EXPLORING THE INFLUENCE OF DEVELOPMENTAL KINDERGARTEN
ATTENDANCE ON LATER LITERACY AND SOCIAL-EMOTIONAL OUTCOMES: A
RECORDS REVIEW INVESTIGATION IN ONE MICHIGAN SCHOOL DISTRICT
By
Erin Seif

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
School Psychology – Doctor of Philosophy
2014

ABSTRACT
EXPLORING THE INFLUENCE OF DEVELOPMENTAL KINDERGARTEN
ATTENDANCE ON LATER LITERACY AND SOCIAL-EMOTIONAL OUTCOMES: A
RECORDS REVIEW INVESTIGATION IN ONE MICHIGAN SCHOOL DISTRICT
By
Erin Seif
The transition to kindergarten from previous early childhood experiences is a milestone and
challenge for both children and parents. Developmental kindergarten (DK) is a specific type of
early childhood educational intervention that is designed to ease the transition to kindergarten.
However, very little research is published in peer-reviewed journals pertaining to the effects of
DK as an early education intervention for five-year old children. Five years of archival data from
one suburban school district in Michigan was used to better understand the influence of DK
attendance on long-term academic social-emotional growth. The sample consisted of 1082
students ranging in age from five years to twelve years old. Thirty percent (30%) of the sample
attended DK. Students were divided into cohorts based on current grade level. A two-level
hierarchical linear model was used to compare the literacy and social-emotional growth
trajectory of students who did versus did not attend DK. Results indicated that children who
received the DK intervention and their peers who did not receive the intervention experienced
similar literacy and social-emotional growth trajectories across time. Implications of this study
are relevant to researchers and educators interested in the short and long-term effects of DK on
typically developing children from advantaged backgrounds.
Keywords: early childhood education, developmental kindergarten, early childhood
intervention

To Jasen and Jax for all of your sacrifices on behalf of this work. To my mom and dad for their
amazing work ethic and willingness to help others. And to first generation college students
everywhere. May you never give up.

iii

ACKNOWLEDGEMENTS

I wish to thank my dissertation chair, Dr. John Carlson, for the time he spent meeting
with me to refine my conceptualization of this project and reading draft upon draft of this
dissertation. I would also like to thank the other members of my committee, Dr. Sara Witmer,
Dr. Konstantopoulos, and Dr. Skibbe for their support and guidance. I am also indebted to my
former supervisor who encouraged me to take full advantage of the opportunities at the school
where I completed my practicum work. I also wish to thank the assistant superintendent and
elementary principals who welcomed me into their school buildings and allowed me to collect
data. Special thanks are in order for Amber Markey for her remarkable efficiency and attention
to detail during the data collection process. I also wish to express thanks to those who have
always been incredibly supportive of this and other endeavors including Kristen, Hannah, Erin,
Marla, Dylan, Teryn, and Matt.

iv

TABLE OF CONTENTS

LIST OF TABLES .............................................................................................................................viii
LIST OF FIGURES ...........................................................................................................................x
CHAPTER 1
INTRODUCTION .............................................................................................................................1
CHAPTER 2
LITERATURE REVIEW ..................................................................................................................10
Definitions................................................................................................................................10
Theoretical Models ..................................................................................................................17
Maturational Model ............................................................................................................17
Comprehensive Model ........................................................................................................17
Bronfenbrenner’s Bioecological Model ..............................................................................18
Developmental Model of Transition ...................................................................................18
Historical Early Childhood Programs ......................................................................................19
High/Scope Perry Preschool ...............................................................................................20
Carolina Abecedarian Project .............................................................................................21
Chicago Child-Parent Centers.............................................................................................22
Head Start............................................................................................................................23
Developmental Kindergarten Programs ...................................................................................25
Age at Kindergarten Entry .......................................................................................................35
Redshirting ..........................................................................................................................35
Perceived Gains Fade Over Time .......................................................................................36
Kindergarten Retention ............................................................................................................38
Negative Effects Associated with Being Young in Kindergarten ......................................43
Special Education Rates ......................................................................................................43
School Readiness ................................................................................................................45
Predictive Validity of School Readiness Measures .................................................................46
Perceptions of School Readiness ........................................................................................48
Risk Factors Relating to School Readiness .....................................................................48
School Readiness in Relation to Family Income .............................................................50
School Readiness Skills and Prior Preschool Experience................................................51
Differential gains from Preschool Programs............................................................................52
Social-emotional Skills in Relation to Academic Skills ..........................................................55
Preschool Social-Emotional Learning .....................................................................................57
Self-Management ................................................................................................................57
Attention .............................................................................................................................60
Relationship skills ...............................................................................................................63
Early Literacy Skills ................................................................................................................66
v

