Walden University

COLLEGE OF EDUCATION

This is to certify that the doctoral study by

Kathy Jones

has been found to be complete and satisfactory in all respects, and that any and all revisions required by the review committee have been made.

Review Committee Dr. Thomas Schnick, Committee Chairperson, Education Faculty

Dr. Barbara Bailey, Committee Member, Education Faculty Dr. Brett Welch, University Reviewer, Education Faculty

Chief Academic Officer

David Clinefelter, Ph.D.

Walden University 2010

Abstract

The Relationship Between Oral Reading Fluency and Reading Proficiency

by

Kathy S. Jones

MA, Abilene Christian University, 2001

BS, Abilene Christian University, 1997

Dissertation Submitted in Partial Fulfillment

of the Requirements for the Degree of

Doctor of Education

Administration

Walden University

August 2010

Abstract

Students who struggle with reading in Grade 3 often fall behind their peers in reading

proficiency. Failure to meet minimum reading proficiencies of state-mandated tests can

negatively affect children’s success in subsequent grades. Educators have used oral

reading fluency tests as reliable indicators of students’ later reading proficiency. Studies

in 7 states found that oral reading fluency predicted performance on state reading

assessments. One aspect of the automaticity theory was used to explain why struggling

readers have insufficient attention to devote to reading proficiently. This

nonexperimental, quantitative study investigated whether a statistically significant

relationship existed between Grade 3 students’ oral reading fluency rates and their

reading proficiency when assessed by the state-mandated assessment. Pearson correlation

was used to compare the middle-of-year oral reading fluency rates, measured by the

Dynamics Indicators of Basic Literacy Skills oral reading fluency, and reading

proficiency, measured by the scale score Grade 3 Reading Texas Assessment of

Knowledge and Skills, of 155 Grade 3 students for the 2008-2009 school year in a school

district. The results indicated a relationship between oral reading fluency and reading

proficiency. Study results may help elementary school administrators, teachers, and

reading specialists to identify at-risk readers and implement interventions to enable

students to gain greater reading proficiency and improve their performance on state-

mandated assessments.

The Relationship Between Oral Reading Fluency and Reading Proficiency

by

Kathy S. Jones

MA, Abilene Christian University, 2001

BS, Abilene Christian University, 1997

Dissertation Submitted in Partial Fulfillment

of the Requirements for the Degree of

Doctor of Education

Administration

Walden University

August 2010

UMI Number: 3423184

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Dedication

This dissertation is dedicated to God. Throughout my life, He has prepared me for

what was coming next. At times, He prepared me for something before I even dared to

dream about it. My doctoral journey has been no exception. God first planted the dream

in me of pursuing a doctorate 15 years ago. I did not even have a bachelor’s degree at the

time, and the dream seemed impossible. Every time it was in danger of fading, God

would use someone to nudge me forward and place me back on track.

He has been with me through all the twists and turns of these past 5 years that I

have been enrolled in the doctoral program. He has molded me and made me into the

person I have become. I dedicate this honor to Him and trust that He will guide me as He

continues to use me to serve others with the talents with which He has blessed me.

Acknowledgments

God has used many people to encourage and inspire me on this doctoral journey. I

am thankful for the support of my family. My husband, Roy, has stood by my side

through all the ups and downs. He celebrated with me as I conquered hurdles and

encouraged me when I was discouraged. My adult children, Rachel, Benjamin, Timothy,

and Daniel, have showered me with comments, and I have especially been bolstered and

encouraged with their cries of “Way to go, Mom!” My parents, Bill and Anita Love,

planted the vision of setting goals and working hard to achieve them. My father has gone

on, but I treasure the memory of the crack in his voice as he proudly told others I was

working on my doctorate.

People in the field of academia have guided me on my journey as well. I

appreciate the support of my chair, Dr. Thomas L. Schnick. He has promptly reviewed

my work each time it was submitted and provided me with constructive criticism that

improved the quality of my dissertation. Dr. Barbara Bailey served as my methodologist.

I thank her for helping me see how the problem, purpose, and research questions

provided the foundation for the dissertation.

I am especially appreciative of my editor, Dr. Noelle Sterne, who coached me

from where I was to where I needed to be. She had a clear vision of what my dissertation

had to be and how to get me there. In addition to editorial changes, she encouraged me to

clearly describe my thoughts, to tell her more about what I was writing, and to find

additional sources to support my statements. This coaching was invaluable in my desire

to deepen and expand the substance of this dissertation.

I am grateful too for the bonds I have forged with fellow students. Because

Walden is an online university, I have not had the pleasure of meeting many of my peers.

Nonetheless, I was amazed at how deeply the bond of friendship developed. I especially

appreciate the friendship of Susan Myers. We met in our first online classes, roomed

together at two residencies, exchanged many emails, and talked on the phone. I am

confident that our professional relationship will continue even beyond graduation.

I appreciate and thank Keith Richardson, the superintendent of the district

involved in this study, for his cooperation. He supported me in signing the data use

agreement and letter of cooperation so that I could use the district archival data for the

study. I appreciate also the continued support and encouragement of Doug Doege, the

principal of the school for the study. He began working with me when the logistics of the

study were still a dream to me. As the details developed, he helped make them a reality. I

am also grateful for the cooperation of the Grade 3 teachers and students.

Finally, I give special thanks to Dynamics Measurement Group for giving me

permission to use the DIBELS ORF benchmark in the study and to the Texas Education

Agency for granting copyright permission for the use of the Grade 3 Reading TAKS in

the study.

i

Table of Contents

List of Tables .......................................................................................................................v

Section 1: Introduction to the Study ....................................................................................1

Problem Statement .........................................................................................................3

Nature of the Study ........................................................................................................4

Research Question and Hypothesis ................................................................................6

Purpose of the Study ......................................................................................................6

Theoretical Framework ..................................................................................................7

Operational Definitions ..................................................................................................8

Assumptions, Limitations, Scope, and Delimitations ..................................................10

Significance of the Study .............................................................................................11

Transition Statement ....................................................................................................13

Section 2: Literature Review .............................................................................................16

Introduction ..................................................................................................................16

Automaticity Theory ....................................................................................................16

Oral Reading Fluency ..................................................................................................21

Definition of Oral Reading Fluency ..................................................................... 22

The Role of Oral Reading Fluency in the Context of Learning to Read .............. 26

Fluency Instruction ............................................................................................... 29

Reading Proficiency .....................................................................................................30

Reading Proficiency and Automaticity Theory .................................................... 30

ii

Definition of Reading Proficiency ........................................................................ 34

Vocabulary and Matthew Effects .......................................................................... 36

Comprehension ..................................................................................................... 38

Relationship Between Oral Reading Fluency and Reading Proficiency in

State-Mandated Assessments ...........................................................................43

Studies of Grade 3 Only ........................................................................................ 44

Studies of Reading First Schools .......................................................................... 44

Studies of Grade 3 and Other Grades ................................................................... 45

Limitations of State Studies .................................................................................. 47

Summary ......................................................................................................................49

Section 3: Research Design ...............................................................................................52

Introduction ..................................................................................................................52

Research Design...........................................................................................................52

Setting and Sample ......................................................................................................55

Setting ................................................................................................................... 55

Characteristics of the Sample................................................................................ 55

Sampling Method .................................................................................................. 57

Sample Size ........................................................................................................... 57

Eligibility Criteria for Study Participants ............................................................. 58

Instrumentation and Materials .....................................................................................58

DIBELS ORF ........................................................................................................ 59

TAKS ................................................................................................................... 67

iii

Data Collection and Analysis.......................................................................................71

Data Collection ............................................................................................................71

Data Analysis ...............................................................................................................73

Researcher’s Role ........................................................................................................74

Protection of Participants’ Rights ................................................................................74

Summary ......................................................................................................................75

Section 4: Results of the Study .........................................................................................77

Introduction ..................................................................................................................77

Research Question and Hypothesis ..............................................................................77

Research Tools .............................................................................................................78

Data Analysis ...............................................................................................................80

Summary ......................................................................................................................87

Section 5: Discussion, Conclusions, and Recommendations .............................................89

Overview ......................................................................................................................89

Interpretation of Findings ............................................................................................89

Recommendations for Action ....................................................................................100

Recommendations for Further Study .........................................................................105

Quantitative Studies ............................................................................................ 105

Qualitative Studies .............................................................................................. 108

Mixed-Method Studies........................................................................................ 109

Conclusion .................................................................................................................112

References ........................................................................................................................116

iv

Appendix A: Permission to Collect Data .........................................................................133

Appendix B: Data Use Agreement ..................................................................................135

Appendix C: Permission to Use DIBELS ........................................................................139

Appendix D: Permission to Use TAKS ...........................................................................141

Curriculum Vitae .............................................................................................................151

v

List of Tables

Table 1. Characteristics of Grade 3 Students in Texas Overall and the Research Site .......................................................................................................................56 Table 2. Correlation of DIBELS ORF Rates and TAKS Scores for Grade 3 Students .....80 Table 3. Ranges and Categorization Cut Points of DIBELS ORF and Grade 3 TAKS ....82 Table 4. Comparison of Students’ Performance by Categories for DIBELS ORF and Grade 3 Reading TAKS .......................................................................................84 Table 5. Studies Correlating State-Mandated Assessments to the DIBELS ORF .............90

1

Section 1: Introduction to the Study

It is important for students to learn to read proficiently by the end of Grade 3.

From kindergarten through Grade 2, students focus on learning to read (Ehri, 2005). The

process of learning to read is a complex but systematic one. Many children learn to

recognize letters and words even before beginning formal school (Ehri, 2005). By the

end of Grade 3, students are expected not only to decode the words in a text, but also to

understand what they read (National Institute of Child, Health and Human Development

[NICHHD], 2000). Students who struggle with reading at the end of Grade 3 often

continue to fall farther behind their peers in terms of reading proficiency (Morgan,

Farkas, & Hibel, 2008). The failure to meet minimum reading proficiencies at the end of

Grade 3 can have negative consequences on children’s success in subsequent grades

(Jimerson, Anderson, & Whipple, 2002; Katsiyannis, Zhang, Ryan, & Jones, 2007).

After Grade 3, students transition from learning to read to reading to learn in other

subject areas (Musti-Rao, Hawkins, & Barkley, 2009). As a part of implementing the No

Child Left Behind legislation (NCLB, 2002), the federal government commissioned the

National Accessible Reading Assessment Project (NARAP, 2006) to define reading

proficiency. Their definition described reading as a process in which readers decode

words in order to make meaning. Readers understand text by using a variety of reading

strategies to determine the purpose of a passage and understand the context and nature of

the text. Once the NARAP established its working definition of reading proficiency,

states used this definition to write and assess curriculum objectives for reading. In section

2

2, I review literature that discussed reading in the context of students’ learning to read

and reading proficiency.

In compliance with NCLB (2002), federal legislators mandated that school

districts monitor students’ progress by identifying academic needs early in school, and

providing scientifically-based interventions. As NCLB requires, states have designed

curriculum standards and annual assessments to measure the number of students who

read proficiently. For example, Texas has used performance on high-stakes tests in

Grade 3 to determine promotion or retention of students (Texas Education Agency

[TEA], 2008). Given the legal mandates and the commitment of NCLB to leave no child

behind academically, it is important that local school districts identify nonproficient and

struggling readers before they fail in reading and later grades (Jenkins, Hudson, &

Johnson, 2007).

To ascertain students’ reading proficiency in the early grades, researchers have

established that oral reading fluency is a reliable predictor of reading proficiency (Fuchs,

Fuchs, Hosp, & Jenkins, 2001; Simmons et al., 2008). Section 2 contains additional

reports of researchers who found that oral reading fluency was a predictor of

performance on seven state-mandated reading assessments (Baker et al., 2008; Barger,

2003; Roehrig, Petscher, Nettles, Hudson, & Torgesen, 2008; Shapiro, Solari, &

Petscher, 2008; Vander Meer, Lentz, & Stollar, 2005; Wilson, 2005; Wood, 2006).

Section 2 also contains reviews of literature in which reading experts disagree on the

definition of fluency (Kame’enui & Simmons, 2001; Samuels, 2007). States define

reading proficiency by using curriculum standards rather than the verbal definitions of

3

NARAP (2006), and the curriculum standards may differ from state to state (Colorado

Department of Education, 2009; Florida Department of Education, 2005; TEA, 2004).

Researchers have established positive correlations between oral reading fluency

rates and reading proficiency (Hosp & Fuchs, 2005; Simmons et al., 2008). Additional

research is needed to confirm the specific relationship between oral reading fluency

assessments and other state-mandated tests for reading proficiency (Roehrig et al.,

2008). The purpose of this research project was to determine if a relationship existed

between oral reading fluency of Grade 3 students in a West Texas school district and

their performance on the state-mandated assessment in Texas in the 2008-2009 school

year.

Problem Statement

In Texas, the site of the current research, in 2009, 33,462 students, approximately

15% of all Grade 3 students, were unable to read proficiently enough to pass the Grade 3

Reading Texas Assessment of Knowledge and Skills (TEA, 2009c). According to the

Nation’s Report Card in Reading (U. S. Department of Education, 2007), 67% of the

fourth-grade students who took the National Assessment of Educational Progress (NAEP)

in 2007 scored at the basic level or above. However, 33% of the tested students did not

read well enough to score at the basic level. The majority of students learn to read

proficiently (Chard et al., 2008; Ehri, 2005). Nevertheless, many students do not reach an

acceptable level of reading by Grade 3 and are considered struggling readers (Applegate,

Applegate, McGeehan, Pinto, & Kong, 2009; Pressley, Gaskins, & Fingeret, 2006;

Torgesen & Hudson, 2006).

4

Educators have used oral reading fluency as a reliable indicator of students’

progress toward overall reading proficiency (Jenkins et al., 2007). The following

researchers have found significant correlations between oral reading fluency rates and

reading proficiency in seven states’ mandated reading assessments: Arizona (Wilson,

2005), Colorado (Shaw & Shaw, 2002; Wood, 2006), Florida (Buck & Torgesen, 2003;

Roehrig et al., 2008), North Carolina (Barger, 2003), Ohio (Vander Meer et al., 2005),

Oregon (Baker et al., 2008), and Pennsylvania (Shapiro et al., 2008). However, it is

unknown whether a similar connection exists in the Texas school system (Roehrig et al.).

An investigation of this possible relationship is important for providing evidence to aid

elementary school administrators, teachers, and reading specialists to identify at-risk

readers. Early identification of struggling readers in concurrence with research-driven

interventions can close the gap between these readers and their proficient peers before the

end of Grade 3 (Simmons et al., 2008).

Nature of the Study

To determine if a statistically significant (p < .05) relationship existed between

students’ oral reading fluency rates and their reading proficiency, this nonexperimental

quantitative study compared the middle-of-year oral reading fluency rates and reading

proficiency of 155 Grade 3 students for the 2008-2009 school year in a West Texas

school district. The students resided in a small West Texas town with a population of

6,821, and in which all Grade 3 students attended the same elementary school. The

demographics of the school district are similar to those of all Grade 3 students in Texas

5

(TEA, 2009c). To obtain as wide a range of scores as possible, all of the Grade 3 students

in this district comprised the nonprobability convenience sample.

The Dynamic Indicators of Basic Early Literacy Skills Oral Reading Fluency

(DIBELS ORF) comprised the independent variable to measure students’ oral reading

fluency rates. The developers of DIBELS ORF found the assessments reliable and valid

(Good & Kaminski, 2002a). Additionally, other researchers have found DIBELS ORF

rates reliable (Baker et al., 2008; Buck & Torgesen, 2003; Roehrig et al., 2008; Shaw &

Shaw, 2002; Vander Meer et al., 2005; Wilson, 2005, Wood, 2006). However, some

researchers disagreed with the definition of fluency used by the developers of DIBELS

(Hudson, Lane, & Pullen, 2005; Young & Rasinski, 2009) and the reliability and validity

of the assessment (Samuels, 2007). Section 2 contains a review of the literature on

DIBELS ORF, including the controversy.

The Grade 3 Reading Texas Assessment of Knowledge and Skills (TAKS) scale

scores (TEA, 2009b) comprised the dependent variable to measure students’ reading

proficiency. The TEA in conjunction with Pearson Education established the reliability

and validity of TAKS (TEA & Pearson, 2008). Staff members of these organizations

have worked regularly with teachers in Texas and national testing experts to ensure that

the TAKS is a quality assessment. Further information describing the reliability and

validity of TAKS is included in section 3.

To address the study problem, I used the middle-of-year 2008-2009 DIBELS ORF

benchmark rates of the Grade 3 sample from January 2009 and the scale score of the

2009 Grade 3 Reading TAKS. I applied the Statistical Package for the Social Sciences

6

(SPSS, 2009) software program, version 17.0, and conducted a Pearson correlation

analysis to determine if there was a statistically significant relationship (p < .05) between

oral reading fluency rates as measured by DIBELS ORF and reading proficiency as

measured by the scale score of the Grade 3 Reading TAKS.

Research Question and Hypothesis

The following research question guided this study: Is there a statistically

significant relationship between Grade 3 students’ oral reading fluency rates and their

reading proficiency? From this question, the following null and alternative hypotheses

were formulated:

H0: There is no statistically significant relationship between students’ oral reading

fluency rates, as measured by the students’ middle-of-year DIBELS ORF rates, and their

reading proficiency, as measured by their scale scores on the Grade 3 Reading TAKS for

the 2008-2009 school year.

H1: There is a statistically significant relationship between students’ oral reading

fluency rates, as measured by the students’ middle-of-year DIBELS ORF rates, and their

reading proficiency, as measured by their scale scores on the Grade 3 Reading TAKS for

the 2008-2009 school year.

Section 3 contains additional information regarding the research question,

hypotheses, methodology, and measurements.

Purpose of the Study

The purpose of this nonexperimental, quantitative study was to determine whether

a statistically significant relationship (p < .05) existed between Grade 3 students’ oral

7

reading fluency rates and their reading proficiency. With a nonprobability convenience

sample of 155 Grade 3 students in a West Texas school district, I sought to determine if a

statistically significant relationship existed between oral reading fluency rates and

students’ reading proficiency on the summative, high-stakes reading assessment results

for the 2008-2009 school year. The independent variable was oral reading fluency, and

the dependent variable was reading proficiency. The outcome of the study identified

additional ways in which elementary teachers can screen struggling readers so that

interventions can take place to help these students to increase their reading ability.

Theoretical Framework

The automaticity theory developed by LaBerge and Samuels (1974) and expanded

upon by Samuels (2006) formed the theoretical basis of this study. The automaticity

theory explains the relationship between fluency and comprehension. When initially

proposing the automaticity theory, LaBerge and Samuels found that accurately reading

words alone was not sufficient for reading proficiency. They posited that for students to

devote attention to other aspects of reading, they must first accurately and fluently read

words.

In 2006, Samuels identified four components of the reading process: decoding,

comprehension, metacognition, and attention; the last he viewed as limited. When

students spend too much time trying to sound out words, they cannot comprehend what

they have read by the end of a line or a page. Unless students are able to fluently decode

the words in a text, they do not have sufficient attention to devote to comprehend what is

read or to use metacognitive strategies to improve their comprehension. This theory

8

explains why slow readers who may accurately identify all or most of the words in a

passage may still not read proficiently enough to pass state-mandated reading

assessments.

Several researchers have tested the automaticity theory and found a relationship

between oral reading fluency and reading proficiency in general (Baker et al., 2008;

Daane, Campbell, Grigg, Goodman, & Oranje, 2005; Kuhn, 2005; Morgan & Sideridis,

2006; Riedel, 2007). However, scholars disagree on the definition of oral reading fluency.

Some define oral reading fluency as rate and accuracy alone (Kame’enui & Simmons,

2001; Riedel), and others include prosody and comprehension (Allington, 2009; Samuels,

2006). I will further discuss the automaticity theory, including controversies in the

literature, in section 2.

Operational Definitions

The following terms as defined were used throughout this study.

Automaticity theory: The four-component process by which proficient readers

decode words fluently, enabling them to focus attention on higher comprehension skills

of the passages read (Samuels, 2006).

Dynamic Indicators of Basic Early Literacy Skills (DIBELS): Short, 1-minute

assessments that educators use to measure the development of early literacy skills. These

assessments include oral reading fluency, retell fluency, and nonsense word fluency

(Good & Kaminski, 2002b).

Matthew effects: The gap between readers and struggling readers. Matthew

effects are based on the Biblical concept found in Matthew 25:29, a verse which refers to

9

the rich becoming richer and the poor becoming poorer. In the context of reading, this

term indicates that students who read consistently increase their knowledge base and

vocabulary, and readers who read less will learn less and continue to be struggling

readers. The gap between proficient readers and struggling readers widens as they

progress through school (Morgan et al., 2008; Stanovich, 1998).

Oral reading fluency (ORF): The ability to read words accurately and quickly

(Fuchs et al., 2001; Roehrig et al., 2008) with proper expression (Eldredge, 2005; Hudson

et al., 2005) and comprehension (Marcell, 2007; Samuels, 2007). In the current study,

Grade 3 students’ DIBELS ORF rates were used as the independent variable (Good &

Kaminski, 2002b).

Proficiency level: A scale score of 2100 or more on the Grade 3 Reading TAKS

(TEA, 2009b). Out of the 36 questions, proficient readers answer at least 24 correctly to

demonstrate proficiency.

Reading proficiency: The ability of a reader to decode the words in a passage and

comprehend what it says. Proficient readers employ a variety of strategies to comprehend

a passage, such as determining the purpose for reading, using context clues and the nature

of the passage, and using background knowledge (Cline, Johnstone, & King, 2006).

Proficient readers demonstrate a basic understanding of reading, apply knowledge of

literary elements, use a variety of strategies to analyze a passage of text, and apply

critical-thinking skills to analyze a passage by scoring 2100 or more on the Grade 3

Reading TAKS (TEA, 2004). In the current study, I used students’ scale scores from the

Grade 3 Reading TAKS as the dependent variable to measure reading proficiency.

10

Scale score: In 2009, the TEA measured performance on the TAKS using a scale

score. A raw score of zero had a scale score of 1399, and a perfect raw score of 36 had a

scale score of 2630. Students who achieved a scale score of 2100 or above were

considered proficient; students who received a scale score of 2400 or above received

commended performance (TEA, 2009b).

Struggling readers: Struggling readers have at least average intelligence, but they

read more slowly than other readers their age and may be at risk for long-term reading

difficulties (Pressley et al., 2006).

Texas Assessment of Knowledge and Skills (TAKS): The TAKS is a state-

mandated, summative, high-stakes assessment in Texas that assesses specific

proficiencies in Grades 3 to 11 in accordance with the state curriculum (TEA, 2009a).

