This document certifies that Kathy Jones' doctoral study was found to be complete and satisfactory. It was reviewed by a committee consisting of Dr. Thomas Schnick, Dr. Barbara Bailey, and Dr. Brett Welch. The study investigated the relationship between 3rd grade students' oral reading fluency rates and their reading proficiency on the state-mandated Texas Assessment of Knowledge and Skills. The results indicated a relationship between oral reading fluency and reading proficiency. The study may help schools identify at-risk readers and implement interventions to improve student reading proficiency.

1. 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

2. 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

3. 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.

5. 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

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7. 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.

8. 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.

9. 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.

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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

16. 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

17. 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).

18. 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

19. 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

20. 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

21. 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

22. 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

23. 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.

24. 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.

25. 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.

26. 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).

27. 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.

28. 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

29. 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.

30. 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

31. 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

32. 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

33. 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.

34. 20
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

35. 21
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

36. 22
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;

37. 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

38. 24
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.

39. 25
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

40. 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-

41. 27
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

42. 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

43. 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,

44. 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

45. 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

46. 32
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

47. 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

48. 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

49. 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

50. 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

51. 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

52. 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.,

53. 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

54. 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.

55. 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

56. 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

57. 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).

58. 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

59. 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,

60. 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

61. 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

62. 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

63. 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

64. 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.

65. 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.

66. 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

67. 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

68. 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

69. 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.

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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

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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

95. 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

101. 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

102. 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)

105. 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

107. 93
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

108. 94
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

109. 95
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

111. 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

112. 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).

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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

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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

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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

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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

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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

127. 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

128. 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

129. 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.

130. 116
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id=3216&menu_id=793
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raw score conversion table reading—March 2009 administration grade 3.
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scoring/convtables/2009/taks/mar09_g03_read.pdf
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Appendix A: Permission to Collect Data

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Appendix B: Data Use Agreement

150. 136

151. 137

152. 138

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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.
UniversityState/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

157. 143
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.
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161. 147
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shall be provided to TEA promptly upon request.

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regulations found in 34 CFR, Part 99.

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9. Miscellaneous.
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provision to the minimum extent necessary to make it legal and enforceable while

164. 150
preserving its intent. It is the specific intent and request of TEA and Licensee that
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hereof or a default herein will be deemed a waiver by such party of a subsequent
breach or default of like or similar nature.

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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

166. 152
• 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

167. 153
• 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

168. 154
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

169. 155
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

170. 156
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