Early Literacy Skills Associated with Later Academic Achievement .....................................68
Alphabet Knowledge ..........................................................................................................68
Phonological Processing .....................................................................................................69
Phonological Awareness ...................................................................................................69
Phonological Memory.......................................................................................................70
Development of Phonological Processing Skills ..............................................................70
Rapid Automatic Naming ........................................................................................................71
Writing Letters and Writing Name ..........................................................................................72
Concepts of Print......................................................................................................................74
Oral Language ..........................................................................................................................75
Visual Processing .....................................................................................................................76
Models of Emergent Literacy Development ............................................................................77
Contemporary Models of Emergent Literacy Development ..............................................79
Development of Early Literacy Skills................................................................................80
Curriculum-Based Measurements ............................................................................................81
Current Study Research Questions and Hypotheses ................................................................85
Research Questions and Hypotheses .......................................................................................86
CHAPTER 3
METHOD ..........................................................................................................................................90
Participants ..............................................................................................................................90
Inclusion criteria ................................................................................................................92
Description of DK Program ...............................................................................................93
Variables Considered in the DK Placement Process .........................................................93
Description of Kindergarten Program ................................................................................94
Measures .................................................................................................................................94
Kindergarten Screening Measure .......................................................................................94
Scoring the Kindergarten Screener ..................................................................................95
DIBELS Scores ..................................................................................................................96
Letter Naming Fluency ......................................................................................................97
Initial Sound Fluency .........................................................................................................97
Phoneme Segmentation Fluency ........................................................................................98
Nonsense Word Fluency ....................................................................................................98
Oral Reading Fluency ........................................................................................................99
Rationale ............................................................................................................................100
Michigan Educational Assessment Program ..........................................................................100
Reliability...........................................................................................................................101
Validity ..............................................................................................................................101
Rationale ............................................................................................................................102
Data Collection .......................................................................................................................103
Data Analysis ..........................................................................................................................103
Research Questions One and Two ..........................................................................................103
Research Question Three ........................................................................................................107
Missing Data ...........................................................................................................................108

vi

CHAPTER 4
RESULTS ..........................................................................................................................................112
Question One ..........................................................................................................................112
Question Two ..........................................................................................................................119
Question Three ........................................................................................................................124
CHAPTER 5
DISCUSSION ....................................................................................................................................128
Implications............................................................................................................................132
Limitations .............................................................................................................................137
APPENDICES ...................................................................................................................................140
Appendix A – Kindergarten Screener .......................................................................................141
Appendix B – Kindergarten Screener Rubrics..........................................................................142
Appendix C – Information Obtained from CA-60 Files ...........................................................145
Appendix D – End of Year Developmental Kindergarten Progress Report .............................146
Appendix E – Social-emotional Measures from Kindergarten through Fourth Grade Report
Cards ..................................................................................................................147
Appendix F – Level 2 Descriptive Statistics.............................................................................148
BIBLIOGRAPHY ..............................................................................................................................150

vii

LIST OF TABLES

Table 1

Early Childhood Interventions Available in one Michigan County ..........................14

Table 2

Similarities and Differences between Pre-K and DK ................................................26

Table 3

Examples of Michigan Early Childhood Standards of Quality for
Pre-Kindergarten ......................................................................................................32

Table 4

Characteristics of School Readiness ..........................................................................47

Table 5

Significant Differences Between Groups Based on Percentage ................................92

Table 6

Sample Size by Grade Level and School ID..............................................................92

Table 7

Variables Included in the Study .................................................................................109

Table 8

Proposed Research Questions, Measures, and Analytic Procedures .........................110

Table 9

Second Grade Final Estimation of Fixed Effects – Literacy Growth ........................113

Table 10

Third Grade Final Estimation of Fixed Effects – Literacy Growth ...........................114

Table 11

Fourth Grade Final Estimation of Fixed Effects – Literacy Growth .........................115

Table 12

Fifth Grade Final Estimation of Fixed Effects – Literacy Growth ............................116

Table 13

Average Raw Scores for Literacy Outcomes Across Time .......................................117

Table 14

Percentage of Students Scoring at the Proficient or Advanced Level on the MEAP
Test .............................................................................................................................118

Table 15

Third Grade Final Estimation of Fixed Effects – Social-Emotional Growth ............120

Table 16

Fourth Grade Final Estimation of Fixed Effects – Social-Emotional Growth ..........121

Table 17

Fifth Grade Final Estimation of Fixed Effects – Social-Emotional Growth .............122

Table 18

Average Raw Scores for Social-Emotional Outcomes Across Time ........................123