The TAKS is scored with a scale score, defined above. For this study, I used the scale

score of the Grade 3 Reading TAKS to measure the dependent variable of reading

proficiency (TEA, 2006, 2009e).

Assumptions, Limitations, Scope, and Delimitations

In this study, I made four assumptions. First, the DIBELS ORF was a reliable

measure of oral reading fluency. Second, the Grade 3 Reading TAKS was a reliable

measurement of reading proficiency. Third, the Grade 3 students’ DIBELS ORF rates and

Grade 3 Reading TAKS scale scores reported for the target West Texas school district

were accurate and reliable. Finally, the statistical method chosen for this study was

appropriate.

11

I acknowledged four limitations for this study. The first was the use of a

nonprobability convenience sample, and the second was the limitation of the study

population to students in Grade 3. Because of these factors, the results may not generalize

to students in other elementary grades. Third, the study took place in a single

geographical location, a small town in West Texas. Similarly, the results may not

generalize to other locations in Texas or other states. Finally, quantitative correlational

analysis does not prove the existence of relationships between variables. Rather, in

correlational studies, a statistical procedure may establish a relationship between two

variables, but neither the method nor results prove that one variable causes another

variable (Gravetter & Wallnau, 2005). Thus, study results do not prove the existence of a

relationship between oral reading fluency rates and reading proficiency or that low

fluency rates cause poor reading comprehension. Rather, results indicate whether a

statistically significant relationship exists between the two variables.

The scope focused on the oral reading fluency rates and reading proficiency of

Grade 3 students in a Western school district. I limited the study to 155 students in Grade

3 in a West Texas elementary school district. I investigated only the two variables of oral

reading fluency and reading proficiency for a single school year, 2008-2009. Each of the

variables was operationalized by a single state-mandated assessment, for oral reading

fluency the DIBELS ORF and for reading proficiency the Grade 3 Reading TAKS.

Significance of the Study

This study was significant in several ways. With regard to the literature, the study

filled a gap that existed regarding students’ oral reading fluency and reading proficiency.

12

Researchers in seven states (Baker et al., 2008; Barger, 2003; Roehrig et al., 2008;

Shapiro et al., 2008; Vander Meer et al., 2005; Wilson, 2005; Wood, 2006) used DIBELS

ORF rates to determine if there was a significant relationship between oral reading

fluency rates and reading proficiency as measured by their states’ mandated reading

assessment. Although each of these studies found that oral reading fluency rates

correlated with reading proficiency, additional studies were needed for other states since

the curriculum standards that define reading proficiency differ from state to state

(Roehrig et al.). This study filled a gap in the literature on the assessment of struggling

readers by determining if such a relationship exists with Grade 3 students in Texas.

In addition, with regard to professional application of the study, the results can

help teachers in Texas. NCLB (2002) mandates that school districts must make adequate

yearly progress in students’ reading scores. In situations where the school or district has

not met adequate yearly progress for 2 consecutive years, state education agencies are

required to impose corrective actions, such as removing the principal, replacing the staff,

receiving advice from outside experts, or requiring the implementation of an entirely new

curriculum.

The study results can help Texas educators identify struggling readers before the

administration of the Grade 3 Reading TAKS. Educators can then provide interventions

designed to improve basic reading skills, such as decoding, fluency, vocabulary, and

comprehension skills. Such interventions may help struggling readers’ possibilities of

scoring in the proficient range on the state-mandated assessment (Simmons et al., 2008).

13

In turn, the school districts may increase the likelihood of meeting adequate yearly

progress.

Study results may also contribute to positive social change. Elementary educators

may more easily identify struggling readers so that interventions can take place before

students take the Grade 3 Reading TAKS. Such interventions would target basic literacy

skills and include greater oral reading fluency and decoding strategies to improve

struggling readers’ reading proficiency (Jenkins et al., 2007). Diagnosis of struggling

readers and skills implementation help reduce the risk of students’ failing the state tests

and increase their possibilities of academic success (Ehri, 2005; Shapiro et al., 2008).

Struggling readers who are identified and remediated before the end of Grade 3

are more likely to improve their reading skills, thus helping to close the academic gap

with more proficient peers (Simmons et al., 2008). When struggling readers experience

success in reading, they are more likely to continue academic achievement through the

grades and graduate from high school (Houge, Peyton, Geier, & Petrie, 2007; Rumberger

& Palardy, 2005). Graduation from high school with proficient reading skills increases an

individual’s opportunities for employment and contribution to society (Katsiyannis et al.,

2007).

Transition Statement

It is important for students to learn to read proficiently by the end of Grade 3

(Ehri, 2005; NCLB, 2002). Nationwide, most students learn to read before the fourth

grade (U. S. Department of Education, 2007); however, between 15% (TEA, 2009c) and

33% (U.S. Department of Education, 2007) of students do not read proficiently.

14

Researchers in Arizona (Wilson, 2005), Colorado (Wood, 2006), Florida (Roehrig et al.,

2008), North Carolina (Barger, 2003), Ohio (Vander Meer et al., 2005), Oregon (Baker et

al., 2008), and Pennsylvania (Shapiro et al., 2008) have found that oral reading fluency

rates correlated with reading proficiency as assessed on their states’ mandated reading

assessment. The two variables have been studied only in these seven states.

This nonexperimental quantitative study, based on the automaticity theory

(LaBerge & Samuels, 1974) and using Pearson correlation, filled a gap in the literature to

determine with a sample of 155 Grade 3 students in Texas if a statistically significant

relationship (p < .05) existed between their oral reading fluency rates (middle-of-year

DIBELS ORF) and their reading proficiency (end-of-year TAKS). Study findings may

result in positive social change by providing Texas educators with a valuable tool for

identifying struggling readers in Grade 3 (Simmons et al., 2008). Once struggling readers

are identified, educators can provide scientifically-based reading interventions to

strengthen phonemic awareness, phonics, fluency, vocabulary, and comprehension skills

(Chard et al., 2008). The identification and assistance of struggling readers can help them

improve academically and increase their success later in life (Katsiyannis et al., 2007;

Shaw & Berg, 2009).

In section 2, I review pertinent literature on the automaticity theory, oral reading

fluency, reading proficiency, and related concepts. In section 3, I describe the study

methodology in greater detail. Aspects include the sample, instruments, protection of

participants’ rights, data collection, and data analysis. In section 4, I report the study

findings. In section 5, I analyze the findings and discuss data from the study in light of

15

the previous studies that compared DIBELS ORF rates with student performance on

state-mandated assessments. Additionally, I make recommendations in section 5

regarding future actions and ideas for future studies.

16

Section 2: Literature Review

Introduction

In this section I review literature pertinent to this study in terms of the theory and

studies relevant to the variables. The section is organized as follows: (a) automaticity

theory; (b) oral reading fluency, including definitions, the role of oral reading fluency in

learning to read, and fluency instruction; (c) reading proficiency, including reading

proficiency and automaticity theory, definitions of reading proficiency, vocabulary and

Matthew effects, and comprehension; and (d) the relationship between oral reading

fluency and reading proficiency in state-mandated assessments, including studies of

Grade 3 only, of Reading First schools, and of Grade 3 and other grades, as well as

limitations of these studies. The section is concluded with a summary.

To investigate the literature for this study, I searched electronic databases, such as

Academic Search Premier, EBSCO, Dissertations and Theses, and ERIC, using the

keywords oral reading fluency/ORF, phonemic awareness, phonics, reading

comprehension, reading proficiency, and vocabulary. I also used bibliographies of

articles to search for additional literature and reviewed peer-reviewed articles. In

addition, I read several recently published books on the subject of oral reading fluency.

Automaticity Theory

LaBerge and Samuels (1974) used the automaticity theory to explain the

relationship between fluency and reading proficiency. They acknowledged that reading is

a complex skill that takes years to develop. Fluent readers are able to process the

necessary information in less than a second. However, some readers never reach a level at

17

which they fluently read a text, even though they are able to adequately communicate

orally.

Reading is a complex skill with many subskills, in which readers must recognize

letters, spelling patterns, and words as well as attach meanings of words and context.

According to this theory, attention is a limited faculty, and when students are beginning

to learn to read, their attention is focused on factors other than meanings, such as shapes

of letters (LaBerge & Samuels, 1974). In prekindergarten and kindergarten, students must

initially focus on the shapes within a letter, the length of lines, and the direction letters

are facing. As beginning readers, students have great difficulty distinguishing the

difference between letters. In addition, at first, students focus their attention on

recognizing and naming letters and do not have enough attention to focus on the sounds.

In addition to letter naming, LaBerge and Samuels (1974) found that a certain

amount of attention devoted to other subskills is also necessary for development of fluent

reading. Once beginning readers automatically recognize letters, they must learn to

associate sounds with the letters. Then they can focus their attention on reading parts of

words and entire words.

To test their theory of automaticity, LaBerge and Samuels (1974) designed an

experiment with eight college students. They measured the time the students took to

identify patterns of familiar and unfamiliar letters. The students were able to accurately

identify patterns of familiar letters more quickly than those of unfamiliar letters. Next, the

students received training on the unfamiliar letters. At the end of a 20-day period, they

were able to recognize the unfamiliar letters more accurately although still not as fast as

18

the familiar letters. LaBerge and Samuels concluded that some degree of attention was

still needed for the students to make the association for unfamiliar letters.

From these results, LaBerge and Samuels (1974) expressed concerns regarding

their observations of teaching reading. They had found that teachers often directly teach

letter names until students are able to correctly identify the letters. Then teachers move to

direct instruction in other aspects of reading, such as letter sounds and blending.

However, students may still not be able to fluently identify letters. Because their attention

is focused on this task, they may not have adequate attention to devote to learning sounds

and how to blend them together to make words. Thus, LaBerge and Samuels

recommended that teachers continue teaching and testing letter naming until students

reach a level of automaticity. The researchers maintained that only when students can

automatically recognize letters can they focus a significant amount of attention on the

sounds the letters make.

In 1974, when LaBerge and Samuels first proposed the automaticity theory, they

focused on automaticity at the word level. Their study showed how readers who had not

reached a level of automatically decoding words would have trouble comprehending. At

that time, LaBerge and Samuels did not conceptualize that automaticity in other areas

was also important.

However, as researchers continued to develop the automaticity theory, they

recognized that metacognition also played an important role in comprehension and that

aspects of metacognition could be automaticized (Samuels, Ediger, Willcutt, & Palumbo,

2005). Metacognition is the readers’ awareness of what is being read and whether or not

19

comprehension is taking place. Readers who use metacognition are thinking about

whether or not they are thinking about what the passage says. Factors such as readers’

motivation to read, their attitudes and beliefs about their reading ability, their interest in

the topic, and the amount of attention they devote to reading can affect how much they

comprehend. Whether or not readers are distracted by other factors, such as the

environment, noises, or other thoughts, can affect comprehension.

Metacognition also involves the insight readers bring to a text derived from

background knowledge. When readers read something with which they are highly

familiar, gaining new insights and adding to their cognitive repertoire of knowledge

seems easy (Samuels et al., 2005). However, when readers know very little about the

topic, they may have to work harder to comprehend the passage. Good readers learn to

recognize when cognitive aspects interfere with their ability to comprehend and to make

adjustments. Samuels et al. recommended that teachers instruct readers to be aware of

such factors by modeling thinking strategies and measuring students’ use through rubrics

until they automatically use metacognition strategies when reading.

According to automaticity theory, students who have low fluency rates struggle

with reading proficiency (Goffreda, Diperna, & Pedersen, 2009). In order to read

proficiently, students must be able to recognize words in context and use a variety of

strategies to comprehend a passage. Samuels (2006) summarized the automaticity theory

by identifying four components as elements of the relationship between oral reading

fluency and reading proficiency: decoding, comprehension, metacognition, and attention.

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First, a reader must decode the words in a text (LaBerge & Samuels, 1974).

Beginning or struggling readers may devote so much attention to decoding words that

comprehension is difficult, if not impossible (Samuels, 2006). However, proficient

readers are able to decode words and quickly attach meaning to them (Shaywitz, 2003).

Skilled readers can read a word and, within 150 milliseconds, less than the time it takes

for the heart to beat once, the brain has attached meaning to the word. However,

beginning and struggling readers process reading differently. Whereas skilled readers see

whole words, beginning and struggling readers, such as dyslexics, may only see a few

letters or sounds at a time (Samuels, 2006).

In 1974, LaBerge and Samuels could only presume that oral reading fluency

would affect comprehension. By 2006, Samuels had identified comprehension as another

component of the reading process. Fluent readers spend less attention on decoding words

and therefore can devote more attention to comprehending. Proficient readers combine

the information in a text with their background knowledge and critically analyze the text.

Samuels believed that readers must automatically decode before they can devote

sufficient attention to comprehension.

Samuel’s (2006) next component of the reading process is metacognition or one’s

own awareness of the thought processes. Proficient readers use metacognition when they

do not understand a text and make adaptations so they can comprehend it. Walczyk and

Griffith-Ross (2007) found that readers can comprehend by using metacognition to know

when they do not comprehend and adapt by using reading strategies such as slowing

down, reading out loud, rereading, or sounding out difficult words. Some readers use

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metacognition to improve their use of reading strategies until the strategies become

automatic. For example, readers can learn the skill of making inferences and use this skill

repeatedly until they automatically infer meaning while reading a passage. Proficient

readers use metacognition as they read and analyze text (Samuels, 2006).

Samuels’ (2006) final component of the reading process is attention. This is an

outcome of the previous three components, decoding, comprehension, and metacognition.

Beginning readers use excessive attention to decode words and have insufficient attention

remaining for comprehending or thinking about reading strategies they could use. As

readers become more proficient, they decode words automatically and devote more

attention to comprehension and metacognition. According to the automaticity theory,

readers are not proficient until they can apply their attention to decode, comprehend, and

use metacognition at the same time (Samuels, 2006).

Oral Reading Fluency

Originally LaBerge and Samuels (1974) used the automaticity theory to explain

why low reading fluency rates affect reading proficiency. The degree of expression can

indicate students’ understanding of the passage (Samuels, 2006). Most researchers

studying oral reading fluency and reading proficiency agree that oral reading fluency and

reading proficiency are related (Daane et al., 2005; Deeney, 2010; Miller &

Schwanenflugel, 2006). Researchers disagree, however, on how fluency is defined and

the validity of assessments used to assess it. To measure oral reading fluency, researchers

have developed assessments such as AIMSweb (Edformation, 2004), the DIBELS (Good

& Kaminiski, 2002a), the Reading Fluency Monitor (Read Naturally, 2002), and the

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Texas Primary Reading Inventory (University of Houston, 1999). In particular, Reading

First schools have widely used the DIBELS with more than 1,800,000 children

(Allington, 2009; Baker et al., 2008; Glenn, 2007; Manzo, 2005).

Some researchers have claimed that political reasons may have motivated the

widespread use of the DIBELS (Allington, 2009; Goodman, 2006; Manzo, 2005;

Pearson, 2006; Pressley, Hilden, & Shankland, 2005; Riedel, 2007). One of the

developers of DIBELS, Good from the University of Oregon, served on national

committees that developed Reading First. Critics (e.g., Glenn, 2007) have alleged that

Good personally benefitted when applications for Reading First grants were denied and

schools felt pressured by federal officials and consultants to include DIBELS in their

grant applications (Manzo, 2005). However, despite such claims, researchers recognize

DIBELS as a respected way of measuring oral reading fluency (Baker et al., 2008; Riedel

et al., 2007).

Definition of Oral Reading Fluency

Many researchers have focused on the definition of fluency used by the

developers of the DIBELS, although definitions vary (Hudson et al., 2005; Samuels,

2006). A fluent reader can read text with speed, accuracy, and proper expression

(NICHHD, 2000). Worthy and Broaddus (2002) defined fluency as “not only rate,

accuracy, and automaticity, but also of phrasing, smoothness, and expressiveness” (p.

334). Effective readers do more than just read the words; they understand what they read

(Marcell, 2007). Hudson et al. included accuracy, rate, and prosody in their definition of

fluency. Samuels (2007) and others (Allington, 2009; Miller & Schwanenflugel, 2008;

23

Rasinski, 2006) contended that educators should consider prosody or the expression with

which students read a passage. Fuchs et al. (2001) found that prosody was difficult to

measure, so they chose to focus on rate and accuracy. The developers of the DIBELS

defined fluency as rate and accuracy (Good & Kaminski, 2002a).

Various researchers have asserted that the definition of fluency should include

comprehension (Kuhn, 2005; Marcell, 2007; Pikulski & Chard, 2005; Samuels, 2007).

Pikulski and Chard (2005) defined fluency as follows:

Reading fluency refers to efficient, effective word-recognition skills that permit a

reader to construct the meaning of text. Fluency is manifested in accurate, rapid,

expressive oral reading and is applied during, and makes possible, silent reading

comprehension. (p. 510)

Samuels (2006) not only agreed that the definition of fluency should include

comprehension but also stated that measures of fluency should assess reading and

comprehension at the same time. Samuels noted that beginning readers focus first on

decoding, and once they are able to decode automatically, they focus on comprehension.

Samuels emphasized that the automaticity theory, which he and LaBerge developed

(LaBerge & Samuels, 1974), requires students to decode words automatically so that they

can comprehend. He pointed out educators who assess fluency first and then assess

comprehension later or with a different assessment miss the point of automaticity.

Deeney (2010) included endurance in her definition of fluency. She agreed that

the definition of fluency consists of four components; accuracy, rate or speed, prosody,

and comprehension. However, in her work with students she saw the need to consider

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endurance. In her opinion, 1-minute fluency probes provide useful information for

identifying which students are struggling. However, Deeney pointed out that these

problems did not provide adequate information for determining why students struggle

and what can be done to address their academic needs. She agreed with Pikulski and

Chard (2005), who called for a deeper view of fluency. Deeney believed that such a

deeper view includes rate, accuracy, prosody, comprehension, and endurance.

The developers of DIBELS (Kame’enui & Simmons, 2001) and others (Francis et

al., 2005; Harn, Stoolmiller, & Chard, 2008; Hasbrouck & Tindal, 2006; Jenkins et al.,

2007; Katzir et al., 2006) agreed with the definition of Roehrig et al. (2008) of oral

reading fluency as “accuracy and rate in connected text, or correct words per minute” (p.

345). Reading is a complex skill (Fuchs et al., 2001) that includes various components.

Kame’enui and Simmons discussed the simplicity and complexity of oral reading

fluency. They cited Watson (1968), the discoverer of DNA, who stated, “The idea is so

simple it had to be true” (as cited in Kame-enui & Simmons, p. 203). Like DNA, fluency

is a complex skill with many components, including phonemic awareness, alphabetic

principle, word reading, expression, and comprehension.

Fluency is also easily recognized. For example, a person listening to struggling

readers decoding words sound by sound can easily recognize they are not reading

fluently. Kame’enui and Simmons (2001) emphasized that even though educators have

debated the exact definition of oral reading fluency for decades, definition is not the

major point. Rather, as LaBerge and Samuels (1974) recognized when they developed the

automaticity theory, reading proficiency is a complex skill with many different aspects.

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Although LaBerge and Samuels focused only on rate and accuracy and the subskills of

letter and word recognition in 1974, they recognized that other aspects are involved.

When educators use only rate and accuracy to define fluency, they are measuring only the

subskill of fluency. Different assessments can be used to measure other subskills of

reading proficiency.

Skills such as phonemic awareness, phonics, and word reading are necessary

components of fluency that enable students to read passages expressively and with

understanding. However, by defining fluency as accuracy and rate, researchers gain a

measureable, workable definition to analyze the progress of beginning readers toward the

goal of adequately comprehending what they read. The National Reading Panel

(NICHHD, 2000) identified fluency as one of the main components of early reading

instruction. Hasbrouck and Tindal (2006) analyzed thousands of students’ oral reading

fluency rates in order to develop norms for Grades 1 through 8. Educators can listen to a

student read for as little as 1 minute and compare the fluency rate with thousands of other

students at the same grade level at the beginning, middle, or end of the school year. At

the conclusion of their research, Hasbrouck and Tindal recognized the complexity of

reading and recommended that educators consider fluency in the context of the other

components necessary for mastery.

In the present study, I defined oral reading fluency as the accuracy and rate at

which students read a grade level text (Francis et al., 2008; Harn et al., 2008; Hasbrouck

& Tindal, 2006; Jenkins et al., 2007; Katzir et al., 2006). This definition provided a

specific way to measure oral reading fluency so that I could determine if a relationship

26

existed between oral reading fluency and reading proficiency. Although adopting the

limited definition of accuracy and rate (Roehrig et al. 2008), I also acknowledged that

prosody plays an important role in reading and fluency.

However, because prosody is difficult to measure (Fuchs et al., 2001;

Schwanenflugel et al., 2006), I chose to use the more measurable definition of oral

reading fluency. I also acknowledged that oral reading fluency is more that reading

quickly. Proficient readers are also able to comprehend what they read, as supported by

the research question, whether a relationship exists between oral reading fluency and

reading proficiency, as measured by Grade 3 students’ DIBELS ORF and the Grade 3

Reading TAKS.

The Role of Oral Reading Fluency in the Context of Learning to Read

As readers begin to read, fluency has a significant role (Harn et al., 2008).

Fluency for educators may be compared to temperature readings for physicians

(Hasbrouck & Tindal, 2006). A physician considers a patient’s temperature, and if it is

above normal, the physician looks for possible causes and then determines an appropriate

treatment. In a similar way, educators examine oral reading fluency. If a student’s oral

reading fluency rate is below average, educators look for possible causes and then

determine appropriate interventions (Hasbrouck & Tindal).

Ehri (2005) studied the process by which students learn to read words. She

identified five phases: (a) the prealphabetic phase, (b) the partial-alphabetic phase, (c) the

full-alphabetic phase, (d) the consolidated-alphabetic phase, and (e) the automatic-

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alphabetic phase. These phases describe the process that beginning readers engage in as

they develop the skill of reading.

Phonemic awareness is one of the first skills beginning readers must learn. Ehri

(2005) discussed phonemic awareness in her first two phases: the prealphabetic and

partial-alphabetic phases. Beginning readers must learn to recognize that words they use

in their spoken vocabulary are constructed of individual sounds (Ehri & McCormick,

1998). Katzir et al. (2006) demonstrated the role of phonemic awareness in fluency. They

concluded that readers need phonemic awareness the most when decoding words they

have not seen before. After readers have developed a certain level of fluency, the brain

focuses less on phonemic awareness and more on other components of fluency, such as

the speed at which they are able to recognize letter patterns or word units. Researchers

have also found phonemic awareness in kindergarten to be a predictor of oral reading

fluency in later years (Katzir et al.).

