Sun

2. Which statement explains why light from the Sun can warm up water in a glass?

A. Light travels very fast.

B. Light travels in straight lines.

C. Water reflects light energy.

D. Water absorbs light and energy.

3. Which animal develops inside its mother before it is born alive?

A. Butterfly

B. Duck

C. Cat

D. Frog

4. When you are riding a bicycle at night, your bicycle’s reflectors help people in cars see

your bicycle. How do bicycle reflectors work?

A. They are made of a special material that gives off its own light.

B. They are hooked up to batteries that allow them to produce light.

318

C. They bounce light back from other sources.

D. They are covered with paint that glows in the dark.

5. A farmer thinks that the vegetables on her farm are not getting enough water. Her son

suggests that they use water from the nearby ocean to water the vegetables. Is this a good idea?

A. Yes, because there is plenty of ocean water.

B. Yes, because ocean water has many natural fertilizers.

C. No, because ocean water is too salty for plants grown on land.

D. No, because ocean water is much more polluted than rainwater.

6. Where does water in a lake get most of its energy to evaporate?

A. The sun heating the lake

B. Green plants living in the lake

C. Streams entering the lake

D. Cold springs under the lake

319

APPENDIX F

Student Observation Form Text Reading and Responding

Paraphrasing Observation Form

Date:

Number of students observed:

Start time:

End time:

Fidelity Check Instructions: Observe students as they work through one text. Complete the

checklist to the extent that the components were observed, and write detailed notes regarding

these or other components observed.

In preparation. Gather/complete the following information prior to the observation.

 List of students who you will be observing

 List of ID numbers for the students being observed

Observation Notes:

Student(s) are seated in an area that is not overly distracting (i.e., student is able to focus on the module

the majority of the time).

Very few minor to no distractions Some distractions Very distracting for the majority of

the time

Were the student(s) able to get started on the activity (begin loading a module) within a reasonable

amount of time (e.g., 2 minutes) of transitioning? Yes No

Anything else to note regarding the environment, tech issues, behavior of the children, or other things

noteworthy:

320

Instructions and Code.

Use momentary time sampling (look to the designated student at each interval and determine

whether or not they are displaying the desired behavior at that moment in time). Select a logical

order of students to observe and rotate through, looking at one student and then the next for each

time interval. Focus only on the designated student for that interval and record only on that

student’s behavior when your interval timer beeps. Write a *, 1, or a 0 in the column under the

text title section indicating the observed behavior. If the student had a glitch, place an “X” in this

column and simply skip over student during their interval. Observe their use of directions and

record in this column as well.

* Glitch (e.g., freezing, link did not work, etc.)

1 Engagement was observed

0 Engagement was not observed

Observation Order

Student ID

Text Title /Directions

Time

Student

Reading

Paraphrasing

Vocabulary

Other

0:10

0:20

0:30

0:40

0:50

1:00

1:10

321

1:20

1:30

1:40

1:50

2:00

2:10

2:20

2:30

2:40

2:50

3:00

3:10

3:20

3:30

3:40

3:50

4:00

4:10

4:20

4:30

4:40

4:50

5:00

5:10

5:20

5:30

322

5:40

5:50

6:00

6:10

6:20

6:30

6:40

6:50

7:00

7:10

7:20

7:30

7:40

8:00

8:10

8:20

8:30

8:40

8:50

9:00

9:10

9:20

9:30

9:40

9:50

323

10:00

10:10

10:20

10:30

10:40

10:50

11:00

11:10

11:20

11:30

11:40

11:50

12:00

12:10

12:20

12:30

12:40

12:50

13:00

13:10

13:20

13:30

13:40

13:50

14:00

14:10

324

14:20

14:30

14:40

14:50

15:00

15:10

15:20

15:30

15:40

15:50

16:00

16:10

16:20

16:30

16:40

16:50

17:00

17:10

17:20

17:30

17:40

17:50

18:00

18:10

18:20

18:30

325

18:40

18:50

19:00

19:10

19:20

19:30

19:40

19:50

20:00

Subtotals: column

observations/possible

= %

Overall Total: total observations possible

/ = %

326

APPENDIX G

Coding Table for Student Paraphrase Responses

FILTER: Too

short

0 = the response is more than

one word long

1 = the response is only one word

DO NOT CONTINUE SCORING

FILTER:

Copy/Paste

0 = the response is not a

copy/paste of the target

sentence (minor

morphological changes do not

count, i.e. “don’t” to “do not”

or “big” to “bigger”)

1 = the response is a copy/paste or retyping

of the sentence without anything added

(e.g., only one word is different but it is a

stem or slight morphological change); if

some minor words are cut out and no new

words are added, it is counted as a

copy/paste; it does not have to be the entire

TS copied, but counts if the entire response

was directly copied from the TS; ask

yourself: would I want to give the

respondent feedback of “please try again

and please change some more words”

DO NOT CONTINUE SCORING

FILTER:

Clause

Reversal (copy

and paste)

0 = no clause reversal

1 = Copy and paste of the target sentence,

just reversed clauses

DO NOT CONTINUE SCORING

FILTER

Garbage

0 =the response makes sense

and uses words, the response

is meaningful and makes

sense

1= the response is garbage, difficult to

derive meaning from response

DO NOT CONTINUE SCORING

FILTER:

Irrelevant

0 = the response is at least

partially relevant to the text

1= the response is irrelevant information to

the text

DO NOT CONTINUE SCORING