Table 19

Predictive Validity of Kindergarten Screening Measure Across time for Literacy
Outcomes ...................................................................................................................124

viii

Table 20

Predictive Validity of Kindergarten Screening Measure Across time for SocialEmotional Outcomes ..................................................................................................125

Table 21

Second Grade Descriptive Statistics ..........................................................................148

Table 22

Third Grade Descriptive Statistics .............................................................................148

Table 23

Fourth Grade Descriptive Statistics ...........................................................................148

Table 24

Fifth Grade Descriptive Statistics ..............................................................................149

ix

LIST OF FIGURES

Figure 1

Developmental Model of Transition ..........................................................................19

Figure 2

Summary of Factors Associated with Early Literacy Development .........................81

x

CHAPTER 1
INTRODUCTION
“Mom had a hard time not getting upset. Mom was very anxious and worried that she wouldn’t
make the right decision and was looking forward to hearing the kindergarten screening team’s
opinion.”
“Parents are on the fence and feel torn.”
During the past two decades there has been greater interest in programs and policies that
affect early childhood development (Reynolds & Temple, 2008). Since the turn of the century,
research exploring the neurological development that occurs in early childhood and the
importance of high quality early childhood relationships and environments has burgeoned
through seminal works such as From Neurons to Neighborhoods: The Science of Early
Childhood Development (Shonkoff & Phillips, 2000). Laws and policies have slowly begun to
acknowledge the importance of early childhood, such as the provisions in The Individuals with
Disabilities Education Act (IDEA) of 2004 for children from birth to age two (United States
Department of Education, 2013). Although the intense focus on early childhood education
reflected in the agendas of policy makers, economists, and researchers is somewhat recent, the
difficult transitions and decisions that families face when a child is ready to begin kindergarten
are long-standing. Parents are often left with many questions and few answers during this early
childhood milestone.
The opening quotes were taken directly from kindergarten screeners and reflect the
difficulties and struggles many families face in the transition from home-based or center-based
care during the first years of a child’s life to formal K-12 schooling. In addition to adjusting to
children spending less time at home, many parents wrestle with decisions related to their child’s
1

kindergarten attendance. Does my child have the appropriate school readiness skills to begin
kindergarten? Would a year of developmental kindergarten (DK) prior to kindergarten help my
child develop school readiness skills for kindergarten and beyond? Would delayed entry into
kindergarten result in long-term academic benefits? Will my child struggle more in kindergarten
because he was born later in the calendar year? Will my child be more likely to be retained if he
begins kindergarten when he isn’t “ready”? Rarely do parents turn to or have access to empirical
research to better understand whether their child is “ready” for kindergarten or if kindergarten is
“ready” for their child. Many parents and educators are also unfamiliar with the research base
pertaining to children who experienced delayed entry into kindergarten and those who did not.
Yet the age and time when a child begins kindergarten is a common decision that many parents
face and some parents still question long after their child has graduated high school.
In order to alleviate some of parents’ common fears related to the transition to
kindergarten, the Michigan Department of Education (MDE) has several online guides for
parents. For example, one guide is designed to help parents understand if their child is “ready”
for kindergarten. In this guide, the MDE (2013a) encourages parents to note that kindergarten
classrooms should be equipped to support all age-eligible kindergarten children – regardless of
ability. Moreover, children are not required to take a test to qualify to enter kindergarten (MDE
2013b).
Some children seem too young or not ready for school. Some families and teachers
believe that getting older will help the child get ready for kindergarten. This is not always
true; remember that children change a lot between May and September. (MDE, 2013a,
p.1)

2

In order to ease the transition to kindergarten and increase school readiness skills, some
children attend DK the year they are age-eligible for kindergarten. From the MDE’s perspective,
DK is considered a form of kindergarten retention and is reflected accordingly on a child’s
school records (MDE, 2013c). “Developmental kindergarten is intended to provide children who
are not ready with an extra year of schooling” (MDE, 2013c, p.1). In addition, the guide alerts
parents that DK attendance is not associated with academic, athletic, or social benefits and
increases a child’s chances of dropping out of high school. The information presented in this one
page guide seems to send mixed messages to parents about the outcomes associated with DK
attendance.
Although the information in the MDE guides tends to highlight the lack of established
benefits associated with DK, some parents choose to delay a child’s entry into kindergarten to
give their child a perceived cognitive or physical advantage over his peers, a practice commonly
called “redshirting” (Cascio, 2008; Deming & Dynarski, 2008; Lincove & Painter, 2006).
Redshirting, a term borrowed from the long-standing practice of delaying college athletic
involvement for a year to allow a player to hone his skills and maximize physical ability, affects
some children more than others as boys from affluent families are the most likely to be
“redshirted” (Deming & Dynarksi, 2008). The topic of “redshirting” has been rampant in the
popular press, with articles addressing the subject in publications such as the New York Times
(“Delay Kindergarten at Your Child’s Peril”; Wang & Aamodt, 2011) and the Chicago Tribune
(“Parents Bothered by Age Maximum in Chicago Schools”; Dizikes, 2011).
The evidence surrounding the academic outcomes associated with forms of delayed
kindergarten entry or kindergarten retention is mixed. Overall, research indicates that children
who are older than their peers tend to score better on academic assessments during first and