As students learn phonemes, they begin to learn phonics, learning to associate the

phonemes to letters or graphemes (Ehri, 2005; Ehri & McCormick, 1998). Although

beginning readers focus on phonemic awareness, they deal only with the sounds of

language. When they begin to understand that letters represent sounds, they use phonics.

In Ehri’s second phase, the partial-alphabetic phase, children use the first and last letters

when identifying words. Children then learn to master the ability to sound out words.

Approximately half way through first grade, most readers enter what Ehri described in

her third phase as the full-alphabetic phase. During the first two phases, readers

laboriously sound out words. As they move into the full-alphabetic phase, they begin to

28

recognize that certain letters work together to make certain sounds. Recognizing more of

these letter patterns, students are able to read faster. Over time, students learn to

recognize more letter patterns and words allowing them to read more words correctly

each minute (Ehri & McCormick).

Researchers have established a relationship between the knowledge of phonetic

elements and fluency (Chard et al., 2008; Eldredge, 2005; Harn et al., 2008). Chard et al.

documented that students who had demonstrated mastery in the alphabetic principal by

the end of Grade 1 were more fluent readers than their struggling peers at the end of

Grades 2 and 3. The readers who struggled with the alphabetic principle in Grade 1 did

not progress at the same rate as their peers who had mastered the alphabetic principle.

Chard et al. emphasized that teachers’ assuring that students have a good grasp of

phonetic knowledge by the end of Grade 1 is critical, because phonetic knowledge serves

as a predictor of how fluently they will read in later years. Mastery at the full-alphabetic

phase is essential before moving to the next two stages, the consolidated-alphabetic and

the automatic-alphabetic phases.

Usually during Grade 2, students progress to Ehri’s (Ehri & McCormick, 1998)

fourth phase, the consolidated-alphabetic phase. Readers begin to recognize more

combinations of letters within words (Harn et al., 2008). They begin to read words

syllable by syllable as well as to recognize prefixes and suffixes in words. This ability to

identify groups of letters helps to facilitate fluent reading as readers recognize more

words by sight (Ehri, 2005). However, readers may not completely develop the concepts

of the full-alphabetic phase until Grade 8 (Ehri & McCormick). In fact, some students

29

learn to read and progress well until approximately Grade 4, when they begin to read

words with four or more syllables. As Ehri pointed out, educators may need to provide

further instruction to help these students see the syllabic units in larger words.

Fluency is the final phase, the automatic-alphabetic phase, in Ehri’s (Ehri &

McCormick, 1998) developmental sequence to early reading proficiency. During this

phase, students are able to read most words quickly and efficiently. When they encounter

a word they do not know, they use one or more of several methods they have developed

to ascertain meaning. Speece and Ritchey (2005) established that oral reading fluency

predicts reading comprehension. In their study with students in Grade 1 and Grade 2, a

significant gap was found between the oral reading fluency rates of students at risk for

reading difficulty and their peers who were not at risk. The researchers concluded that the

most unique variance for students’ second-grade increases in reading mastery and state

assessment achievement was predicted by increases in oral reading fluency for students in

the first grade.

Fluency Instruction

Oral reading fluency has been correlated with overall reading competence (Fuchs

et al., 2001), and studies have confirmed several strategies to improve reading fluency.

When students repeatedly read a passage, their fluency increases (Begeny, Daly, &

Valleley, 2006; Hiebert, 2005; Martens et al., 2007; Therrien, Gormley, & Kubina, 2006;

Therrien & Hughes, 2008). The repeated reading strategies can be implemented in a

variety of ways including readers’ theater, in which students repeatedly read a script as

they prepare to perform the reading for an audience (Corcorcan & Davis, 2005; Rasinski,

30

2006). Although studies have found repeated readings effective, Kuhn (2005) found that

wide reading is just as effective, and Morgan and Sideridis (2006) found motivational

strategies were more effective than repeated readings. In addition, other strategies have

improved fluency. Nes Ferrera (2005) found that pairing struggling readers with more

experienced readers helped the struggling readers to read more fluently. Rasinski and

Stevenson (2005) found parents an effective resource when they helped their at-risk

students by working daily at home with them on reading.

Reading Proficiency

Reading proficiency involves more than mechanical reading of a passage. Based

on their review of literature, the National Reading Panel (NICHHD, 2000) captured the

essence of reading by identifying its five most important components. These are

phonemic awareness, phonics, fluency, vocabulary, and reading comprehension.

Reading Proficiency and Automaticity Theory

Several researchers (Baker et al., 2008; Kuhn, 2005; Morgan & Sideridis, 2006;

Therrien & Hughes, 2008) have confirmed a relationship between reading proficiency

and automaticity. Baker et al. found that the DIBELS ORF rates of 4,696 Grade 3

students in Oregon significantly predicted their performance on the state-mandated

assessment. Students who read fluently also comprehended well enough to attain scores

of proficient on the state assessment.

Kuhn (2005) also confirmed the automaticity theory in a study of 24 Grade 2

students in a southeastern United States city with three student groups. The first group

participated in the repeated reading condition, in which students read the same story

31

repeatedly over a 3-day period using strategies such as modeling, repetition, choral

reading, and pair reading. Over the 6-week period, this procedure was followed with six

books.

The second group participated in the nonrepetitive reading condition, in which

students read each book one time. The students read the same six stories as the ones used

in the repeated reading condition, with an additional 12, so that a new story was available

at each session. The third group participated in the listening only condition, in which the

researcher expressively read the books aloud to the students. Over the 6-week period,

these students listened to the same 18 stories as the students in the nonrepetitive group

read. The fourth group was the control group, in which students received no interventions

outside of the normal classroom instruction (Kuhn, 2005).

Kuhn (2005) found that the repeated reading and nonrepetitive reading

intervention groups were a more effective way to help students decode words than simply

listening or providing no intervention. Thus, Kuhn’s work confirmed the automaticity

theory. The students in the repeated reading and nonrepetitive reading groups

demonstrated that they automaticized the knowledge of words and sounds better than the

students in the listening only and control groups. Students in the first two groups

demonstrated greater gains in their ability to read both real and nonsense words and their

oral reading fluency rates.

Therrien and Hughes (2008) studied the effects of repeated reading and question

generation on students’ reading fluency and comprehension. During a 2-week period,

students who read at Grade 2 or 3 instructional levels were randomly divided into two

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groups. One group received the repeated reading intervention. Students were asked to

read a passage repeatedly until they reached the desired fluency level. On average,

students reached the fluency goal after 2.42 readings. The other group received the

question-generation intervention. Students read the passage once and received questions

to cue them to better comprehend the narrative passage, such as the following: (a) Who is

the main character?, (b) Where and when did the story take place?, and (c) What did the

main character do?

In both groups after the intervention was completed, tutors asked both factual and

inferential questions. Results documented that repeated reading improves fluency:

students in the repeated reading group read 22.5 more correct words per minute than

students in the question-generation group, who only read the passage one time.

Additionally, the students in the repeated reading group comprehended more factual

questions than the students in the question-generation group. There was no significance

difference in the two groups when they answered inferential questions (Therrien &

Hughes, 2008).

Therrien and Hughes (2008) concluded that repeated reading improved both

fluency and comprehension. However, they recommended that additional research be

conducted to determine the effects of text difficulty. Oral reading fluency rates are

important to consider when students are reading passages in which they cannot read a

significant percentage of the words. For example, in this study the researchers considered

instructional level to be one at which students correctly read 85% to 95% of the words.

Therefore, the students in the question-generation group may not have been able to

33

understand 5% to 15% of the words in the text. When students do not know 5% to 15%

of the words in a passage, their comprehension can be affected. The situation can be

further compounded when students read at their level of frustration, less than 85% of the

words in the passage.

Therrien and Hughes (2008) recommended that other research studies focus on

how comprehension is affected by readers’ levels of difficulty. The researchers also

recommended that studies with longer intervention time be conducted to indicate whether

more than 2 weeks of intervention would enable the students in the question-generation

group to use cued questions to answer the inferential questions. This study demonstrated

that repeated reading does improve both fluency and comprehension.

In contrast to these and other studies that found repeated reading to be an effective

intervention (Begeny et al., 2006; Hiebert, 2005; Hudson et al., 2005; Rasinski, 2006;

Therrien et al., 2006; Therrien & Kubina, 2007), Morgan and Sideridis (2006) found that

repeated reading was not as effective as other strategies. They conducted a meta-analysis

of 30 studies that used single-subject research designs to determine “the effectiveness of

different types of interventions on fluency for students with or at risk for learning

disabilities” (p. 200). The researchers categorized the interventions by the following

strategies: (a) keywords and previewing, (b) listening and repeated readings, (c) goal

setting plus performance feedback, (d) contingent reinforcement, (e) goal setting plus

feedback and reinforcement, (f) word recognition, and (g) tutoring.

According to Morgan and Sideridis’ (2006) findings, the most effective

interventions were reinforcement, goal setting plus feedback, and goal setting plus

34

feedback and reinforcement. When the researchers analyzed the students’ improvements

over time, the goal setting interventions showed significant growth, and the listening and

repeated readings interventions did not. Although Morgan and Sideridis’ findings did not

concur with other researchers’ findings regarding repeated readings, their results

nevertheless substantiate the automaticity theory. They found that when students were

motivated to set goals and were positively reinforced, they were able to improve their

automaticity, as demonstrated by increases in their oral reading fluency rates.

Definition of Reading Proficiency

After the authorization of NCLB (2002), the U.S. Department of Education

formed the NARAP to define reading and reading proficiency (2006). Since NCLB

mandated that all students be proficient in reading by 2013-2014, states and test

developers needed a definition of reading proficiency to create appropriate measurement

assessments. This task was not a simple one. The definition had to capture the essence of

reading and encompass the developmental attributes of reading across grade levels

(NARAP).

Each of the 50 states defines reading proficiency at each grade level in terms of

their curriculum expectations, as measured by the state’s reading assessment. NARAP’s

(2006) definition also had to include students with disabilities who access texts

differently from nondisabled students. For example, blind students access texts through

braille. Hearing-impaired students may not decode the words of a text in the same

manner as nonhearing-impaired students. Furthermore, students with learning disabilities

35

such as dyslexia may require accommodations, including extra time in order to read a

passage proficiently.

Thus, the national definition of reading proficiency had to allow for differences in

states’ definitions, curriculum differences, students’ ages and grades, and conditions of

handicap. After NARAP (2006) convened a panel of experts who were discussing

working definitions with focus groups, NARAP formulated the following definition of

reading proficiency:

Reading is the process of deriving meaning from text. For the majority of readers,

this process involves decoding written text. Some individuals require adaptations

such as braille or auditorization to support the decoding process. Understanding

text is determined by the purposes for reading, the context, the nature of the text,

and the readers’ strategies and knowledge. (Cline et al., 2006, para. 8)

Following from this definition, states were able to use it as a guide to examine

their curriculum expectations at each grade level and design assessments to measure

reading proficiency. Under the NCLB (2002), implementation means that 50 different

states are assessing reading proficiency at Grades 3, 5, 8, and exit level. Consequently,

200 definitions could exist for defining reading proficiency (four grades times 50 states).

Many states also give assessments of reading proficiency in more grades. In Texas, for

example, assessments are given in eight grades, Grades 3 through 10 (TEA, 2009d).

Definitions vary among states. TEA, for example, requires proficient readers in

Grade 3 to have a basic understanding of reading, apply knowledge of literary elements,

use a variety of strategies to analyze text, and apply critical-thinking skills to analyze the

36

passage (TEA, 2004). Florida’s state assessment that measures reading proficiency

contains four areas of assessment: (a) word phrases in context; (b) main idea, plot, and

purpose; (c) comparison and cause/effect; and (d) reference and research (Florida

Department of Education, 2005). In Colorado, the definition of reading proficiency

includes requiring students to “locate, select, and make use of relevant information from

a variety of media, reference, and technological sources” and to “read and recognize

literature as a record of human experience” (Colorado Department of Education, 2010,

para.7). Even though NARAP (2006) provided states with a general definition of reading

proficiency, as these examples show, each state assesses reading proficiency with its

own definition, based on their curriculum standards.

As the definition of reading proficiency in Texas shows, reading proficiency is a

complex skill. Proficient readers, as noted earlier, must attach meaning to the words they

read to understand what the author is communicating (NARAP, 2006). Proficient readers

not only read the words on a page, but they use strategies to read between the lines and

beyond the lines. Thus, a review of literature relating to vocabulary and comprehension is

warranted.

Vocabulary and Matthew Effects

Vocabulary is one of the National Reading Panel’s five essential components for

effective reading programs (NICHHD, 2000). Vocabulary is comprised of the words an

individual knows (Rosenthal & Ehri, 2008). People may identify words by the way they

sound, the way they are used in context, or the way they are spelled. New words are

introduced either through words that are heard or read. Thus, readers can read more

37

proficiently when they decode unknown words and attempt to determine the meaning of

unknown words (NICHHD, 2000). Ouellette (2006) found that readers are more likely to

decode an unknown word if it exists in their spoken vocabulary. When readers know 90%

to 95% of the words in a text, they are able to figure out the meaning of the other

unknown words (Hirsch, 2003).

Struggling readers have difficulty decoding words. Because reading is difficult for

them, they become frustrated (Ehri & McCormick, 1998). They must work hard to read

and often find numerous ways to avoid reading. Consequently, they do not want to read

widely, and their vocabulary does not increase. Conversely, proficient readers have a

larger vocabulary than struggling readers because they have read more. Proficient readers

are able to use their vocabulary to decode and determine the meaning of even more

unknown words. The more they read, the more they know. Stanovich (1998) referred to

this gap between proficient readers and their struggling peers as Matthew effects—a

reference to the Biblical passage, Matthew 25:29, that refers to the rich becoming richer

and the poor becoming poorer (p. 10). For struggling readers, the gap widens as they

progress through the grades (Morgan et al., 2008; Stanovich, 1998).

Several studies support Matthew effects. Katz, Stone, Carlisle, Corey, and Zeng

(2008) studied the difference in growth of reading skills between Grade 1 proficient

readers and struggling readers. The researchers reported that not only did the struggling

readers have lower oral reading fluency rates than the proficient readers, but they

improved at a slower rate. A study with students in kindergarten to Grade 3 in Oregon

and Texas documented the presence of Matthew effects for students in all four grades

38

(Chard et al., 2008). Rosenthal and Ehri (2008) studied the acquisition of new vocabulary

with students in Grades 2 and 5. For students at both grade levels, the researchers

documented the gap between struggling readers and proficient readers and its effect on

students’ learning of new words.

Consequently, struggling readers’ vocabulary is limited when compared to their

proficient peers (Rosenthal & Ehri, 2008). Struggling readers’ limited vocabulary hinders

them from learning as many new words as their proficient fellow students. Struggling

readers who have a limited vocabulary have difficulty understanding texts that they read,

decoding and learning new words, and developing skills that allow them to become

proficient readers.

Comprehension

The final component for effective reading programs identified by the National

Reading Panel is comprehension (NICHHD, 2000). Comprehension and oral reading

fluency rates are related, and researchers continue to examine the relationship from

various perspectives. These include questions such as the following: Are oral reading

fluency rates and comprehension related only in the beginning stages of reading? Do all

readers with low reading fluency rates struggle with comprehension? Are there readers

with high oral reading fluency rates who are unable to comprehend? The following

researchers have asked these questions.

Fuchs et al. (2001) were among the first to establish oral reading fluency as an

accurate and reliable measure that served as a predictor of general reading

comprehension. Other researchers (Baker et al., 2008; Chard et al., 2008; Katz et al.,

39

2008; Simmons et al., 2008) have since correlated oral reading fluency rates and

comprehension at different grade levels and on a variety of assessments. As beginning

readers progress through the various phases of learning to read (Ehri, 2005), teachers

design instructional strategies to meet their needs and help them improve their reading

skills. By the middle of first grade, a connection is established between how many words

a minute students read and how much they comprehend (Hosp & Fuchs, 2005).

For students in Grades 1 through 4, researchers (Hosp & Fuchs, 2005; Simmons

et al., 2008) have found that oral reading fluency correlated with reading performance on

the Woodcock Reading Mastery Test-Revised (Woodcock, 1973). For these same grades,

other researchers have studied the relationship between oral reading fluency and

comprehension (Daane et al., 2005). Baker et al. (2008) and Chard et al. (2008) found a

relationship between oral reading fluency rates and performance on SAT-10. The results

of Pressley et al. (2005) confirmed a relationship between oral reading fluency and

reading performance on the TerraNova. Speece and Ritchey (2005) also demonstrated the

relationship between oral reading fluency and the Comprehensive Test of Phonological

Processing (CTOPP) and the Test of Word Reading Efficiency (TOWRE).

Researchers have also studied the relationship between oral reading fluency and

comprehension in older students. With students above Grade 4, Therrien and Hughes

(2008) as well as Therrien and Kubina (2007) found that oral reading fluency and

comprehension were significantly related. In work with middle and junior high school

students, Fuchs et al. (2001) established a correlation between oral reading fluency and

reading proficiency as measured by the Stanford Achievement Test. However, for

40

students at various grade levels, additional research should be conducted to examine

whether a statistically significant relationship exists between oral reading fluency and

reading proficiency as defined by specific state reading assessments, such as the TAKS.

The current study filled this gap for Grade 3 students in Texas.

Older struggling readers with low oral reading fluency rates can learn to use

certain learning strategies to improve their comprehension (Walczyk & Griffith-Ross,

2007). Walczyk and Griffith-Ross worked with students in Grades 3, 5, and 7 to

determine if struggling readers at these grade levels could develop compensatory

strategies to help them read text. The researchers found that struggling readers sometimes

slowed down in order to facilitate their comprehension. For example, to compensate for

decoding unknown words, struggling readers would sound out unknown words or simply

skip them. When the students realized they were not comprehending, they might pause,

look back, or reread the text.

In addition, factors other than familiarity or understanding of words can affect

comprehension. These factors include degree of readers’ motivation or feelings of time

pressure. Walczyk and Griffith-Ross (2007) found that students who had low motivation

read slowly, but those who were interested in the text could comprehend by using

compensation strategies. Stage of maturation also seemed to play a role in the effect of

time pressure on comprehension. Students in Grade 3 comprehended less when under

time constraints than students in Grade 7. However, students in Grade 5 performed at

generally the same level with and without time constraints.

41

Walczyk and Griffith-Ross (2007) conjectured that the readers’ engagement made

the difference. The students in Grade 3 seemed to be engaged in the text as they tried to

decode the words, and time pressure negatively affected their comprehension. In contrast,

by Grade 7 many of the students had become less engaged with routine reading

assignments, but their engagement increased when they were timed. The students in

Grade 5 appeared to be in transition between the two modes of reading text. Thus,

Walczyk and Griffith-Ross demonstrated that students with low fluency rates can

comprehend text by using metacognitive strategies to compensate, such as sounding out

words, and engaging with greater motivation when experiencing time pressure.

Researchers indicate that oral reading fluency rates predict comprehension (Chard

et al., 2008; Daane et al., 2005) not because readers can read a passage quickly but

because fluent readers are able to use mental energy comprehending rather than

struggling with decoding (Fuchs et al., 2001; Samuels, 2006). Kuhn et al. (2005)

indicated that when the readers in their study focused on how fast they read the passage,

their comprehension was not as effective as those who focused on the passage itself.

Samuels (2007) reiterated that when readers focus too intensely on how fast they are

reading, their ability to comprehend suffers.

Fluency is only one component of reading (NICHHD, 2000). When Hasbrouck

and Tindal (2006) developed the oral reading fluency norms, they observed that once

readers reached the 50th percentile, teachers should not encourage them to read faster.

The researchers recommended that teachers only provide intervention for those students

who read 10 words per minute below the 50th percentile. This advice was based on the

42

principle that fluency intervention is reading fluently enough to focus on comprehension

rather than a race for readers of the most words in a minute.

Some readers read fluently but have trouble comprehending (Harrison, 2008;

Samuels, 2006). If readers are not actively engaged in the reading process, they can

mechanically read a passage but not understand what the author is saying (Schnick &

Knickelbine, 2000). Readers who are intrinsically motivated to read can understand what

the author is saying because they are curious and want to read more. In contrast, readers

who are not motivated to read are often not engaged and fail to make the necessary

connections for comprehension.

Marcell (2007) reported on a student who was able to read a passage fluently at

120 words correct per minute but could not retell what he had read. This student needed

further instruction in comprehension strategies in order to become a proficient reader.

Samuels (2006) pointed out that students whose second language is English may

successfully decode passages although they have very little comprehension. His work

with among students in St. Paul, Minnesota, revealed that although about 20% could read

fluently, they could not comprehend what they read. Furthermore, some high-

comprehending readers have low fluency rates (Samuels, 2006).

The goal of reading is to comprehend or understand text (Applegate et al., 2009;

NICHHD, 2000), and the studies in this section indicate a relationship between students’

oral reading fluency rates and comprehension at various stages of reading and grade

levels. Oral reading fluency rates are important not because of how fast students read but

43

because fluency demands little conscious attention and enables them to focus on

comprehension (Samuels, 2006).

Relationship Between Oral Reading Fluency and Reading Proficiency in State-

Mandated Assessments

Since LaBerge and Samuels’ (1974) development of the automaticity theory,

many studies (Daane et al., 2005; Kuhn, 2005; Riedel, 2007) have confirmed a

relationship between how fluently students read and how proficiently they comprehend

text at various grade levels. However, fewer studies have considered oral reading fluency

rates with the DIBELS ORF and reading proficiency as measured by state-mandated

assessments. Many school districts use the DIBELS ORF assessment to identify students

at risk for failing (Cusumano, 2007; Fletcher, Francis, Morris, & Lyon, 2005; Gersten &

Dimino, 2006; Jenkins et al., 2007; Katz et al., 2008; Stecker, Lembke, & Foegen, 2008;

Wood, Hill, Meyer, & Flowers, 2005). Studies have been conducted for only seven states

for positive correlations between students’ oral reading fluency rates, measured by the

DIBELS ORF, and reading proficiency, using their states’ mandated reading assessments.

These states are as follows: Arizona (Wilson, 2005), Colorado (Shaw & Shaw, 2002;

Wood, 2006), Florida (Buck & Torgesen, 2003; Roehrig et al., 2008), North Carolina

(Barger, 2003), Ohio (Vander Meer et al., 2005), Oregon (Baker et al., 2008), and

Pennsylvania (Shapiro et al., 2008).

44

Studies of Grade 3 Only

Researchers have conducted two studies with Grade 3 students only. In Colorado,

Shaw and Shaw (2002) conducted research using 52 Grade 3 students from a Colorado

elementary school to determine if the DIBELS ORF benchmarks were a predictor of

success on the Colorado State Assessment Program. The researchers found the DIBELS

ORF to be strongly correlated, .80, the highest correlation of the studies reviewed here.

For Florida Grade 3 students, Buck and Torgesen (2003) compared the DIBELS

ORF rates of 1,102 students in 13 elementary schools to their performance on the Florida

Comprehension Assessment Test. The researchers found a significant correlation, .70.

They thus concluded that for this sample the DIBELS ORF rate was a predictor of

success on the Florida Comprehension Assessment Test.

Studies of Reading First Schools

For studies in three states, the researchers (Baker et al., 2008; Roehrig et al.,

2008; Wilson, 2005) used the large databases from Reading First schools to determine if

DIBELS ORF correlated with state-mandated assessments. To identify and monitor the

progress of struggling readers, over 90% of the Reading First schools used DIBELS oral

reading fluency (Glenn, 2007; U.S. Department of Education, 2010). With an Arizona

Reading First school, Wilson conducted a study with 241 Grade 3 students. He found a

moderately large correlation (.74) between the DIBELS ORF and the Arizona Instrument

to Measure Standards. Roehrig et al. conducted a similar study with Florida students, in

which the DIBELS ORF rates of 35,207 Grade 3 students were compared to their

performance on the Florida Comprehensive Assessment. Correlations were also

45

moderately large, ranging from .70 to .71. In Oregon, Baker et al. used 34 randomly

selected Oregon Reading First schools located in 16 different school districts. The

researchers compared the DIBELS ORF rates of 4,696 Grade 3 students with their

performance on the Oregon State Reading Assessment. The correlations ranged from

0.58 to 0.68, somewhat lower than the Arizona and Florida studies.

Pressley et al. (2005) suggested that studies on the DIBELS should be conducted

by researchers not associated with Reading First. In response, Barger (2003) compared

the DIBELS ORF rates of 38 students to the North Carolina End of Grade 3 Test. Barger

also found a moderately large correlation (.73), similar to those found by Wilson (2005)

and Roehrig et al. (2008). These researchers documented the positive relationship

between the DIBELS ORF and four different state-mandated reading assessments for

Grade 3 students.

Studies of Grade 3 and Other Grades

However, Fuchs et al. (2001) suggested that the correlation between oral reading

fluency and comprehension may be stronger in Grade 3 than in other grades, for which

assessments measure higher levels of comprehension. Three groups of researchers

(Shapiro et al., 2008; Vander Meer et al., 2005; Wood, 2006) studied this issue by using

students in Grades 3, 4, and 5. For Colorado schools, Wood (2006) used 82 Grade 3

students, 101 Grade 4 students, and 98 Grade 5 students to determine if the DIBELS ORF

consistently predicted performance on the Colorado Student Assessment Program across

grade levels. Wood found significant correlations at all three levels: for Grade 3 at .70,

46

Grade 4 at .67, and Grade 5 at .75. These values were similar to those found by Wilson

(2005), Roehrig et al. (2008), and Barger (2003) for Reading First schools.

For two grade levels with students in Ohio, Vander Meer et al. (2005) correlated

the end-of-year Grade 3 DIBELS ORF with performance on the reading portion of the

Ohio Proficiency Test. A total of 318 Grade 4 students from three elementary schools

comprised the sample. Vander Meer et al. (2005) found a significant correlation, .65,

between the end-of-year Grade 3 ORF scores and the Grade 4 Ohio Proficiency Test

scores. Because this study considered the same students across two successive grades, the

researchers concluded that oral reading fluency was an accurate predictor of performance

on the reading portion of the Ohio Proficiency Test.

With students in Pennsylvania across grade levels, Shapiro et al. (2008) compared

the DIBELS ORF rates of 401 Grade 3 students, 394 Grade 4 students, and 205 Grade 5

students with their performance on the Pennsylvania System of School Assessment. The

researchers found significant correlations for all three grades: Grade 3 at.67, Grade 4 at

.64, and Grade 5 at.73. Again, these results were similar to those of the previous studies.

The findings of Wood (2006) and Shapiro et al. support the use of the DIBELS ORF as a

consistent predictor of performance on state-mandated reading assessments not only for

Grade 3 but also across grade levels.

Thus, for seven states of the 50 that require state-mandated assessments of

reading proficiency, studies have found significant positive relationship between the

DIBELS ORF and the state measures. However, because definitions of reading

proficiency differ across states and grade levels, the need existed for researchers to

47

determine if DIBELS ORF correlates significantly with state-mandated assessments in

other states and at other grade levels (Roehrig et al., 2008). The present study focused on

Grade 3 students in Texas. No similar study has been conducted to determine if a

significant relationship existed for Grade 3 students between DIBELS ORF rates

(independent variable) and reading proficiency (dependent variable), as measured by the

scores on the Grade 3 Reading TAKS.

Limitations of State Studies

In the studies reviewed above, the researchers all reported significant

relationships between the DIBELS ORF in relation to Grade 3 students and reading

proficiency as assessed on state-mandated assessments. However, the researchers also

recognized limitations of their studies. One limitation was sample composition and size.

For example, the Colorado sample (Wood, 2006) consisted of primarily White students.

The North Carolina sample (Barger, 2003) had only 38 students. On the other hand, the

Oregon sample (Baker et al., 2008) and one of the Florida samples (Roehrig et al., 2008)

had large statewide samples from students in Reading First schools. One of the criteria

for being a Reading First school was a high population of students from low

socioeconomic backgrounds, and thus these samples were not representative of the

general Grade 3 population. In all these studies, researchers recommended future research

that would include wider cross-sections of students as well as non-Reading First schools

for greater generalizability of results to other school settings.

Another limitation of these studies was recognition of other variables that might

affect the relationship between oral reading fluency and reading proficiency. In the

48

Oregon study, Baker et al. (2008) singled out diversity as a factor. The Reading First

sample schools had large poverty rates and low reading achievement, and Baker et al.

recommended additional research that focused on specific ethnic backgrounds as well as

subpopulations, such as special education students. In Arizona, Wilson (2005)

recommended future studies after Arizona implemented the 2005 Arizona’s Instrument to

Measure Standards Dual Purpose Assessment (AIMS DPA) measurement scale and

performance levels. Wilson posited that the relationships between scores would be

different with the new standards. When Wilson published his results, it was not clear

whether the expected performance levels would be higher or lower than the ones used in

his study.

For the Pennsylvania study, Shapiro et al. (2008) used data from the 4Sight

assessments in addition to DIBELS. They used the 4Sight assessments to provide further

information on students’ reading comprehension to predict reading proficiency. The

4Sight assessments are short tests similar in format and other aspects to state assessments

and are used throughout the school year to produce overall scores that may predict

students’ scores on state assessments. Many states use the 4Sight assessments, including

California, Pennsylvania, Tennessee, and Texas (Success for All Foundation, 2010).

In the Pennsylvania study (Shapiro et al., 2008), the 4Sight benchmark

assessments were administered to students as a group rather than individually. Whole

group administration enabled researchers to assess many students in approximately 1

hour. However, some reading skills, such as oral reading fluency, are best tested when

49

administered individually so educators can monitor the rate and accuracy with which a

student reads.

Shapiro et al. (2008) recommended future studies in other states to determine if

their findings could be replicated. Additional studies over time and in various locations

would help generalize the findings to larger populations. Shapiro et al. also noted that the

schools in their samples represented varying demographic characteristics but were similar

in their levels of poverty. The researchers recommended additional studies in other

schools with different poverty levels to eliminate poverty as a factor and for greater

generalization.

As a result of these limitations and recommendations, researchers indicate the

need for additional studies on the DIBELS ORF and state-mandated assessments, in

Grade 3 and other grades. Roehrig et al. (2008) pointed out this need especially in other

states. I responded to this need with this study to determine if a statistically significant

relationship existed between the DIBELS ORF and the TAKS for Grade 3 students in

Texas.

Summary

In section 2, literature regarding the automaticity theory, oral reading fluency, and

reading proficiency was reviewed. LaBerge and Samuels (1974) developed the

automaticity theory to explain why readers who struggle with low oral reading fluency

rates also struggle with comprehension. La Berge and Samuels and other researchers that

followed (Baker et al., 2008; Kuhn, 2005; Morgan & Sideridis, 2006) demonstrated that

readers have a limited amount of attention to devote to reading. When too much attention

50

is focused on decoding words, readers have insufficient attention to allocate to other

aspects of reading, such as comprehending.

Next, I reviewed oral reading fluency, beginning with various definitions of oral

reading fluency (Allington, 2009; Deeney, 2010; Hudson et al., 2005; Kame’enui &

Simmons, 2001; Marcell, 2007; Roehrig et al., 2008; Worthy & Broaddus, 2002).

Researchers have pointed out the complexity of oral reading fluency and demonstrated

norms (Hasbrouck & Tindal, 2006; Kame’enui & Simmons, 2001). The role of oral

reading fluency was then reviewed in the context of learning to read (Ehri, 2005; Ehri &

McCormick, 1998).

Finally, I reviewed literature relating to reading proficiency. In NCLB (2002),

legislators required the development of a definition of reading proficiency that is flexible

enough to be measured by state reading assessments in all 50 states (NARAP, 2006).

Vocabulary (Ouellette, 2006) and comprehension (Samuels, 2006) are important aspects

of reading proficiency that generally cannot take place until students reach a certain level

of oral reading fluency. Once readers are able to fluently decode text, they can devote

their attention to other aspects of reading, such as vocabulary and comprehension.

Researchers in Arizona (Wilson, 2005), Colorado (Shaw & Shaw, 2002; Wood, 2006),

Florida (Buck & Torgesen, 2003; Roehrig et al., 2008), North Carolina (Barger, 2003),

Ohio (Vander Meer et al., 2005), Oregon (Baker et al., 2008), and Pennsylvania (Shapiro

et al., 2008) have established a relationship between oral reading fluency rates and

reading proficiency as measured on their state-mandated reading assessment.

51

However, the specific definition of reading proficiency varies from state to state

because the state-mandated reading assessments are based on the reading objectives

defined in the state curricula (NARAP, 2006). It is therefore necessary for researchers in

other states to determine if a relationship exists between oral reading fluency rates and

their state-mandated assessment (Roehrig et al., 2008). This study investigated whether a

statistically significant relationship (p < .05) existed between oral reading fluency rates as

measured by the middle-of-Grade 3 DIBELS benchmark rates and the reading

proficiency measured by the scale score of the Grade 3 Reading TAKS. In section 3, I

focus on the methodology of this study. In section 4, I report the findings of the study,

and in section 5, I discuss implications of the findings in comparison with previous

studies, application to social change, and recommendations for action and further

research.

52

Section 3: Research Design

Introduction

The purpose of this study was to determine whether a statistically significant

relationship (p < .05) existed between Grade 3 students’ oral reading fluency rates and

their reading proficiency. In this section, I explain the research design of this study,

followed by a description of the sample and population. Then, I discuss the reliability and

validity of the two instruments used in this study and finally the procedures for data

collection and analysis.

Research Design

I designed this quantitative study to determine if a statistically significant

relationship (p < .05) existed between oral reading fluency and reading proficiency.

Specifically, I used the middle-of-year DIBELS ORF rates of 155 students in a Texas

school district as the independent variable to measure oral reading fluency rates, and the

scale scores on the Grade 3 Reading TAKS as the dependent variable to measure reading

proficiency. I did not conduct experimental research to determine, for example, if one

group performed better than another group with regard to either oral reading fluency rates

or reading proficiency, because the study purpose was to determine if a relationship

existed between oral reading proficiency and reading proficiency.

Neither a qualitative study nor a mixed study was appropriate because I focused

on quantitative statistical data to fulfill the study purpose. These data were used to

determine whether a statistically significant relationship (p < .05) existed between Grade

3 students’ oral reading fluency and their reading proficiency on a state-mandated

53

assessment. This purpose was in contrast to that of a qualitative study, which might ask

students about their attitudes, feelings, or self-efficacy during performance on the

examination.

I considered several nonexperimental research methods, including point-biserial

correlation, Spearman correlation, chi-square test for independence, and Pearson

correlation. The point-biserial correlation is a type of formula researchers use to

determine relationships between two variables when one variable can represent only one

of two components (Gravetter & Wallnau, 2005). For example, in a study in which a

student can either pass or fail an examination, researchers assign each of the options of

the pass-fail dichotomous variable a number. A researcher might assign 1 if the student

passes the examination and 0 if the student fails it. However, I did not use a point-biserial

correlation because neither of the variables was dichotomous.

Researchers also use Spearman correlations to determine relationships between

two variables in which the variables are rank ordered (Gravetter & Wallnau, 2005). For

example, this study could have used the students’ middle-of-year DIBELS ORF rates to

rank the students from the fastest to the slowest readers. I could have also ranked students

by the scale scores received on the Grade 3 Reading TAKS. I then would have used the

Spearman correlation to determine the relationship between the students’ performance on

both assessments.

However, I chose not to use a Spearman correlation because students’ same

scores could skew the data and render inaccurate results. Specifically, all the students

who reached a scale score of exactly 2100 on the Grade 3 Reading TAKS would have

54

received the same ranking. Because there are 36 questions on the Grade 3 Reading

TAKS, I could have used 36 ranks. However, the oral reading fluency rates could then

yield a greater number of ranks because the students could read anywhere between 0 to

150 or more words correct per minute. The Spearman correlation was additionally

inappropriate because the results would yield a different number of ranks for each

variable.

I also considered using a chi-square test for goodness of fit that uses frequencies

to determine if the frequencies in the sample fit the frequencies in the population

(Gravetter & Wallnau, 2005). For example, in this study a chi-square could have been

used to determine the percentage of Grade 3 students in each of three categories, that is,

at-risk, some-risk, and low-risk readers, who passed and failed the TAKS. I would then

calculate and compare the percentage of frequencies in both the sample and population.

However, I did not include the categorization of students in the study purpose.

I chose a Pearson correlation as the most appropriate nonexperimental statistical

method for this study. Pearson correlations “measure and describe a relationship between

two variables” (Gravetter & Wallnau, 2005, p. 412). In this study, I described and

measured the relationship between the middle-of-year Grade 3 students’ DIBELS ORF

rates and their scale scores on the Grade 3 Reading TAKS. If I had used the point-biserial

method, results would have simply indicated whether students passed or failed the

assessment. However, using the Pearson correlation, I obtained additional information

that described the relationship between the two variables. For example, instead of

indicating solely whether the students passed or failed, I could determine the range of

55

scores with greater precision, such as whether the students passed with a minimum scale

score of 2100 on the Grade 3 Reading TAKS or whether they passed with a high score of

2400 or more.

Although I could have obtained useful information from a chi-square analysis, but

with a Pearson correlation I acquired the most accurate data analysis. A chi-square test is

a nonparametric test, and the Pearson correlation is a parametric test. Researchers prefer

parametric tests because they require statistical data on individual participants (Gravetter

& Wallnau, 2005). However, some researchers use nonparametric tests in studies when

detailed data on individual participants are not available. Because detailed data of

individual participants were available for the present study, I chose the more reliable

parametric test, the Pearson correlation.

Setting and Sample

Setting

This study took place in a West Texas town with a population of 6,821.

According to the community’s economic development corporation, the average annual

income of the 2,946 households at the time of the study was $37,000. For reasons of

confidentiality, the source for this information was not referenced in this study.

Approximately 38% of the households had school-age children, and 160 students in the

district were in Grade 3. All of these students attended the same elementary school.

Characteristics of the Sample

In Table 1, I show the characteristics of the sample and compare them to the

population of Grade 3 students in Texas who took the Grade 3 Reading TAKS in March

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2009. Of the students in Grade 3 in the district, 52% were male and 48% were female. In

terms of ethnicity, 54% of the students were Hispanic, 38% were White, 6% were Black,

and 1% was Native American. The district listed 56% of the students as economically

disadvantaged, with10% in special education.

Table 1

Characteristics of Grade 3 Students in Texas Overall and the Research Site Characteristic

Texas Overall (%)

Local District (%)

Male

50

52

Female

50

48

White

37

38

Hispanic

44

54

Black

15

6

Native American

<1

1

Asian

4

0

Economically disadvantaged

56

56

Special education

5

10

Total participants

316,319

159

Note. From Texas Education Agency (TEA, 2009c, 2009d).

As shown in Table 1, the characteristics of the district population were similar to

those of the state overall. Consequently, the sample of Grade 3 students from this school

district was representative of the population of Grade 3 Texas students overall. In 2009,

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all 316,319 Texas students took the first administration of the Grade 3 Reading TAKS

(TEA, 2009c). In the district at the research site, all 155 students took the Grade 3

Reading TAKS (TEA, 2009d).

Sampling Method

The sampling method for this study was a nonprobability convenience sample of

Grade 3 students. Since all Grade 3 students attended the same elementary school, all

these students comprised the study sample. Although random selection would have more

closely ensured that participants represented the population (Creswell, 2009), a

convenience sample, such as that for the present study, used an already formed sample.

However, because the total number of students was 155 (Table 1), I chose the larger

convenience sample rather than a randomly selected smaller sample to increase

representativeness.

Sample Size

The sample was comprised of 155 students. I considered a random sample size of

50 but recognized concerns of sample variance in inferring the results of a sample to an

entire population. When researchers use a sample of 20 or 50 to make inferences to a

population of thousands, the sample variance is generally higher than with a sample of

100 or more (Gravetter & Wallnau, 2005).

In addition, I conducted an a priori power analysis to determine a statistically

acceptable sample size. For one-tailed (unidirectional) bivariate correlation analysis, the

power indicated was .80, a power acceptable for research studies. The effect size

indicated for correlation was medium, .30. The population effect size is the measure of

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the strength (effect) of the alternative hypothesis. The alpha level was set at .05, widely

acceptable in educational research (Creswell, 2009). This value indicates a 5%

probability of committing a Type I error, in which a researcher would reject the null

hypothesis when it was actually true (Gravetter & Wallnau, 2005). I used the G*Power

statistical program (Faul, Erdfelder, Lang & Buchner, 2007), and results showed a

minimum required sample size of 64. The power analysis provided additional support for

the nonprobability convenience sample of 155 students.

Eligibility Criteria for Study Participants

I set three criteria for students to participate in this study. First, students must

have attended Grade 3 in the district during the 2008-2009 school year. Second, teachers

would have screened these students with the middle-of-year DIBELS benchmark in

January 2009. Third, students must have taken the Grade 3 TAKS Reading assessment in

March 2009.

Instrumentation and Materials

I used two instruments in this study to determine if a statistically significant

relationship (p < .05) existed between Grade 3 students’ oral reading fluency and reading

proficiency. The first instrument was the DIBELS ORF, the independent variable, which

teachers administered to students in the middle of the school year. The second instrument

was the Grade 3 Reading TAKS, the dependent variable, which students took at the end

of the school year.

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DIBELS ORF

Researchers have identified oral reading fluency as a predictor of reading

proficiency (Fuchs et al., 2001; Hasbrouck & Tindal, 2006; Pikulski & Chard, 2005).

Educators use oral reading fluency benchmarks to measure the number of correct words a

student correctly reads in 1 minute in three passages. The original study for DIBELS was

conducted in Lane County, Oregon, with a sample of 673 students in kindergarten

through Grade 3 (DIBELS, 2002). For Grade 3, Good and Kaminski (2002a) used the

Spache Readability Formula and determined the readability of the passages at 2.9, 3.0,

and 3.1 grade levels, respectively. The developers selected these passages for Grade 3 so

that the first one, “The Field Trip,” represented the easiest passages (2.9). The second

one, “Keiko the Killer Whale,” represented passages of medium difficulty (3.0). The third

one, “Getting Email,” represented passages of greatest difficulty (3.1).

The developers of the DIBELS (University of Oregon Center in Teaching and

Learning, 2008) established categories that educators can use to determine if students are

at low risk, some risk, or at risk for poor language and reading outcomes. Students who

read less than 67 correct words per minute on the middle-of-year ORF benchmark in

Grade 3 are at risk for poor language and reading outcomes; students who read between

67 and 91 correct words per minute are at some risk; and students who read 92 or more

words per minute are at low risk for poor language and reading outcomes. From their

sample, the University of Oregon Center on Teaching and Learning determined that for

number of correct words a student correctly reads in 1 minute, some students in the low-

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risk category are more likely to pass reading outcomes, and conversely, students in the at-

risk category are more likely to fail reading outcomes than pass.

Barger (2003) found these categories to be accurate in correlating the end-of-year

DIBELS ORF of 38 students to the North Carolina End-of-Grade Test. In his study,

100% of the students in the low-risk category passed the assessment, and 67% of the

students in the at-risk category failed the assessment. Baker et al. (2008) also confirmed

the findings of the University of Oregon Center on Teaching and Learning (2008) in a

study of 9,602 Oregon students in Grades 1, 2, and 3. As discussed in section 2, other

researchers found similar results (Buck & Torgesen, 2003; Shaw & Shaw, 2002; Vander

Meer et al., 2005; Wilson, 2005).

In addition to the number of correct words a student correctly reads in 1 minute,

educators use another component of the DIBELS ORF to assess students on retelling

what they read (Good & Kaminski, 2002b). The purpose of the retell fluency assessment

is to verify that students understand what they read, as opposed to simply word calling.

The developers of the DIBELS, Good and Kaminski, established that students should use

at least 25% of the number of words read when they retell a passage. Students who read

100 correct words per minute should use at least 25 words when they retell a passage.

Furthermore, Good and Kaminski specified that students who are progressing

appropriately toward their reading goal must read at their determined goal and use at least

25% of the words read correctly in 1 minute when retelling a passage.

Reliability and validity of the DIBELS ORF. The developers of the DIBELS

ORF probes established their reliability and validity. Researchers use reliability to

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indicate whether an assessment consistently provides a score that researchers can trust

(Creswell, 2009). When the assessment committee analyzed DIBELS (DIBELS, 2002),

they found test-retest coefficients between .91 and .96 when the DIBELS ORF was

compared to other comparable assessments (DIBELS). The 1-minute fluency probes

provided reliable results. However, the developers recommended administering three to

five 1-minute probes to improve reliability.

Researchers use validity to indicate whether an assessment measures what it is

intended to measure (Creswell, 2009). They use concurrent validity to establish whether

the scores from one assessment compare to the scores from similar assessments

(Creswell, 2008). Hasbrouck and Tindal (1992) developed national oral reading fluency

norms by comparing the oral reading fluency rates of students throughout the country.

The DIBELS Assessment Committee (2002) indicated that the Hasbrouck and Tindal’s

(1992) research corresponded with the DIBELS’ benchmark goals.

In 2006, Hasbrouck and Tindal updated the national norms of ORF and expanded

them to include Grades 1 through 8. Their study included the DIBELS ORF probes along

with the Texas Primary Reading Inventory (University of Houston, 1999); AIMSweb

(Edformation, 2004); and the Reading Fluency Monitor (Read Naturally, 2002).

Hasbrouck and Tindal found similar results to the developers of DIBELS (Good &

Kaminski, 2002b). Examining the oral reading fluency rates of 17,383 students in the

middle-of-year Grade 3, Hasbrouck and Tindal found that students in the bottom 25th

percentile read less than 63 words correctly in a minute. The top half of the Grade 3

students in the middle of the year read more than 92 words correctly per minute.

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Jenkins et al. (2007) reviewed studies that used ORF screenings during the

previous 10 years and concluded that the DIBELS ORF screenings were comparable to

other fluency assessments. This conclusion applied especially to students scoring in the

lowest category, at risk, and those scoring in the highest category, low risk. Jenkins et al.

found that the DIBELS cut scores tended to overestimate students in the middle category,

some risk. For comparison of results, they referred to Buck and Torgesen’s (2003) study

conducted in Florida Reading First schools, in which students in the middle group were

equally likely to perform satisfactorily or unsatisfactory on other assessments.

A study conducted in Oregon and Texas (Harn et al., 2008) confirmed that the

results of the DIBELS ORF rates provided comparable results. Harn et al. based their

study on Ehri’s (2005) phase theory, explained in section 2. In accordance with the

model, students in the prealphabetic phase progress from painstakingly sounding out

every letter in a word to recognizing units of sound within words. Eventually, they

progress to the more advanced consolidated alphabetic phase, in which they can fluently

read passages.

Jenkins et al. (2007) confirmed Ehri’s (2005) phase theory. The researchers

measured entering first-grade students’ knowledge of letter sounds using DIBEL’s

Nonsense Word Fluency assessment and compared it with their oral reading fluency rate

at the end of the Grade 1 using the DIBELS’ oral reading fluency assessment. DIBELS

ORF rates produced reliable results, confirming that first-grade students at the beginning

of the year in the prealphabetic phase who were able to recognize letter sounds

progressed to the consolidated alphabetic phase and were able to fluently read connected

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text by the end of Grade 1. Thus, these researchers, as well as others, have established the

concurrent validity of DIBELS ORF (Begeny et al., 2006; Chard et al., 2008; Francis et

al., 2005; Katz et al., 2008; Pressley et al., 2005; Riedel, 2007).

Studies have also correlated the DIBELS ORF to reading proficiency on state-

mandated assessments in Arizona (Wilson, 2005), Colorado (Shaw & Shaw, 2002;

Wood, 2006), Florida (Buck & Torgesen, 2003; Roehrig et al., 2008), North Carolina

(Barger, 2003), Ohio (Vander Meer et al., 2005), Oregon (Baker et al., 2008), and

Pennsylvania (Shapiro et al., 2008). In addition, Pressley et al. (2005) found a

correlational relationship between DIBELS ORF and the reading portion of the Terra

Nova assessment to a greater degree than the Qualitative Reading Inventory (Leslie &

Caldwell, 1995) or teachers’ predictions. Researchers (Baker et al., 2008; Chard et al.,

2008) have also correlated the DIBELS ORF probes to the Stanford Achievement Test

(Harcourt Brace Educational Measurement, 2002) and the Iowa Test of Basic Skills (Katz

et al., 2008). The results of these studies further indicate the validity of the DIBELS ORF

benchmarks.

However, other researchers have questioned the validity of the DIBELS ORF.

(Allington, 2009; Goodman, 2006; Pearson, 2006; Pressley et al., 2005; Samuels, 2006).

Goodman criticized DIBELS ORF for not predicting reading proficiency. Pressley et al.

and Riedel (2007) claimed that the DIBELS ORF mispredicts reading comprehension on

other assessments. Concerned about bias, Pressley et al. called for researchers other than

the developers of DIBELS or those associated with Reading First to perform research

regarding the relationship of DIBELS ORF and reading proficiency.

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In a study with 17,409 students, Roehrig et al. (2008) confirmed a significant

relationship between DIBELS ORF and reading proficiency as measured by the Florida

Comprehensive Assessment Test. However, the researchers recommended that the

developers of DIBELS ORF change the cut points. Roehrig et al. determined that

students reading less than 45 words correct per minute were at risk for unsatisfactory

performance on other measures of language and reading outcomes. The category of some

risk would consist of students reading between 46 and 75 words correct per minute.

Those reading more than 76 words correct per minute would be in the low risk category.

When Roehrig et al. evaluated the data using the cut scores, they found that 86% of the

students in the low-risk category, 62% of students in the some-risk category, and 20% of

the students in the at-risk category met grade level expectations at the end of the year.

Currently, the developers of the DIBELS categorize students who read 77 or more

words correct per minute at the beginning of Grade 3 as at low risk for not meeting grade

level expectations in other measures of language and reading outcomes. The developers

categorized students who read less than 53 words correct per minute as at high risk and

students who read between 53 and 76 words correct per minute as at some risk

(University of Oregon Center on Teaching and Learning, 2008). Based on these cut

scores, the University of Oregon Center on Teaching and Learning found that 90% of the

students in their low risk category, 34% of those in the some risk, and 3% of those in the

at-risk category met the goals expected of them at the end of Grade 3.

Roehrig et al. (2008) recommended “improved efficiency of classifications” (p.

353), and their educators screened students four times a year. The cut scores developed

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by the University of Oregon Center on Teaching and Learning (2008) used in the current

study are based on studies that benchmarked students three times a year. Consequently,

the Roehrig et al. middle-of-year benchmark goals are different from those discussed

above in section 3. However, the beginning of year benchmark goals from the Roehrig et

al. study and the DIBELS benchmark goals are comparable.

Similar to Roehrig et al. (2008), Jenkins et al. (2007), after conducting a meta-

analysis of universal screening studies, recommended a reexamination of the cut points.

They pointed out that although many studies have found the DIBELS ORF valid, a

change in cut points might improve the assessment. More precise cut points should allow

educators to more accurately identify students who are at risk for not meeting grade level

language arts and reading outcomes. Such improved information will allow educators to

provide interventions only for the students who need it the most (Jenkins et al., Roehrig

et al.).

Administration of the DIBELS ORF. In the administration of the Grade 3

middle-of-year DIBELS ORF, each student read three passages (Good & Kaminski,

2002b). Trained teachers individually administered the middle-of-year DIBELS ORF

benchmark, timing students as they read three passages: (a) "The Field Trip," (b) "Keiko

the Killer Whale," and (c) "Getting Email" (Good & Kaminski). The passages were

arranged in order from the easiest to the most difficult. The student read each passage for

1 minute while the teacher recorded substitutions and omissions as errors. In addition, if

the student hesitated longer than 3 seconds, the teacher read the word and recorded it as

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an error. Conversely, the teacher did not consider as errors words that the student self-

corrected within 3 seconds.

At the end of each passage, the teacher recorded the total number of words the

student read correctly in 1 minute as the oral reading fluency rate. This number was

determined by subtracting the number of errors from the total number of words the

student read. Then the teacher asked the student to retell what was read and recorded the

number of words the student used as the retell fluency. After the student read all three

passages, the teacher examined the oral reading fluency rate of the three passages and

recorded the mean rate as the middle-of-year oral reading fluency rate.

Scoring of the DIBELS ORF. The developers of DIBELS (Good & Kaminski,

2002b) categorized oral reading fluency rates as at risk, some risk, or low risk. On the

middle-of-year Grade 3 DIBELS ORF, students who read fewer than 66 words correct in

1 minute were considered at risk for poor language and reading outcomes. The

developers recommended that teachers provide these students with intensive intervention

for 60 minutes daily to target basic reading skills. Students who read between 67 and 91

correct words in 1 minute were considered at some risk for poor language and reading

outcomes. The developers recommended that teachers provide these students with

strategic intervention for 30 minutes daily to address their reading skills. Students who

read more than 92 words correctly in 1 minute were in the highest category and

considered at low risk for difficulties with language and reading outcomes (Good &

Kaminski). After administration and scoring of the DIBELS by the teachers, as described

above, student information was stored on a secured website.

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The developers of DIBELS (Good & Kaminski, 2002b) did not establish

benchmark goals for the retell fluency portion. However, they explained that students

should use at least 25% of the words read correctly in 1 minute when they retell what

they read. For example, students who read 100 words correctly in 1 minute should use at

least 25 words when they retell the passage they read. Although benchmark goals have

not been established, the developers recommended that students who use less than 25%

of the words they read to retell a passage are not considered developed readers (Good &

Kaminski).

TAKS

The purpose of the TAKS is to determine which students are reading proficiently

on their grade level. The TAKS was developed by teams of educational specialists with

consultation from many educators (TEA & Pearson, 2008). Advisory committees

comprised of teachers of each subject at each grade level worked with test developers and

TEA staff to review and assess the TAKS at several points in the development process.

The advisory committees were comprised of educators from throughout Texas and

represented diverse ethnicities (TEA & Pearson).

The first advisory committee convened to identify which student expectations in

the state curriculum TAKS should be tested (TEA & Pearson, 2008). After testing, the

specialists and TEA staff compiled an assessment of the outcome. Subsequently, a second

advisory committee met to examine whether the wording of the passages, questions, and

answer choices measured the assigned student expectations. Based on this committee’s

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report, test writers made the recommended changes, and field testing followed this

process.

The team at TEA and Pearson then analyzed the field testing results, and another

advisory committee met and evaluated the passages, questions, and answer choices to

identify any biases (TEA & Pearson, 2008). This committee also recommended

elimination of specific questions that appeared to reflect biases. In addition to these

processes, members of TEA and Pearson frequently consulted with national testing

experts during development of the TAKS. These detailed procedures resulted in an

assessment instrument that reflected the state curriculum and measured specific student

expectations.

Reliability and validity of the TAKS. Researchers have established both the

reliability and validity of the TAKS. The TEA and Pearson (2008) established reliability

and verified the internal consistency of the TAKS with the Kuder-Richardson Formula

20. With perfect reliability given the value of 1.0 (Gravetter & Wallnau, 2005),

reliabilities for dichotomously scored TAKS assessments ranged from .87 to .90,

respectively.

The TEA and Pearson (2008) also established concurrent validity of the TAKS.

Researchers use concurrent validity to establish how an assessment compares with other

similar assessments (Creswell, 2009). The TEA and Pearson conducted a grade

correlation study to determine how scores on the TAKS compared with performance in

respective grades or courses. The grade correlation study included all TAKS assessments

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from Grade 3 to the Exit Level. TEA and Pearson reported the outcome indicated high

concurrent validity:

Results indicated that a high percentage of students who pass the TAKS tests also

pass their related courses. Small percentages of students passed the TAKS tests

but did not pass their related courses, passed their related courses but did not pass

the TAKS tests, or failed to pass the TAKS test or their related courses. (p. 166)

Administration of the Grade 3 Reading TAKS. The Grade 3 Reading TAKS

was a criterion-referenced assessment that measured four objectives:

1. The student will demonstrate a basic understanding of culturally diverse

written texts.

2. The student will apply knowledge of literary elements to understand culturally

diverse written texts.

3. The student will use a variety of strategies to analyze culturally diverse

written texts.

4. The student will apply critical-thinking skills to analyze culturally diverse

written texts. (TEA, 2004, p. 4)

To measure these objectives, students completed testing booklets containing three

passages of between 500 and 700 words. The passages were accompanied by a total of 36

multiple-choice questions, with the number of questions for each passage varying

between 11 and 13. The TAKS was an untimed assessment, and students took as much

time as they need during one school day to answer the questions. Students answered the

questions directly in the test booklet.

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School administrators trained Grade 3 teachers to ensure the fidelity of testing

administration. The teachers administered the first Grade 3 Reading TAKS in March.

Students who failed this round (scored under 2100; see scoring explanation below) were

offered intensive intervention, developed by student success teams comprised of the

students’ parents, teachers, and administrators. Then the students were offered additional

opportunities in April and June to retake the Grade 3 Reading TAKS. Students unable to

score above 2100 after three attempts were retained in Grade 3 or provided intensive

intervention determined by the student support teams in Grade 4.

After administration of the TAKS by teachers, as described above, school

administrators collected students’ test booklets and kept them in a secure location. The

administrators then sent the booklets to the TEA staff in the headquarters in Austin,

Texas (TEA, 2009f). Staff members scored the booklets and returned the results to the

district. Educators who have access to the TAKS information signed oaths to maintain

confidentiality; those who break this confidentiality are subject to consequences that can

include loss of certification.

Scoring of the TAKS. The possible range of scores for the TAKS is from 1381 to

2630 (TEA, 2009b). Students were required to answer 24 questions correctly to obtain

the minimum expectancy scale score of 2100, indicating they were reading proficiently at

Grade 3 level. Students who answered 34 questions correctly received the commended

score of 2400, indicating they had demonstrated high academic achievement and

possessed a thorough understanding of the reading curriculum (TEA, 2006).

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Data Collection and Analysis

The data were collected and analyzed to test the null and alternative hypotheses

for this study. They were the following:

H0: There is no statistically significant relationship between students’ oral reading

fluency rates, as measured by the students’ middle-of-year DIBELS ORF rates, and their

reading proficiency, as measured by their scale scores on the Grade 3 Reading TAKS.

H1: There is a statistically significant relationship between students’ oral reading

fluency rates, as measured by the students’ middle-of-year DIBELS ORF rates, and their

reading proficiency, as measured by their scale scores on the Grade 3 Reading TAKS.

To test the null hypothesis, after appropriate permissions were granted, I collected

archival data from Grade 3 students’ DIBELS ORF and TAKS. The school district at the

research site screened all students in Grade 3 three times a year with DIBELS ORF

benchmarks, and I used the middle-of-year DIBELS ORF for the 2008-2009 school year.

All Grade 3 students in Texas were required to take the Reading TAKS during the spring

semester, and the researcher used this TAKS for the 2008-2009 school year.

Data Collection

First I sought permission to conduct the study from Walden University’s

Institutional Review Board (IRB), and permission was granted (IRB Approval Number

06-06-10-0334942). I requested and was granted permission from the superintendent of

the school district to use the Grade 3 students’ DIBELS ORF and TAKS scores for the

2008-2009 school year (Appendix A).

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For data collection of the DIBELS ORF scores, the students’ scores were stored

on a secure district website. Only individuals who signed an agreement of confidentiality

could obtain access to the site. The district involved in this study purchased and agreed to

the terms of confidentiality, allowing me access during the 2008-2009 school year. When

I became the district dyslexia teacher in 2009, I obtained access to the DIBEL’s ORF

rates for all the students in the district. The district superintendent granted me permission

to use these data for the study (Appendices A and B).

For data collection of the TAKS scores, the TEA sent reports to the district listing

individual test scores. After return of the students’ TAKS scores by the TEA to the

district, school administrators kept students’ individual information confidential,

accessible only to the students, their parents, and teachers. I had access to these data to

carry out my duties as the district dyslexia teacher. In addition, the district superintendent

granted me approval to use the data. I used the TAKS scores in the aggregate for the

2008-2009 school year.

With access to the school records, I used the Grade 3 students’ middle-of-year

DIBELS ORF rates and the end-of-year TAKS scale scores. To preserve students’

anonymity, I assigned code numbers to all students’ scores instead of using their names.

Then I entered the DIBELS benchmark rates and TAKS scale scores into the chosen

software program.

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Data Analysis

I employed SPSS, version 17.0 (SPSS, 2009) for data analysis. SPSS is a widely

used statistical software package in educational research (Creswell, 2009). Following the

SPSS instructions, I entered the data into the computer.

I performed a Pearson correlation to answer the research question. Pearson

correlations “measure and describe a relationship between two variables” (Gravetter &

Wallnau, 2005, p. 412). I entered into the SPSS program the DIBELS ORF scores for

each student as the independent variable and the TAKS scores for each student as the

dependent variable. The level of significance was .05, a level widely used in educational

research (Creswell, 2009). The resulting statistic indicated whether a significant

relationship existed for Grade 3 students between their DIBELS ORF scores and TAKS

scores for the 2008-2009 school year.

With regard to the direction of the relationship, a correlation coefficient (Pearson

r) of 0 would indicate no linear relationship between two variables. A positive correlation

of 1.0 would indicate the maximum strong relationship, in which the scores of the two

variables increase together. A negative correlation of -1.0 would indicate the maximum

weak relationship, in which the scores of the two variables decrease together (Creswell,

2008; Gravetter & Wallnau, 2005). With regard to the strength of the relationship,

whether negative or positive as represented by Pearson’s r, value of generally .20 to .35

indicate a slight relationship, values of .35 to .65 indicate a somewhat strong relationship,

values of .66 to .85 indicate a very good relationship, and values of .86 and above (to the

perfect 1.0) indicate an excellent relationship (Creswell, 2008).

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Researcher’s Role

During the 2008-2009 school year, I was a teacher of Grade 2 at the research site

of this study. In this position, I volunteered to tutor four dyslexic Grade 3 students, the

only ones identified as such in the third grade. In March 2009, I administered the Grade 3

Reading TAKS to these students. As of the 2009-2010 school year, I became the district

dyslexia teacher. In this capacity, I previewed all the assessment data from the students

on the campus and recommended which students needed additional reading instruction. I

teach some of these students in small groups, addressing their dyslexic tendencies. In

addition, when principals in the district request dyslexic assessments, I individually

administer a battery of assessments and report the information to a committee that

decides whether the student is dyslexic. I provide direct, explicit, systematic, sequential

instruction in all aspects of reading to most of the dyslexic students in the district.

Because I was a second-grade teacher during the 2008-2009 school year, to

remain neutral and removed from the testing administration, I did not administer any of

the DIBELS benchmarks. However, as described above, I worked with four identified

dyslexic students in an afterschool tutorial program and administered the Reading TAKS

to them. Because of my involvement in the administration of their TAKS, I did not

include the data from these four students in this study.

Protection of Participants’ Rights

I protected the rights of participants in several ways, first seeking and obtaining

approval for the study from Walden University’s IRB. The district granted me permission

to use the archival data of Grade 3 students’ DIBELS ORF and TAKS scores from the

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2008-2009 school year (Appendices A and B). In addition, the Dynamic Measurement

Group granted me permission to use DIBELS in the study (Appendix C). The TEA

granted me copyright permission to use the 2009 Grade 3 Reading TAKS in this study

with the understanding that the TEA and Pearson Corporation are the owners of the

TAKS and with the understanding that individual student data were to be kept

confidential (Appendix D).

I did not include the children’s names or other information that could identify the

children in any reports of the study, and individual children’s rates and scores were not

reported. All oral reading fluency rates and scale scores were assigned code numbers and

were reported in group form only. Letters of consent or assent were not needed for the

study participants because the data were archival. The DIBELS ORF and TAKS are

routine assessments all students are required to take.

Summary

The purpose of this nonexperimental, quantitative study was to determine whether

the middle-of-year DIBELS ORF rates correlated with the scale scores of the Grade 3

Reading TAKS for students in a West Texas school district during 2008-2009 school

year. I used a quantitative correlational design to determine whether a statistically

significant relationship (p >.05) existed between the independent variable, the DIBELS

ORF rates, and the dependent variable, the scale scores of the Grade 3 Reading TAKS. A

nonprobability convenience sample of 155 Grade 3 students participated in the study, and

their demographic composition was representative of Grade 3 students in Texas overall.

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In this retrospective study, archival records were used for two instruments, the

DIBELS ORF and the TAKS for Grade 3 students. Both instruments have been reported

with good reliability and validity in many studies. Data collection took place with the

permission of Walden University’s IRB and the district superintendent. The

superintendent provided a letter of cooperation and data use agreement for my use of

archival data (Appendices A and B), and I accessed archival records of Grade 3 students’

DIBELS ORF rates and TAKS scores for the 2008-2009 school year. In addition, the

Dynamic Measurement Group granted me permission to use DIBELS (Appendix C). The

TEA granted me copyright permission to use the 2009 Grade 3 Reading TAKS with the

understanding that the TEA and Pearson Corporation were the owners of the TAKS and

that individual student information would be kept confidential (Appendix D). Data

analysis took place with the SPSS software package, and I used Pearson correlation to

test the null hypothesis that there is no statistically significant relationship (p >.05)

between Grade 3 students’ middle-of-year DIBELS ORF rates and TAKS scores.

Although I taught second grade at the research site school, I have not taught third

grade, and I am presently the district dyslexia teacher. My professional role did not

compromise data collection or analysis. Protection of participants was assured, and

potential harm to participants was minimal. Data were coded by numbers only, and

students’ names did not appear. Further, results were presented solely in group form. I

report the results of the study in section 4 and discuss the findings in section 5.

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Section 4: Results of the Study

Introduction

The purpose of this quantitative, retrospective study was to determine if a

statistically significant relationship (p < .05) existed between students’ oral reading

fluency and reading proficiency. Pearson correlation analysis was used to examine 155

Grade 3 students’ oral reading fluency rates and reading proficiency scores in a West

Texas school district. The data were analyzed to investigate whether a significant

relationship existed between the students’ middle-of-year Grade 3 DIBELS ORF rates

and their scale scores on the Grade 3 Reading TAKS during the 2008-2009 school year.

Research Question and Hypothesis

The following research question guided this study: Is there a statistically

significant relationship between Grade 3 students’ oral reading fluency rates and their

reading proficiency? From this question, the following null and alternative hypotheses

were formulated:

H0: There is no statistically significant relationship between students’ oral reading

fluency rates, as measured by the students’ middle-of-year DIBELS ORF rates, and their

reading proficiency, as measured by their scale scores on the Grade 3 Reading TAKS for

the 2008-2009 school year.

H1: There is a statistically significant relationship between students’ oral reading

fluency rates, as measured by the students’ middle-of-year DIBELS ORF rates, and their

reading proficiency, as measured by their scale scores on the Grade 3 Reading TAKS for

the 2008-2009 school year.

78

Research Tools

The dependent variable, oral reading fluency, was measured by the middle-of-

year 2009 Grade 3 DIBELS ORF benchmark rates. The independent variable, reading

proficiency, was measured by the scale score on the 2009 Grade 3 Reading TAKS. In this

section, I describe how these research tools were used in this study.

The Grade 3 teachers in the small West Texas school district were trained in the

administration of DIBELS. During January 2009, they listened to each student read three

passages: (a) "The Field Trip," (b) "Keiko the Killer Whale," and (c) "Getting Email"

(Good & Kaminski, 2002b). As the student read a passage for exactly 1 minute, the

teacher recorded the number of words read. The teacher marked substitutions and

omissions as errors and subtracted the number of errors made from the total number of

words read to ascertain the words read correctly in 1 minute. After the student read the

passage, the teacher asked the student to retell what was read (Good & Kaminski).

The teacher used the same procedure for all three passages and recorded the

median oral reading fluency score as the student’s middle-of-year DIBELS ORF

benchmark rate. These rates were stored on a secure website to which only authorized

personnel had access. As district dyslexia teacher, I was authorized to view the rates

(Appendix A).

The Grade 3 Reading TAKS was administered according to the guidelines set by

the TEA in compliance with the NCLB (2002) mandates for determining adequate yearly

progress. The teachers were trained to administer the Grade 3 Reading TAKS before

March 2009. The students were given 1 school day to read three passages and answer 36

79

questions. Upon completion, the booklets were securely transported to Austin for scoring

by the TEA, and the scale scores were electronically sent back to the district. The district

stored the scale scores on a secured website accessible only by authorized personnel. As

the district dyslexia teacher, I had authorized access to the scale scores

(Appendix A).

The district superintendent signed a letter of cooperation and a data use agreement

(Appendices A and B). These gave me permission to use the middle-of-year DIBELS

benchmark rates and the Grade 3 Reading TAKS scale scores from the 2008-2009 school

year. In addition, Dynamic Measurement Group granted me permission to use the

DIBELS (Appendix C). The TEA granted me copyright permission with the

understanding that the TEA and Pearson Corporation are the owners of TAKS and no

individual student information would be used in the study (Appendix D).

Data were collected with the following procedure. On an Excel spreadsheet, I

matched the DIBELS ORF benchmark rates and the Grade 3 Reading TAKS scale scores

for each individual student. Although 160 students were enrolled in the district’s Grade 3

during the 2008-2009 school year, the data for four students were not included because I

had administered the TAKS to them. Additionally, one student was excluded because no

score was available for the Grade 3 Reading TAKS. Thus, the oral reading fluency rates

and scale scores of the 155 remaining students were used in the study.

The DIBELS ORF benchmark rates and Grade 3 Reading TAKS scale scores

were imported into SPSS 17.0. To verify the accuracy of data entry, I compared the sum

of the benchmark rates on the Excel spreadsheet to the sum of the benchmark rates

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entered into SPSS 17.0. The same procedure was followed with the Grade 3 Reading

TAKS scale scores. To verify accuracy and obtain the means and standard deviations for

both variables, I used an Excel spreadsheet to compute the formula for the Pearson

correlation and obtained the same results.

Data Analysis

A Pearson correlation analysis was conducted to determine if a statistically

significant relationship (p < .05) existed between the middle-of-Grade 3 DIBELS ORF

rates and the scale scores from the Grade 3 Reading TAKS for the sample of 155

students. The bivariate Pearson correlation analysis was conducted with the two

variables, with a one-tailed test of significance. Table 2 shows the results.

Table 2

Correlation of DIBELS ORF Rates and TAKS Scores for Grade 3 Students

Measure

1

2

Mean

Standard Deviation

1. DIBELS

ORF

---

.655*

86.9

33

2. TAKS

.655*

---

2268

187

*p < .01.

As Table 2 shows, for the sample of 155 students, the mean for DIBELS ORF

was 86.9 (SD = 33), and the mean for the TAKS was 2268 (SD = 187). A statistically

significant correlation was found, r = .66 (p = .01), between the students’ DIBELS ORF

81

rates and TAKS scale scores for the 2008-2009 school year. This correlation was strong

enough to reject the null hypothesis and was in the very good range (.66-.85; Creswell,

2008). This correlation indicated a linear relationship between the two variables. Students

who had a high DIBELS ORF rate tended to have a high Grade 3 Reading TAKS scale

score and vice versa (Gravetter & Wallnau, 2005). Thus, Null Hypothesis 1 was rejected.

A statistically significant relationship was found between students’ oral reading fluency

rates, as measured by the students’ middle-of-year DIBELS ORF rates, and their reading

proficiency, as measured by their scale scores on the Grade 3 Reading TAKS for the

2008-2009 school year.

Although the stated level of significance was p < .05, the finding of p < .01 is a

stronger level of significance and also results in rejection of the null hypothesis. For

example, in a study with 100 participants, if r were less than .16, I would reject the null

hypothesis if the alpha level for the one-tailed Pearson correlation was .05. However, if r

were less than .23, I would reject the null hypothesis if the alpha level for the one-tailed

Pearson correlation was .01 (Gravetter & Wallnau, 2005).

The study findings confirmed LaBerge and Samuels’ (1974) proposal regarding

fluency in the automaticity theory. LaBerge and Samuels (2006) posited that when

readers are able to read fluently, they have more attention to focus on other areas, such as

reading proficiency. The present results indicate a relationship between oral reading

fluency, as measured by the DIBELS ORF rates and reading proficiency, as measured by

the scale score on the Grade 3 Reading TAKS. Thus, the results support H1: There was a

statistically significant relationship between students’ oral reading fluency rates, as

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measured by middle-of-year DIBELS ORF rates, and their reading proficiency, as

measured by scale scores on the Grade 3 Reading TAKS for the 2008-2009 school year.

In addition, I investigated how the students in each of the DIBELS ORF

categories performed on the Texas Grade 3 Reading TAKS, although this aspect was not

part of the study purpose. However, this investigation is similar to Buck and Torgesen’s

(2003) classification of information in their correlational study comparing DIBELS ORF

rates to performance on the Florida Comprehensive Assessment Test (FCAT) to show

how the students in each of the DIBELS ORF categories performed on the FCAT.

To understand the present results, the ranges for the sample are reported for both

the DIBELS ORF and TAKS. Ranges are reported in relation to the cut points and

performance categories of the DIBELS ORF and TAKS. Table 3 displays these values.

Table 3

Ranges and Categorization Cut Points of DIBELS ORF and Grade 3 TAKS

DIBELS ORF

Possible Range

Sample Range

At risk

Some risk

Low risk

0 – 92+ 3-169

-67 67-91 92+

TAKS

Possible Range

Sample Range

Not proficient

Proficient

Commended

1381-2630

1835-2630

-2100

2100+

2400+

Note. All DIBELS ORF scores are expressed in words read correctly per minute.

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As Table 3 shows, for the present sample, the DIBELS ORF scores ranged from 3

words read correctly per minute (wcpm) to 169 wcpm. As mentioned in section 3, those

students whose oral reading fluency rates are less than 67 wcpm are considered to be at

risk for poor learning outcomes on other reading and language arts assessments. Students

whose oral reading fluency rates are between 67 and 91 wcpm are considered to be at

some risk, and students whose oral reading fluency rates are 92 or more wcpm are

considered at the lowest risk for poor outcomes on other reading and language arts

assessments. Table 3 shows that the range of Grade 3 Reading TAKS scale scores in this

sample of 155 students was 1835-2630. As stated in section 3, students are expected to

have a scale score of 2100 or more to be considered proficient. Students with scale scores

of 2400 or greater receive a rating of commended.

With this summary of the ranges and cut score categorizations of the DIBELS

ORF and TAKS, the results of the study sample per category can be better understood.

These were calculated with frequencies and percentages. Table 4 displays the Grade 3

DIBELS ORF and TAKS performance of the study sample.

As Table 4 shows, of the 155 students, 44 were considered to be at risk. About

half of the at-risk students (52%) failed the Grade 3 Reading TAKS with scale scores less

than 2100. About half (48%) scored proficient on the assessment. Five (11%) of the at-

risk students scored in the commended range.

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Table 4

Comparison of Students’ Performance by Categories for DIBELS ORF and Grade 3

Reading TAKS

Number of Students

DIBELS ORF Categories

TAKS

Not proficient

Performance Proficient

Categories Commended

44

At risk

23 (52%)

21 (48%)

5 (11%)

47

Some risk

9 (19%)

39 (79%)

14 (30%)

64

Low risk

0 (0%)

64 (100%)

41 (64%)

155 Total

32 (21%)

123 (79%) 60 (39%)

As Table 4 also shows, the 47 students in the some-risk category performed much

better than the 44 students in the at-risk category on the Grade 3 Reading TAKS. Only

19% of the some-risk students did not score proficient on the Grade 3 Reading TAKS,

and 79% scored proficient. About three times as many of the some-risk students (30%)

scored in the commended range compared to those in the at-risk category (11%). In the

low-risk category, all (100%) of the 64 students passed the Grade 3 Reading TAKS, and

over half (64%) scored in the commended range.

The results as shown in Table 4 confirmed the values used by the developers of

DIBELS ORF to define their categories (University of Oregon Center in Teaching and

Learning, 2008). Such information as that in Table 4 could additionally help educators

and reading specialists identify which students could be at risk of failing the Grade 3

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Reading TAKS before it is administered. This information could aid educators especially

in benchmarking, setting oral reading fluency goals for students, and monitoring their

progress (Baker et al., 2008; Buck & Torgesen, 2003; Roehrig et al., 2008).

The results of the current study also confirmed the findings of Hasbrouck and

Tindal’s (2006) oral reading fluency norms. Hasbrouck and Tindal found that Grade 3

students at the 50th percentile at the middle of the year were reading 92 wcpm. They

recommended that students who read less than 10 wcpm of the 50th percentile (82 wcpm)

be considered for intervention program. In the current study, all but 2 of the 86 students

(98%) who read 82 or more wcpm scored proficient on the Grade 3 Reading TAKS. One

hundred percent of the students who read 84 or more wcpm scored proficient. These

findings seem to support Hasbrouck and Tindal’s research.

Although the study results indicated a strong positive correlation between

students’ DIBELS ORF rates and Grade 3 Reading TAKS scores, the findings

demonstrate a relationship between oral reading fluency rates and reading proficiency.

They do not prove a causal relationship (Gravetter & Wallanau, 2005). In this study, the

significant linear relationship indicated that when oral reading fluency rates increased, the

Grade 3 Reading TAKS scale score tended to increase, with the converse also true. The

results do not, however, prove that high oral reading fluency rates cause high scores on

the Grade 3 Reading TAKS. Other variables could be contributing factors, such as

comprehension strategies students may use to answer questions on the Grade 3 Reading

TAKS, and such strategies could affect their performance.

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This caution is supported by the study results. They do not prove that good oral

reading fluency always results in proficient reading. For example, 5 of the 44 at-risk

students not only scored proficient on the Grade 3 Reading TAKS but scored in the

commended range. Similarly, Buck and Torgesen (2003) reported that 42 of the 220

students in their high-risk category scored adequate on the FCAT. Another factor that

could affect reading proficiency is students’ knowledge of the English language. As

noted earlier, Samuels (2006) documented cases in which Hmong students whose second

language was English could fluently read English but could not read proficiently.

The use of compensational strategies could also have an effect on students with

low fluency rates but score proficient on reading assessments. In the current study, 21

(48%) of the at-risk students scored proficient on the Grade 3 Reading TAKS. In fact, 5

(11%) scored commended. In the some-risk category, 38 (79%) scored in the proficient

range and 14 (30%) scored in the commended range. These scores do not indicate that

students with low fluency rates cannot comprehend text but rather that they find it more

difficult to read proficiently.

Walczyk and Griffith-Ross (2007) reported that struggling readers in Grades 3, 5,

and 7 can compensate by applying strategies such as pausing, slowing down, reading

aloud, and looking back in the text. The Grade 3 students read at a constant rate and were

more affected by constraints, such as time pressure, than the Grade 7 students in the

study. Walczyk and Griffith-Ross conjectured that the Grade 3 students read at a slower

rate and were more likely to take the time to sound out words they did not know or use

87

context clues to read than the Grade 7 students. By using these skills, the struggling

readers in Grade 3 were able to comprehend.

Walczyk and Griffith-Ross’s (2007) conclusions may explain why 48% of the at-

risk students in the present study and 79% of the some-risk students were able to score

proficient despite their low fluency rates. Although the use of compensation strategies

may account for struggling readers’ ability to score in the proficient range, it should be

noted that the faster students read, the higher their chances of scoring proficient (at-risk

students, 48%; some-risk students, 79%; 100% low-risk students). In addition, the faster

students read, the higher their chance of scoring commended (at-risk students, 11%;

some-risk students 30%; low-risk students, 64%).

Summary

The purpose of this study was to determine if a statistically significant

relationship existed between oral reading fluency and reading proficiency for Grade 3

students in a West Texas school district. I used the following research question to guide

the study: Is there a statistically significant relationship between Grade 3 students’ oral

reading fluency rates and their reading proficiency? The resulting null hypothesis was as

follows: There is no statistically significant relationship between students’ oral reading

fluency rates, as measured by the students’ middle-of-year DIBELS ORF rates, and their

reading proficiency, as measured by their scale scores on the Grade 3 Reading TAKS for

the 2008-2009 school year.

To test the hypothesis, I matched the students’ DIBELS ORF rate with their

Grade 3 Reading TAKS scale scores on an Excel spreadsheet and then imported them

88

into SPSS 17.0 (SPSS, 2009), after which a Pearson correlational analysis was

performed. Results indicated a strong significant correlational relationship (r = .66,

p < .01) between oral reading fluency and reading proficiency. Thus, the null hypothesis

was rejected. The study results confirmed LaBerge and Samuels’ (1974) proposal in the

automaticity theory: Students who read fluently can devote their attention to other

reading skills, such as comprehension.

This research indicated a linear relationship between oral reading fluency and

reading proficiency; as students’ oral reading fluency rates increased, reading proficiency

also tended to increase. Although a positive correlational relationship was found, this

result did not prove that oral reading fluency rates cause reading proficiency. Other

factors such as comprehension strategies and knowledge of English as a second language

may affect reading proficiency. Nevertheless, the strong positive correlation found for

Grade 3 students’ DIBELS ORF scores and Reading TAKS performance is important for

interpretation of the findings in terms of practical applications and implications for social

change. In section 5, I discuss these issues, as well as recommendations for action and

further study.

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Section 5: Discussion, Conclusions, and Recommendations

Overview

The purpose of this study was to determine if a statistically significant (p < .05)

relationship existed between oral reading fluency and reading proficiency. The middle-

of-Grade 3 DIBELS ORF was used to measure oral reading fluency and the Grade 3

Reading TAKS scale scores was used to measure reading proficiency with 155 students

in a West Texas school district. In this section, the findings are reviewed and the

correlations found in this study are compared with the correlations of nine other similar

previous studies. The implications for social change are discussed and recommendations

are made both for future actions and further studies.

Interpretation of Findings

Based on the results of the study, I concluded that for Grade 3 students, oral

reading fluency rates are significantly positively related to their performance on state-

mandated assessments. These findings specific to students in Texas supported those of

previous studies correlating state-mandated assessments to the DIBELS ORF in other

states (Baker et al., 2008; Barger, 2003; Roehrig et al., 2008; Shapiro et al., 2008; Vander

Meer et al., 2005; Wilson, 2005; Wood, 2006). For ease of comparison, Table 5 shows

the other studies by state, grade levels, number of students in the sample, and the

correlation statistic. Some researchers studied more than one grade level.

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Table 5

Studies Correlating State-Mandated Assessments to the DIBELS ORF

Authors

State

assessment

Grade level

Number in

sample

Correlation

found

Baker et al., 2008

Oregon State

Reading Assessment

3

4,696

.58 to .68

Buck & Torgesen, 2003

Florida Comprehensive

Assessment Test

3 1,102 .70

Roehrig et al., 2008

Florida

Comprehensive Assessment

Test

3

5,207

.70 -.71

moderately strong

Shapiro et al., 2008

Pennsylvania System of

School Assessments

3 401 .67

Shapiro et al., 2008

Pennsylvania System of

School Assessments

4 394 .64

Shapiro et al., 2008

Pennsylvania System of

School Assessments

5 205 .73 moderately

strong

Shaw & Shaw, 2002

Colorado State Assessment

Program

3 52 .80 Strong

(continued)

91

Authors

State

assessment

Grade level

Number in

sample

Correlation

found

Wilson, 2005

Arizona

Instrument to Measure Standards

3

241

.74 moderately

strong

Wood, 2006 Colorado Student

Assessment Program

3 82 .70 moderately

strong

Wood, 2006 Colorado Student

Assessment Program

4 101 .67

Wood, 2006 Colorado Student

Assessment Program

5 98 .75 moderately

strong

The current study, in relation to these studies, compared the DIBELS ORF and

the TAKS with 155 Grade 3 students, and the results of Pearson correlation showed a

significance level of .66 (p < .05). These results confirmed the findings of the nine other

studies, as Table 5 illustrates, all of which reported significant correlations between

DIBELS ORF and state-mandated assessments. The lowest ranges were .58 to .68 (Baker

et al., 2008, .58 to .68; Shapiro et al., 2008, Grade 3 .67, Grade 4 .64; Vander Meer et al.,

2005, .65; Wood, 2006, Grade 4, .67).

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Some of the researchers found higher correlations. Moderately strong

correlations, .70-.75, were found by Wood (2006, Grade 3, .70, Grade 5, .75), Barger

(2003, .73), and Shapiro et al. (2008, .73). The strongest correlation was found by Shaw

and Shaw (2002), 80.

In the context of these studies, the present results confirmed a significant

relationship between the Texas state-mandated assessments and the DIBELS ORF.

However, the present correlation was lower, .66, than those reporting moderate or strong

correlations (Barger, 2003; Shapiro et al., 2008; Shaw & Shaw, 2002; Wilson, 2005;

Wood, 2006). Several reasons may be cited for this difference.

There were 155 students in the current sample. Several of the studies with higher

correlations had smaller samples. The smallest sample of 38 was that of Barger (2003),

with a moderately strong correlation of .73. Shaw and Shaw (2002), with a sample of 52

students, had a strong correlation, the highest correlation of all the studies (.80). Two of

the grade levels in Wood (2006) had smaller sampler sizes, for the Grade 3 sample 82

students and a moderately strong correlation of .70; and for the Grade 5 sample 98

students and a moderately strong correlation of .75. Wood’s Grade 4 sample with a

population size similar to the one in this study (101) also had a similar significant

correlation (.67).

The other previous studies with correlations closest to the one found in the present

study had larger sample sizes. In the Vander Meer et al. (2005) study, the sample was 318

students, with a .65 correlation. Likewise, in the Shapiro et al. (2008) study, the Grade 3

sample was 401 and a similar significant correlation was found, .67. One of the Reading

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First studies, that of Baker et al. (2008), had a large sample (4,696) and found significant

correlations ranging from .58 to .68.

Demographics could also have been a factor that contributed to varying

correlation values. The student sample used in the Wood (2006) study was mostly White.

Wood recommended replication with samples that represented other demographic

characteristics. The studies conducted with Reading First schools (Baker et al., 2008;

Buck & Torgesen, 2003; Roehrig et al., 2008; Wilson, 2005) had large numbers of

students from low socioeconomic backgrounds. Baker et al. recommended other studies

with samples of varying socioeconomic backgrounds to rule out poverty as a factor. The

present sample of the district Grade 3 students had approximately half Hispanic, a third

White, and half economically disadvantaged students. However, these characteristics

reflected all Grade 3 students in Texas (Table 1).

Another factor that may explain differences in study results was the rigor and

degree of testing higher-level thinking skills of the assessment used to measure reading

proficiency. Although all state-mandated assessments are designed to assess reading

proficiency as required by the NCLB (2002) legislation, they differ from state to state and

from grade to grade. State curricula determine how reading proficiency is defined and

assessed. For example, Wilson (2005) studied the relationship between DIBELS ORF

and performance on the Arizona Instrument to Measure Standards. With his sample of

241 students, he reported a moderately strong correlation (.74). However, in Wilson’s

discussion of limitations, he recommended that the study be repeated after Arizona began

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using the next reading assessment designed to assess higher reading comprehension

skills.

In the study by Baker et al. (2008), when the SAT-10 was used to measure

reading proficiency, the researchers found a stronger correlation (.63 to .80) in their

Grade 2 sample than in their Grade 3 sample (.58 to .68), in which the Oregon State

Reading Assessment was used to measure reading proficiency. The authors speculated

that the rigor of the two reading proficiency assessments might have affected the

correlational differences. Fuchs et al. (2001) recommended additional studies beyond

Grade 3 that measured higher-level thinking. In the exploration by Applegate et al.

(2009) of state-mandated reading assessments in several states, the researchers observed

that the TAKS contained questions which required higher-level thinking than many of the

assessments in other states.

Another factor influencing results may be whether the assessment is timed. In

Texas, students are allowed as long as needed in 1 school day to answer the questions on

the Grade 3 Reading TAKS. However, in the North Carolina study (Barger, 2003), in

which a moderately strong correlation (.73) was found, students had 115 minutes to

answer 56 questions. Walczyk and Griffith-Ross (2007) found that Grade 3 struggling

readers were negatively affected by time constraints because they were struggling to

decode words. In the same study, however, time constraints positively affected Grade 7

struggling readers. These readers seemed to be more engaged when the reading was

timed, in contrast to untimed routine reading assignments. Time constraints should be

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considered in comparisons of studies and future studies of oral reading fluency rates and

reading proficiency.

All of these correlational studies used DIBELS ORF to measure oral reading

fluency and compared the DIBELS ORF to a state-mandated assessment, but not all these

studies used the same DIBELS ORF benchmark. DIBELS ORF benchmarks are

administered three or four times a year. In the current study, I found a correlation of .66

between the middle-of-year DIBELS ORF benchmark administered in January 2009 and

the Grade 3 Reading TAKS administered in March 2009. Barger (2003) found a

moderately strong correlation (.73) between the North Carolina End-of-Grade 3

assessment and the DIBELS ORF benchmark administered 1 week prior to the state-

mandated assessment. Vander Meer et al. (2005) found a .65 correlation when they

compared the end-of-Grade 3 DIBELS ORF to performance on the Ohio Proficiency Test

administered in Grade 4. Baker et al. (2008) took a more comprehensive approach by

determining the correlational relationship between each of the DIBELS ORF benchmarks

over a 2-year period and the Oregon State Reading Assessment at the end of Grade 3

(beginning of Grade 2, .58; middle of Grade 2, .63; end of Grade 2, .63; beginning of

Grade 3, .65; middle of Grade 3, .68; end of Grade 3; .67). Thus, the varying time periods

between the administration of the DIBELS ORF and the administration of state-mandated

assessments could influence the different strengths of correlational values.

Several factors could explain the varying correlational values between this study

and the other nine studies conducted in seven other states. The samples sizes varied from

38 (Barger, 2003) to 5,207 (Roehrig et al., 2008). The demographic representation

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differed widely. The Wood (2006) sample consisted of mostly White students and the

studies conducted in Reading First schools (Baker et al., 2008; Buck & Torgesen, 2003;

Roehrig et al., 2008; Wilson, 2005) had wide socioeconomic representations. Another

factor is the rigor of the state-mandated assessments. Although all are designed to follow

the stringent standards of NCLB (2002), the assessments differ in how reading

proficiency is defined and assessed. A salient factor is whether the assessment is timed; a

discrepancy can affect correlational relationships. Additionally, the time between the

administration of the DIBELS ORF benchmark and administration of state-mandated

assessments can account for varying correlational levels.

Based on the present study findings, several practical applications for

administrators, teachers, parents, and students can be suggested. Based on longitudinal

studies, such as those by Baker et al. (2008) and Vander Meer et al. (2005),

administrators can use oral reading fluency rates to predict which students are at risk for

failing a state-mandated assessment in years prior to the year of assessment

administration. According to Baker et al., oral reading fluency rates at the beginning of

Grade 2 showed a significant correlation (.63) to the state-mandated assessment that was

administered almost 2 years later. Vander Meer et al. showed similar results (.65)

between the end-of-Grade 3 DIBELS ORF and the state-mandated assessment

administered in Grade 4. Wood (2006) demonstrated that a significant correlational

relationship continues to exist between oral reading fluency and reading proficiency

through Grade 5 (Grade 3, .70; Grade 4, .67; Grade 5, .75). As Wood recommended,

administrators could use such information to identify in an early and timely manner

97

students at risk for failing state-mandated assessments and implement intervention

programs to address the needs of at-risk readers before they fail.

Teachers can benefit from the study results showing that oral reading fluency is

significantly related to reading proficiency. Hasbrouck and Tindal (2006) have developed

oral reading fluency norms that identify national percentiles for the beginning, middle,

and end of Grades 1 to 8. For example, the 50th percentile for Grade 3 students at the

middle of the year is 92 wcpm. According to Hasbrouck and Tindal’s instructions, Grade

3 students who are reading less than 82 wcpm should be receiving interventions. In the

current study, 84 of the 86 (98%) students who read more than 82 wcpm on the middle of

year DIBELS ORF scored proficient on the Grade 3 Reading TAKS. Of the remaining 69

students, 43% failed the Grade 3 Reading TAKS.

Teachers could use the information from these data. Students reading within 10

wcpm of the 50th percentile of Hasbrouck and Tindal’s (2006) oral reading fluency

norms have a very good chance of passing the state-mandated reading assessment.

Hasbrouck and Tindal’s oral reading fluency norms were similar to the cut points

established by DIBELS for the at-risk, some-risk, and low-risk categories (University of

Oregon Center in Teaching and Learning, 2008).

Researchers in several of the other state studies (Barger, 2003; Baker et al., 2008;

Buck & Torgesen, 2003; Roehrig et al., 2008; Shaw & Shaw, 2002) confirmed the

reliability of the DIBELS ORF categories in accurately identifying at-risk readers. Thus,

regardless of the grade level, teachers can use the DIBELS ORF benchmarks and

progress monitoring probes to set goals to ensure that as many children as possible score

98

within 10 wcpm of the 50th percentile of Hasbrouck and Tindal’s (2006) oral reading

fluency norms or in the low-risk category of DIBELS (University of Oregon Center in

Teaching and Learning, 2008).

Parents can benefit from the present study results as well. Once parents realize the

importance of their children’s ability to read fluently in the current as well as subsequent

grades, parents can be trained to work with their children at home. For example, teachers

can train parents how to administer a 1-minute oral reading fluency probe in parent-

teacher conferences or through written instructions. Schools can also present meetings for

training purposes. Rasinski and Stevenson (2005) demonstrated that positive changes in

students’ oral reading fluency resulted from parents working with their children daily at

home.

Students can also be encouraged by the present study results. Morgan and

Sideridis (2006) found that when students set goals, they were motivated to improve their

oral reading fluency scores. Once students understand the importance of oral reading

fluency and its relationship to their success on state-mandated assessments, they can set

their own goals to read more fluently. Students can be made aware of a variety of

strategies, such as repeatedly reading text (Begeny et al., 2006; Hiebert, 2005; Hudson et

al., 2005; Rasinski, 2006; Therrien et al., 2006; Therrien & Kubina, 2007); reading a

wide variety of texts (Kuhn, 2006); reading with a partner (Nes Ferrera, 2005); and

participating in reader’s theatre (Young & Rasinski, 2009).

99

Implications for Social Change

With the implementation of the NCLB (2002) legislation, schools have been

charged with demonstration of adequate yearly progress. Each year a significant number

of students must pass the state-mandated assessment. For example, for schools and

districts to meet the NCLB requirements for academic acceptability in 2009, the schools

and districts had to have certain percentages of students in each content area scoring

proficient on the state assessments: 70% in reading/English language arts, writing, and

social studies assessments; 55% in mathematics; and 50% in science. Four levels were

possible: Academically Unacceptable, Academically Acceptable, Recognized, and

Exemplary. For schools and districts to receive a designation of Recognized , 75% of

students in all subjects had to score proficient; for schools and districts to be considered

Exemplary, 90% of students in all subjects had to score proficient (TEA, 2009f).

To meet such goals, elementary educators need to be able to identify struggling

readers before they take assessments such as the Grade 3 Reading TAKS so that

interventions to improve their academic skills can take place. For elementary educators in

Texas, the findings of the present study provide useful information with which to identify

struggling readers. Once they are identified, interventions targeting basic literacy skills,

improvement of oral reading fluency skills, and teaching of decoding strategies can be

provided (Jenkins et al., 2007).

This identification of struggling readers is important for several reasons. In

kindergarten through Grade 3, students learn to read (Ehri, 2005). As they progress

through later years of elementary school, they make the transition to reading to learn in

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other academic areas (Musti-Rao et al., 2009). When struggling readers are identified and

given remediation, the possibilities of their passing state-mandated reading assessments

in Grade 3 and above improve, as well as their success in other academic areas (Ehri,

2005; Shapiro et al., 2008). If struggling readers are able to improve their reading skills

by the end of Grade 3, they will more likely close the academic gap with their peers who

are more proficient in reading (Simmons et al., 2008). Furthermore, if the needs of

struggling readers are not met by the end of Grade 3, they are more likely to fall farther

and farther behind their more proficient peers (Morgan et al., 2008).

With reading mastery, Grade 3 students are more likely to improve academically

as they progress through the grades. They are also more likely to graduate from high

school (Houge et al., 2007; Rumberger & Palardy, 2005). When students graduate from

high school with proficient reading skills, they are more likely to obtain employment and

become contributing members of society.

Recommendations for Action

In this study, my results supported those of nine other studies (Baker et al., 2008;

Barger, 2003; Buck & Torgesen, 2003; Roehrig et al., 2008; Shaw & Shaw, 2002;

Shapiro et al., 2008;Vander Meer et al., 2005; Wilson, 2005; Wood, 2006), confirming a

correlational relationship between oral reading fluency and reading proficiency. Thus, the

first recommended action is for administrators and teachers to recognize the importance

of oral reading fluency to the development of reading proficiency. Second, administrators

should cultivate learning communities (Senge, 2000) of district administrators, teachers,

parents, and students in which at-risk readers are identified early, provided interventions

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that address their needs, and then monitored to determine if they are progressing

academically.

Third, the importance of the correlation between oral reading fluency and reading

proficiency should be communicated not only to educators but to students and parents.

By graphing oral reading fluency rates, students can quickly and easily see whether they

are improving. When these graphs include a goal line, students can see how fast they

need be reading by the end of the year. Once students have a visual representation of

where they need to be, they can also participate in setting their oral reading fluency goals.

Parents can also be trained to listen to their child read for exactly 1 minute and

then count the number of words their child read correctly. Parental training can be

provided through written instructions, parent-teacher conferences, and group training

sessions. Once the methods are established, oral reading fluency rates can be

administered daily or weekly. Rasinski and Stevenson (2005) demonstrated that parents

can be trained to be effective partners in programs designed to improve oral reading

fluency. Morgan and Sideridis (2006) demonstrated that students were motivated to

improve their oral reading fluency skills when they set goals to improve them.

Fourth, teachers in Grades 1 to 3 can be encouraged by administrators and in

professional development workshops to track oral reading fluency rates for their students.

Regardless of the grade level, elementary teachers can use oral reading fluency norms to

determine the developmental level of their students, monitor students’ progress, set goals

to motivate growth, and include instructional activities to build oral reading fluency. With

regard to monitoring students’ progress and setting goals, teachers can graph the oral

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reading fluency of their students with charts and graphic organizers and set goals for

students to reach them, with the students contributing their own goals. Morgan and

Sideridis (2006) found that setting goals improves oral reading fluency. Further, during

reading periods, teachers can pair struggling readers with their more proficient peers so

the struggling students benefit from the modeling of the proficient students (Nes Ferrera,

2005).

With regard to activities, several studies (Begeny et al., 2006; Hiebert, 2005;

Martens et al., 2007; Therrien et al., 2006; Therrien & Hughes, 2008) demonstrated that

repeated reading of passages can improve oral reading fluency rates. Teachers can

motivate students to read a text repeatedly by organizing such activities as a reader’s

theatre. In this activity, students practice reading scripts to perform them before an

audience (Corcorcan & Davis, 2005; Rasinski, 2006).

Researchers have shown that wide reading improves oral reading fluency (Kuhn,

2005). Based on such findings, teachers could organize instructional programs that track

the number of books students read and reward them for reading certain amounts of books.

Students could also be introduced to software that keeps track of their books read and

update their records themselves.

When students are reading books at their instructional levels, they are more likely

to be actively engaged and understand what authors are saying (Schnick & Knickelbine,

2000). Lexiles are one tool teachers can use to determine either a readers’ ability or the

difficulty of text (MetaMetrics, 2010). Texts are analyzed and assigned Lexile numbers,

with lower numbers (from -200L) indicating lower reading ability and higher numbers (to

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+1700L) indicating high ability (MetaMetrics, 2010). Educators can assign students

Lexile levels based on their performance on assessments such as TAKS. For example,

students with a raw score of 2100 on the 2009 Grade 3 Reading TAKS had a Lexile level

of 380L (TEA, 2009b). The Lexile range for that student would be from 280L to 480L.

Once students’ Lexile levels and ranges are determined, students’ abilities to read can be

matched with books which they are likely to be able to read. However, Lexile levels are

not fixed, and many factors can influence readability formulas. For example, interest can

affect Lexile levels. When students are interested in a subject, they may be able to read

text above their Lexile range (Schnick & Knickelbine, 2000). Therefore, a student with a

strong interest in airplanes may be able to read a book about airplanes with a Lexile level

above his Lexile range.

When assigning reading in cognitive subjects, such as social studies and science,

teachers can also make books available for students within their Lexile range. Students

should then feel confident they will be able to understand the text and will feel more

comfortable and motivated in reading. Readers who are intrinsically motivated to read

can understand what the author is saying because they are curious and want to read more.

In contrast, readers who are not motivated to read are often not engaged and fail to make

the necessary connections for comprehension (Schnick & Knickelbine, 2000).

In addition, teacher effectiveness has been identified as a crucial variable in

improved student test scores (Lane et al., 2009; Luster, 2010). Lane et al. found that

students with teachers who had a greater knowledge of the definition of oral reading

fluency and the skills required to test it demonstrated greater gains in oral reading fluency

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than students with teachers who had less knowledge and skills. Professional development

workshops can educate and train teachers on the roles of oral reading fluency and reading

proficiency After training in how to administer oral reading fluency assessments, teachers

can be introduced to instructional activities that have been shown to improve both oral

reading fluency and reading proficiency and enhance students’ skills and motivation,

such as repeated reading (Therrien & Hughes, 2008), reader’s theatre (Young & Rasinski,

2009), goal setting (Morgan & Sideridis, 2006), and wide reading (Kuhn, 2005).

Finally, greater parental involvement is recommended. Although many parents

are involved daily with their children’s learning, parents often need support to become

involved (Persampieri, Gortmaker, Daly, Sheridan, & McCurdy, 2006; Senge, 2000).

School partnership with parents has been shown to have strong positive effects on their

child’s educational experience. Persampieri et al. documented dramatic growth in oral

reading fluency rates with two struggling readers whose parents were trained to work

with them for 10 to 15 minutes 3 times a week for 3 weeks. In a training session with

each individual parent, one of the researchers described the intervention, modeled it, and

observed the parent implementing the routine. Parents were then given a calendar with

stickers to track intervention dates and reward the child. In addition, each child was

assessed 3 times at school each week. One student’s initial reading of a passage on his

reading level went from 43 wcpm to 61 wcpm 3 weeks later. The other student’s initial

reading of a passage went from 36 wcpm to 60 wcpm.

Rasinski and Stevenson (2005) studied two groups of 30 first graders. In one

group, the parents worked with the children on reading assignments an average of 10

105

minutes daily for 11 weeks. In the other group, parents did not assist. The results showed

significantly greater gains for the experimental group in oral reading fluency rates than

for the control group.

Parents can be trained to help their children through parent-teacher conferences

and workshops specifically for parents on activities at home that encourage their children

to read. Activities may include small-group demonstrations, written instructions, and

modeling (Persampieri et al., 2006). To verify that parents are correctly implementing the

method and encourage them, teachers can follow up with procedural checklists, audio

tapes, video tapes, and phone calls (Persampieri et al.).

Recommendations for Further Study

Based on the results of this study, I present several recommendations for further

studies with quantitative, qualitative, and mixed methods. Some of these studies could

replicate the current research to test generalizability. Other researchers could extend the

present results for greater understanding of the relationship between students’ ratings on

the DIBELS ORF and state-mandated assessments as diagnostic tools to improve and

accelerate students’ reading proficiency.

Quantitative Studies

In this study and others (Baker et al., 2008; Barger, 2003; Roehrig et al., 2008;

Shapiro et al., 2008; Vander Meer et al., 2005; Wilson, 2005; Wood, 2006), a

correlational relationship was established between oral reading fluency and reading

proficiency as measured by state-mandated reading assessments. However, because the

definition of reading proficiency differs from state to state and grade to grade, it is

106

important that additional studies be conducted to determine if a statistically significant

relationship exists between oral reading fluency and specific state-mandated reading

assessments (Roehrig et al.).

Thus, I suggest quantitative studies replicating the present study in other states

and at other grade levels than Grade 3. Further, beginning in the 2011-2012 year, the

TEA will replace the TAKS with the State of Texas Assessments of Academic Readiness

(STAAR; TEA, 2009f). An additional study is suggested to determine if a statistically

significant relationship exists between the DIBELS ORF benchmark rates and the Grade

3 STAAR assessment. Results could be compared with those of the present study not

only for additional understanding but also for determination of which assessment is more

strongly related to the DIBELS ORF.

Other quantitative studies could be conducted to explore the correlational

relationship of the DIBELS ORF to other types of reading proficiency assessments which

may measure various comprehension skills. Specifically, within the district in which this

study was conducted, a study could explore whether a statistically significant relationship

existed between DIBELS ORF benchmark rates and reading comprehension measured

with other assessments, such as istation, which assesses students’ reading ability through

Internet-delivered tests (istation, 2010). Additionally, a study could be conducted to

determine if a stronger correlational relationship existed between DIBELS ORF and the

state-mandated assessment or between the istation reading comprehension score and the

state-mandated reading assessment.

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Each spring, the district involved in this study also administers the

Comprehensive Test of Basic Skills (CTBS; Kids IQ Test Center, 2010) to students in

Grades 1 and 2. A quantitative study could be conducted to determine if a statistically

significant relationship existed between DIBELS ORF rates and the comprehensive

reading score on CTBS. A study could also compare the correlational relationship

between the Grade 2 CTBS comprehensive reading scores and the Grade 3 DIBELS ORF

benchmark rates to determine which had the highest correlational relationship to the

Grade 3 state-mandated reading assessment.

Students are motivated to read books when using programs such as the

Accelerated Reader (AR) program (Renaissance Learning, 2010). With the AR, students

receive AR points after they read a book and take a test on the computer. Such

assessments frequently contain many explicit questions to which students can find the

specific answers in the book. In these assessments, few implicit questions are asked in

which students are required to infer or conclude, reading between the lines or beyond the

lines to answer questions. Students who take the Grade 3 Reading TAKS must

demonstrate that they can use higher-order comprehension skills of inference and

concluding.

Following from these observations, a study could be conducted on students’ use

of higher-order and lower-order comprehension skills. A correlational analysis could

investigate whether the DIBELS ORF and a reading proficiency assessment demonstrate

a greater statistically significant relationship if the assessment used required only lower-

order comprehension skills. Such a study would help teachers determine if instruction in

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higher-order comprehension skills needs to be included in the instructional program.

Students could be more strongly motivated to learn if they recognize the relationship

between reading and answering explicit questions could help them in the state-mandated

reading assessment. Furthermore, they could be encouraged to learn additional strategies

to increase the possibilities of answering higher-order comprehension questions on the

state-mandated reading assessment. In addition, struggling readers could benefit from

development of meta-cognitive strategies to improve their scores on both the explicit and

implicit questions.

Finally, as Baker et al. (2008) suggested, researchers could use quantitative

studies to focus on students of specific ethnic backgrounds and subpopulations, such as

economically disadvantaged and special education students. In the current study, 56% of

the sample was economically disadvantaged and 54% was Hispanic. Although this

demographical representation was similar to that of all Grade 3 students in Texas, a study

could be conducted in which subpopulations, such as economically disadvantaged,

Hispanic, or special education students, were larger than the 64, the minimal sample size

determined by the G*Power Statistical Program for a study of this nature (Faul et al.,

2007). Results could help educators identify factors such as poverty and ethnicity that

might affect test scores. Once factors were identified, intervention programs could be

specifically designed and implemented for students in these subpopulations.

Qualitative Studies

I also recommend follow-up qualitative studies to the present research. Using

qualitative studies, researchers could explore factors such as participants’ experiences,

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attitudes, perceptions, and understanding of a phenomenon (Creswell, 2009). In the

present study, I showed a statistically significant relationship between oral reading

fluency and reading proficiency for Grade 3 students. A natural next step could be for

researchers to explore teachers’ attitudes toward oral reading fluency and reading

proficiency. Teachers could be asked if and why they felt that oral reading fluency and

reading proficiency were related, if and why they felt that time spent improving oral

reading fluency was effective, and if and why they felt that periods spent teaching other

reading strategies were more effective. Researchers could include investigation of

teachers’ perceptions of effective teaching strategies that positively impact oral reading

fluency or reading proficiency. Teachers’ experiences with severely struggling readers in

relation to such strategies could be documented as well.

Attitudes and practices of parents could also be studied. Studies (Persampieri et

al., 2006; Rasinski & Stevenson, 2005) have found that when parents were trained to

work with their children, the students’ oral reading fluency increased. Researchers could

use qualitative studies to explore the attitudes and strategies of parents in assisting their

children with reading, as well as the children’s attitudes and experiences working with

their parents to improve oral reading fluency and/or reading proficiency.

Mixed-Method Studies

Mixed-method studies are effective because they combine quantitative and

qualitative designs. Use of the combination may provide a more comprehensive

understanding of the research problem and answers to the research questions than either

single method (Creswell, 2009). A mixed-methods study could be conducted to

110

determine how the administration of each of the assessments affects students’ scores. In

this study and the other state studies (Baker et al., 2008; Barger, 2003; Roehrig et al.,

2008; Shapiro et al., 2008; Vander Meer et al., 2005; Wilson, 2005; Wood, 2006), no

one-to-one correspondence was found between oral reading fluency and the state-

mandated reading assessment. That is, none of the studies found that all the students with

a specific rate on the DIBELS ORF benchmark also achieved the same specific score on

the reading assessment.

Although a perfect one-to-one correspondence would be rare, studies could

investigate the factors that may account for the less-than-perfect results. For example, do

White students have a higher chance of passing the state-mandated assessment than

Hispanic students? In situations in which more White students pass than Hispanic

students, are there indications of bias? Researchers could conduct a mixed-method study

to determine if there were statistical differences in demographic characteristics and

passing rates (quantitative) and the views of teachers and administrators as to the reasons

for the results (qualitative).

Researchers could also conduct a mixed-method study to explore the effect of

testing environments on student performance in reading assessments. The DIBELS ORF

benchmarks are individually administered (Good & Kaminski, 2002b). When the

DIBELS ORF is administered, various factors could affect the results, such as the

presence of other students if the assessment was conducted in a corner of the classroom,

or administration in a quiet room with only the teacher and the student. In the first case, a

student could be distracted by the other students in the room and not read as fluently as if

111

he or she would have if in a quiet room alone with the teacher. The TAKS is most

frequently administered in a group setting (TEA, 2009e). Schools and teachers generally

make every possible effort to maintain test security, but factors such as the behavior of

other students in the classroom and eye contact with the teacher could have an effect on a

student’s performance. Using a mixed-method study, researchers could quantitatively

measure variables, such as student scores from both individual administration and group

administration, and then qualitatively explore participants’ and facilitators’ opinions of

the effects on the students of each variable.

Further, researchers could explore the attitudes of the teacher toward the student’s

reading level and regarding administration of the test. Although test directions

specifically guide the teacher’s verbal expressions, students are often aware of the

teachers’ body language. The teacher’s body language and assumptions about the

student’s difficulties in reading may affect the student’s oral reading fluency (Childs &

Fung, 2009; Singer & Goldin-Meadow, 2005).

Researchers could conduct a mixed-method studies to determine how such factors

might influence the results of the assessments. Quantitative explorations could include

surveys on teachers’ attitudes, as well as correlational analyses between the two tests. In

addition, researchers could ask open-ended questions during individual interviews with

participants on factors such as the tests themselves, distractions during administration,

and perceptions about students’ reading levels.

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Conclusion

The purpose of this study was to determine if a statistically significant

relationship existed between oral reading fluency and reading proficiency. The middle-

of-year DIBELS oral reading fluency rates for 155 Grade 3 students in a West Texas

school district was used to measure oral reading fluency. Reading proficiency was

measured using their Reading TAKS scale scores. In this archival study, I used the data

from the 2008-2009 school year to conduct a Pearson correlation analysis. The analysis

demonstrated a statistically significant positive correlation of .66 (p < .01).

My results were comparable to those of nine other studies conducted in seven

other states (Baker et al., 2008; Barger, 2003; Buck & Torgesen, 2003; Roehrig et al.,

2008; Shaw & Shaw, 2002; Shapiro et al., 2008;Vander Meer et al., 2005; Wilson, 2005;

Wood, 2006). All of these studies found a significant correlation between oral reading

fluency and reading proficiency (range .58 to .80). Shaw and Shaw showed a strong

correlation, .80. Five other researchers (Barger, Roehrig et al., Shapiro et al., Vander

Meer et al., Wilson) reported moderately strong correlations. The difference in levels of

significance might be attributed to factors such as sample size, the rigor of the assessment

used to measure reading proficiency, and the sample demographic composition.

This study is the first to investigate the relationship in Texas between students’

oral reading fluency and reading proficiency. The study fills a gap in the literature by the

investigation of whether a statistically significant relationship existed between oral

reading fluency and reading proficiency as defined by the state-mandated assessment in

Texas (TAKS). Positive social change can occur when educators in Texas use the results

113

of this study to provide them with additional information and tools for helping struggling

readers gain greater fluency and proficiency. Because of the positive correlation between

the DIBELS ORF and the Grade 3 Reading TAKS, educators can use oral reading

fluency as a means of identifying struggling readers as early as Grade 1. Educators can

then provide scientifically-based interventions designed to improve students’ basic

literacy skills before they take the high-stakes Grade 3 Reading TAKS.

If the needs of struggling readers are addressed in the early grades, they have a

better chance of learning to read (Jenkins et al., 2007) and academic success on

assessments such as TAKS and in later course work throughout school (Ehri, 2005;

Shapiro et al., 2008). Struggling readers whose needs have been addressed also improve

their chances of graduating from high school (Houge et al., 2007; Rumberger & Palardy,

2005), as well as obtaining employment after they graduate (Katsiyannis et al., 2007).

I made several recommendations for action in the field to improve oral reading

fluency rates and to help students to become more proficient readers. Teachers, especially

in Grades 1 to 3, can use oral reading fluency rates to monitor their students’ progress.

Teachers can also employ teaching strategies such as repeated reading (Martens et al.,

2007), reader’s theatre (Corcorcan & Davis, 2005), motivational strategies (Morgan &

Sideridis, 2006), and pair reading (Nes Ferrera, 2005). Teachers can also enlist parental

support, with school-designed training programs for parents (Rasinski & Stevenson,

2005). Further, teachers can encourage students’ wide reading (Kuhn, 2005) and help

them monitor their progress. Lexile levels (Schnick & Knickelbine, 2000) can be used to

114

determine students’ instructional reading ranges, and teachers can then help students

select reading material on their level, increasing students’ motivation to read.

I recommended several possibilities for further study with quantitative,

qualitative, and mixed-method research. These recommendations included additional

quantitative studies replicating the present research in other states and grade levels, as

well as quantitative studies on the relationship between the DIBELS ORF and

assessments other than the TAKS, such as the new STAAR assessment to be

implemented in Texas in 2012 (TEA, 2009f). I suggested researchers use qualitative

studies to explore the attitudes of students, teachers, and parents regarding oral reading

fluency and reading proficiency. I suggested further that researchers use mixed-method

studies to explore the differences in the performance of various subgroups and the

reasons and thoughts of teachers and administrators regarding those differences.

Researchers could also conduct mixed-method studies to explore the possible impact of

testing environments on results.

In the current study, I confirmed a statistically significant relationship between

oral reading fluency rates and reading proficiency. Although researchers in other states

(Baker et al., 2008; Barger, 2003; Buck & Torgesen, 2003; Roehrig et al., 2008; Shaw &

Shaw, 2002; Shapiro et al., 2008; Vander Meer et al., 2005; Wilson, 2005; Wood, 2006)

confirmed similar relationships, I was the first to document the relationship between oral

reading fluency rates and reading proficiency for Grade 3 students on the state-mandated

assessment in Texas. Administrators and teachers in districts and schools can use the

study findings to identify struggling readers in the early grades and provide immediate

115

and appropriate interventions to address these students’ reading needs. Through

identification and remediation, the students will not only improve their scores on state-

mandated assessments but will learn to read more proficiently and achieve greater

academic success in the elementary grades and subsequent grades.

116

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Appendix A: Permission to Collect Data

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Appendix B: Data Use Agreement

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Appendix C: Permission to Use DIBELS

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Appendix D: Permission to Use TAKS

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TEXAS EDUCATION AGENCY - COPYRIGHT LICENSE AND PERMISSION FORM

Applicant Information (to be completed by applicant): Name: Kathy Jones

Title: Doctoral Student

City: Odessa

Zip: 79764

Email: jonesks1956@yahoo.com

Company: Walden University

Address: 9060 W.

University State/Province: TX Country:

USAPhone: 432.230.0130

Details of Request (to be completed by applicant):

1. Title/Author of Works (the “Works”) for Which License is Sought (for example,, Texas Assessment of Knowledge and Skills (TAKS), G/T Teacher Toolkit II, Videos from series “Accommodations and Modifications in CTE Classroom Instruction”): Use of TAKS as a resource for completing doctoral study at Walden University 2. Indicate How Works will be Used: � Business/Commercial � Non-Profit/Government � Personal Use 3. Briefly State Purpose for Which License is sought: 5 10-2010 I am a doctoral student at Walden University. My research will determine if a statistically significant relationship exists between oral reading fluency (as measured by the middle-of-year Grade 3 DIBELS benchmark) and reading proficiency (as measured by the scale score on the February, 2009 Grade 3 Reading TAKS). I would like to obtain permission from TEA to use TAKS in my study. As you requested in our phone conversation, I am attaching a copy of my proposal with all the references to TAKS highlighted in green. The specific websites and resources that I referenced are listed below: Texas Education Agency (2004). Grade 3 reading Texas Assessment of Knowledge and Skills information booklet. Austin, TX: Author. Texas Education Agency. (TEA). (2006). TAKS performance level descriptors. Retrieved from http://www.tea.state.tx.us/index3.aspx?id=3222&menu_id=793 Texas Education Agency. (TEA). (2009a). TAKS campus aggregate results page. Retrieved from http://ritter.tea.state.tx.us/cgi/sas/broker

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Texas Education Agency. (TEA). (2009b). Texas Assessment of Knowledge and Skills raw score conversion table reading—March 2009 administration grade 3. Retrieved from http://ritter.tea.state.tx.us/student.assessment/scoring/ convtables/2009/taks/mar09_g03_read.pdf Texas Education Agency. (2009c). Texas Assessment of Knowledge and Skills statewide summary report. Retrieved from http://ritter.tea.state.tx.us/student.assessment/ reporting/results/summary/2009/taks_mar09_g03.pdf Texas Education Agency. (TEA). (2009d). Texas Assessment of Knowledge and Skills—Summary report, group performance: District. Austin, TX: Author. Texas Education Agency. (TEA). (2009e). Texas Student Assessment Program, Accommodations manual, 2009-2010. Retrieved from http://ritter.tea.state.tx.us/ student.assessment/resources/accommodations/AccommManual_2009_10.pdf Texas Education Agency (TEA) & Pearson. (2008). Technical digest for the academic year 2007-2008. Retrieved from http://ritter.tea.state.tx.us/student.assessment/ resources/techdigest/2008/table_of_contents.pdf My committee has approved my proposal. Several people have indicated that many doctoral students complete all the requirements of their dissertation within six months of this point. Consequently, my current goal for completion is December, 2010. On the phone you indicated that you would probably extend permission to use TAKS in my study until March, 2011. Thank you for your time! Kathy Jones 4. Identify the specific URL(s) or website(s) where the “Works” can be located: http://www.tea.state.tx.us/index3.aspx?id=3222&menu_id=793 http://ritter.tea.state.tx.us/cgi/sas/broker The Texas Education Agency is dedicated to improving educational performance. It is the owner of various proprietary materials such as the Works listed above. Any use of the Works is subject to the attached Terms of Use and the provisions listed below. Any use shall include the following notice: Copyright © 2010. Texas Education Agency. All Rights Reserved.

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Terms of Copyright License Authorized, if any (to be completed by Texas Education Agency) A. Authorized Use (to be completed by Texas Education Agency): Authorized to use, reproduce, display, publish, and distribute TEA materials in conjunction with Ms. Jones' doctoral archival study at Walden University. B. Additional Restrictions:Use by applicant of TEA copyrighted material is limited to graduate study only. You may not charge a fee for your study, nor market or sell your study containing TEA copyrighted materials without a license agreement from TEA. C. Fee for Use of Works: None D. Term (check one): From date of issue and ending on March 31, 2011 E. Licensed Territory: � Worldwide � Country/Province � U.S. & its possessions and territories � State(s) (please specify): Texas F. Payment Schedule: None G. Reporting: None COPYRIGHT LICENSE AFFIRMATION OR DENIAL (To be completed by the Texas Education Agency) � I, the undersigned, on behalf of the Texas Education Agency, grant a license for the person or entity identified above to use the Works on a non-exclusive, nontransferable, non-assignable basis pursuant to the above and the Terms of Use set forth below. � I am unable to grant a copyright license for use of the specified Works. By Texas Education Agency Printed Name: Robert N. Jocius

Title: Manager, Office of Intellectual Property

Date: 6/23/2010

By Applicant Printed Name: Kathy Jones

PLEASE RETURN THIS FORM TO: Robert N. Jocius Manager, Office of Intellectual Property, Room 5-125C Texas Education Agency 1701 N. Congress Avenue Austin, TX 78701

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Copyrights@tea.state.tx.us Ph.: (512) 463-9270

TERMS OF USE

1. Definitions. “Agreement” means the above Copyright License and Permission Form and these Terms of Use. “Authorized Use” means the purpose for which the Works are to be used and the approved use of the Works granted by TEA. “Intellectual property rights” means the worldwide intangible legal rights or interests evidenced by or embodied in: (a) any idea, design, concept, method, process, technique, apparatus, invention, discovery, or improvement, including any patents, trade secrets, and know-how; (b) any work of authorship, including any copyrights, moral rights or neighboring rights; (c) any trademark, service mark, trade dress, trade name, or other indicia of source or origin; (d) domain name registrations; and (e) any other similar rights. The intellectual property rights of a party include all worldwide intangible legal rights or interests that the party may have acquired by assignment or license with the right to grant sublicenses. “Licensee” means the applicant specified above, if applicant’s Copyright License and Permission Form is approved by TEA. “Licensed Territory” means the specific Territory (district, area or geographic location) in which Licensee is located and for which the license, if any, is granted by TEA. “TEA” means the Texas Education Agency. “Works” means the works of authorship, written materials or other tangible items specifically set forth above. 2. Grant of License. For the consideration set forth above, TEA grants to Licensee, and Licensee accepts from TEA, a revocable, non-exclusive, non-transferable, non-assignable license to utilize the Works on or in connection with the Authorized Use for educational purposes in the Licensed Territory for the Term specified above.

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3. Term and Termination. (a) The license granted herein will be effective from the date the Agreement is signed by TEA, and shall continue in effect for the Term identified above, unless sooner terminated in TEA’s sole discretion. (b) If Licensee breaches any of its obligations under the terms of this Agreement, TEA may terminate this Agreement effective immediately, without prejudice to any other rights or remedies TEA may have, upon giving written notice of termination to Licensee. (c) If Licensee attempts to assign, sublicense or subcontract any of its rights under this Agreement, without the prior written permission of TEA, TEA may terminate this Agreement effective immediately, without prejudice to any other rights or remedies TEA may have, upon giving written notice of termination to Licensee. Notwithstanding any of the foregoing, TEA has the right to terminate this Agreement, with or without cause, upon giving thirty (30) days written notice of its intent to terminate the Agreement. (d) To the extent permitted by law, Licensee agrees to protect and treat all information provided by TEA to Licensee relating to the Works or this Agreement as confidential, proprietary and trade secret information. Licensee will not use, disclose, or cause to be used or disclosed, such confidential and trade secret information, or otherwise impair or destroy the value of such confidential and trade secret information. Licensee agrees not to disclose or cause to be disclosed the terms of this Agreement, except as required by law. 4. Compensation. (a) Licensee will furnish to TEA a full, complete and accurate report showing all gross and net revenue received regarding the Works according to the reporting requirements found in Section G. of this license. (b) Licensee will keep accurate books of accounts and records covering all transactions relating to this Agreement and the Works for all years during which this Agreement is in effect, and will keep such books for a period of five (5) years after the expiration or termination of this Agreement. TEA and the State of Texas auditor, or their representatives, will have the right to examine such books of account and records and other documents and material in Licensee’s possession or under its control insofar as they relate to the Agreement or the Works.

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(c) TEA, in its sole discretion, may procure registration of the intellectual property rights in and to the Works, or any derivative works thereof. Licensee will not seek to register or secure any intellectual property rights in and to the Works, or any derivative works thereof. Licensee shall notify TEA in writing of any infringements or imitations by others of the Works to which it becomes aware. TEA may then, in its sole discretion, commence or prosecute in its own name any claims or suits for infringement of the Works or the intellectual property rights associated therewith, or any derivative works thereto. (d) Licensee shall not, during the Term of this Agreement, or at any time thereafter, dispute or contest, directly or indirectly, the right, title or interest of TEA in or to the Works, the intellectual property rights therein, the goodwill reflected thereby, or as to the validity of this Agreement or the license terms therein. The provisions of this section 6 shall survive the expiration or termination of the Agreement. (e) Licensee will legibly and prominently display the following copyright notice in connection with all Authorized Use of the Works: Copyright © 2010. Texas Education Agency. All Rights Reserved. 7. Quality Standards. (a) Licensee acknowledges that if the Authorized Use of the Works by Licensee were of inferior quality in design, material or workmanship, the substantial goodwill which TEA has built up and now possesses in the Works would be impaired. Accordingly, Licensee will ensure that its use of the Works will meet or exceed any and all relevant industry standards, and are of such style, appearance and quality as will be reasonable, adequate and suited to their exploitation and to protect and enhance such goodwill. (b) To ensure that appropriate standards of style, appearance, and quality are maintained, Licensee will provide samples to TEA of Licensee’s proposed use of the Works prior to distribution to the intended recipient, for TEA’s approval. 8. Student Information. Licensee understands that any unauthorized disclosure of confidential student information is illegal as provided in the federal Family Educational Rights and Privacy Act of 1974 (FERPA), 20 USC, Section 1232g, and implementing federal regulations found in 34 CFR, Part 99.

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Curriculum Vitae

Kathy Jones jonesks1956@yahoo.com

EDUCATION

2010 Doctor of Education in Administration, Walden University • Dissertation Topic: “The Relationship Between Oral Reading Fluency and

Reading Proficiency” o Conducted research to determine if there was a relationship between

the middle-of-year oral reading fluency rates of Grade 3 students and performance on the state-mandated assessment for reading proficiency

• 4.0 grade GPA • Served on the Walden Advisory Committee • Completed residencies in Dallas, TX and Lansdowne, VA

2001 Master of Education, Reading Specialist

Abilene Christian University, Abilene, Texas • 4.0 GPA • Participant in the education service center program for training professionals

in other fields to become educators • Passed all teacher examinations the first time they were attempted, including

the prestigious Master Reading Teacher

1997 Bachelor of Applied Studies Degree Abilene Christian University, Abilene, Texas • 4.0 GPA • Member of W-Club, an honor society for Christian women at ACU • Member of Kappa Delta Pi • Secretary for the Bachelor of Applied Studies (a degree completion program

for older adult students) o Motivated adult learners to achieve their educational goals o Helped prospective adult students realize how their life experiences

could be used to further their education

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• Secretary for the McNair Scholars Program

o Received inspiration from the story of Ronald McNair, an African American who came from a segregated school, attended MIT, obtained a doctorate in physics , became the second African American astronaut, and died on the Space Shuttle Challenger

o Encouraged first-generation, low-income, undergraduate college students to pursue graduate programs

1995 Third Year Teaching Certificate

University of Micronesia/Federated States of Micronesia, Kolonia, Pohnpei, FM • 4.0 GPA • Elected as the Class Secretary • Student Teacher, Kolonia Elementary School • Conducted research in which 100 native children were assessed to determine

which English sounds the students struggled to learn • Attended the local university in this country in which my family served as

missionaries • Only American student in classes • Obtained the highest degree available in education at that time in that location

TEACHING CERTIFICATES

• Standard o Master Reading Teacher (Grades EC-12), 9/12/2003-2/28/2015 o Classroom Teacher English as a Second Language (Grades EC-12),

9/12/2003-2/28/2015 o Reading Specialist (Grades PK-12), 9/12/2003-2/28/2015

• Provisional o Elementary Reading (Grades 1-8). 2/27/1998-Life o Elementary Self-Contained (Grades 1-8), 2/27/1998-Life o Generic Special Education (Grades PK-12), 5/22/1998-Life

EMPLOYMENT EXPERIENCE

District Dyslexia Teacher Monahans-Wickett-Pyote Independent School District, June 2009 to present

• Devised process for identifying and progress monitoring dyslexic students • Worked collaboratively with teachers, principals, and district administrators to

meet the needs of dyslexic students • Provided dyslexic therapy for dyslexic students in Grades 1 to 6 • Trained other teachers and aides to teach dyslexic students • Analyzed data from students’ standardized assessments to group students for

intervention

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• Conducted 504 meetings where 504 students were identified and plans were made for accommodations to address their educational needs

Teacher Tatom Elementary, Monahans-Wickett-Pyote Independent School District, January 2008 to June 2009

• Taught second graders • Volunteered to work with dyslexic students

o Taught six dyslexic students after school � All of these students who took the state-mandated reading

assessment passed the first time exam was administered o Made recommendations to the district for assessments to use when

determining if students are dyslexic o Trained counselors to administer assessments o Administered dyslexia assessments

• Taught summer school for students who had failed the state-mandated reading assessment twice

o Disaggregated data to determine students’ strengths and weaknesses o Targeted instruction to meet students’ needs o 75% of these students passed on their third attempt to take the state-

mandated reading assessment 504/Dyslexia Coordinator Ector County Independent School District, August 2006 to December 2007

• Supervised six teachers who assessed students referred for dyslexia • Evaluated district process for identifying dyslexics • Improved record-keeping process for maintaining district records • Collaborated with principals and other administrators to serve the needs of 504

students Reading Coordinator Ector County Independent School District, January 2005 to August 2006

• Wrote scope and sequence for reading, Grades K to 8 • Wrote district benchmarks for reading, Grades K to 8 • Trained teachers to administer state-mandated early reading inventory • Organized staff development days to provide a wide range of professional

development activities to enhance instruction in reading • Evaluated effectiveness of district reading programs • Conducted professional development workshops in reading and dyslexia

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Teacher Bowie Junior High School, Ector County Independent School District, August 2000 to December 2004

• Taught reading, Grades 7 and 8 • Assessed and provided services for ESL students • At principal’s request, mentored first-year teachers • Received grants from local education foundation designed to encourage

innovative teaching projects o Hidden in Plain View, $3,000.00 o Walking a Mile in Your Moccasins, $2,970.01 o Be Proud of Your Heritage, $860.00 o Because We Can Change the World, $3,790.25 o Wordplay at Work, $999.74 o Empowering Parents and Teens to be Practically Perfect, $4,874.90 o Reaching Out, $4,745.26

• Secretary and President-elect of local chapter of Texas Classroom Teachers Association

o Met with superintendent each month to discuss teachers’ concerns o Attended conferences in the state capitol to keep informed on political

issues relating to teachers o Did not serve as president because the district hired me as an administrator

(TCTA membership does not include administrators) • Featured in several education spotlights on local television stations and in

newspapers • Invited to join Professional Development Cadre, in which outstanding teachers

were trained to present professional development workshops Special Education Teacher Franklin Middle School, Abilene Independent School District, December 1997 to May 2000

• Taught a self-contained unit of mentally-challenged students • Chosen as Teacher of the Month by student organization • Attended two-year dyslexia training program • Taught mentally-challenged students how to read

Teacher, Adult Education, Abilene Independent School District, September 1996 to May 1997

• Taught adult students whose reading level was less than Grade 3 • Attended workshops for teachers of adult students

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Missionary Church of Christ, Kolonia, Pohnpei, Federated States of Micronesia, May 1982 to June

1995 • Served as missionary in a third-world developing country • Adopted into a local clan • Used the Bible to teach English to over 1,000 individuals • Home-schooled my children over a 10-year period

o Taught and inspired one daughter, who was designated as gifted and talented and later became a lawyer

o Taught and identified one son as dyslexic who later graduated with a masters degree in international development

� Noticed he was not learning to read proficiently � Read numerous books to gather information � Implemented teaching strategies that resulted in his academic

growth from a 2nd-grade reading and writing level to a 7th-grade reading and writing level during his 6th-grade year

o Taught one son with ADHD who is currently enrolled in a medical physics Ph.D. program

• Organized a network of home school families o Taught other home schooled students who were struggling with reading o Taught a Social Studies unit on Australia for all the home schooled

children and culminated the unit with an afternoon spent with the Australian ambassador

• Worked collaboratively with native leaders and expatriates to open a library o Joined other interested individuals during the first meeting to discuss the

idea o Recruited and organized volunteers to work in the library o Served on the Friends of the Library Board

• Conducted a summer school o Wrote curriculum for the summer school o Trained my husband and children to teach in summer school o Invited 40 children who could not read to attend summer school o Taught a boy whom local teachers had declared uneducable how to write

his name o Taught a 17-year-old boy to read for the first time o Taught one boy who claimed that he had learned more in summer school

than in the previous 9 months of school • Accepted principals’ requests to train their teachers how to teach reading

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COMMUNITY SERVICE Visiting Committee, Brown Library, Abilene Christian University, 2004 to 2006

• Accepted appointment by the Director of Library Services to serve on committee • Served with other experts to

o Review library’s operations o Report to provost of the university on the library’s status

School Board Member, Odessa Christian Schools, 2007 to present

REFERENCES

Dr. Thomas Schnick Chairman of Doctoral Committee Walden University 608-242-4629 Thomas.Schnick@waldenu.edu Dr. Barbara Bailey Member of Doctoral Committee 404-272-2222 baileyba@mindspring.com

Susan Myers Adjunct Professor Grand Canyon University (928) 333-4190 (928) 245-3101 susanmyers@frontiernet.net

Doug Doege Supervisor Tatom Elementary School Monahans-Wickett-Pyote Independent School District 432-943-2769 ddoege@mwpisd.esc18.net