3

second grade but academic gains tend to fade over time (Robertson, 2011) and become
negligible by middle school (Domaleski & Oshima, 2006). Using a diverse sample, Stipek and
Byler (2001) found that children who entered kindergarten at a younger age initially did not
perform as well academically as their older kindergarten peers, but the differences in academic
achievement disappeared by third grade.
There is evidence that indicates young-for-grade kindergarten children stand to benefit
from the spillover effects of attending class with older peers and achieve the same long-term
outcomes as old-for-grade kindergarten children (Cascio & Schanzenbach, 2007). Elder and
Lobotsky (2009) found that the differences in kindergarteners’ achievement relative to their age
was not due to each child’s ability to learn material during the kindergarten school year, but
rather the perceived academic advantage older kindergarteners had was due to their increased
experiences and opportunities outside of the school setting.
However, other studies provide evidence for the long-term academic benefits of entering
school later. In a study of over 13,000 kindergarten children, children with birthdays close to the
kindergarten cutoff date scored lower on math and reading assessments than children with
birthdays far from the kindergarten cutoff date during kindergarten and first grade, and the
increased academic gains in older children were even more pronounced for boys and children
with disabilities (Datar, 2006). There is also international evidence indicating that young-forgrade students score lower on standardized tests in fourth and eighth grade compared to old-forgrade students (Bedard & Dhuey, 2006).
Children who are young-for-grade may also be at an increased risk for special education
eligibility or retention. In a study of 1474 disadvantaged first time kindergarten students, youngfor-grade children were at a greater risk for retention even after controlling for prior preschool

4

experience and literacy scores (Huang & Invernizzi, 2013). Research also indicates that children
with summer birthdays are more likely to receive special education services than older children
in their class (Dhuey & Lipscomb, 2010; Martin, Foels, Clanton & Moon, 2004). However, this
may be due to the relative nature of special education evaluations that typically compare children
to their grade level peers as opposed to a child’s absolute ability. Based on percentiles and other
standardized measures, children who are younger than their peers may appear to be struggling
academically more than their older peers even though the younger child’s actual ability may be
comparable to the older peer’s ability at an earlier point in time.
Regardless of age, children who possess school readiness skills upon kindergarten entry
experience better educational outcomes than children who do not possess school readiness skills
upon kindergarten entry (Snow, 2010). School readiness skills are comprised of both academic
skills and social-emotional skills, and the two types of skills are intricately intertwined with one
another. Preschool-age children who exhibit developmentally appropriate social-emotional skills
are less likely to exhibit externalizing or internalizing behaviors as adolescents (Bornstein, Hahn,
& Haynes, 2010) and more likely to maximize their cognitive abilities (Bornstein, Haynes,
O’Reilly, & Painter, 1996). Almost half of all young children lack school readiness skills prior to
kindergarten entry (Rimm-Kaufman, Pianta, & Cox, 2000) and transitional programs prior to
kindergarten are intended to increase students’ school readiness skills and help maximize their
academic success. Examples of school readiness skills include the ability to follow directions,
interact with other children, identify shapes and colors, and write one’s name (Raforth,
Buchenauer, Crissman, & Halko, 2004).
Risk factors for developing school readiness skills are most strongly associated with
poverty (Hair, Halle, Terry-Humen, Lavelle, & Calkins, 2006; Rimm-Kaufman, Pianta, & Cox,

5

2000; Hernandez, Denton, & Macartney, 2007) and prior preschool experience (Camilli, Vargas,
Ryan, & Barnett, 2010). Results of current research indicate that children from disadvantaged
backgrounds stand to benefit more from attending preschool programs than their advantaged
peers (Bumgarner & Line, 2014; Peisner-Feinberg & Schaaf, 2007). Research also indicates that
children from all socioeconomic backgrounds stand to benefit from attending high quality
preschool programs (Barnett, 2008;Burger, 2010; Goodman & Sianesi, 2005; Sylva, Melhuish,
Sammons, Siraj-Blatchford, & Taggert, 2004) and children from disadvantaged backgrounds
experience even more growth during preschool when they attend integrated preschool programs
with children from a variety of socioeconomic backgrounds (Hogden, 2007; Neidell &
Waldfogel, 2010; Schechter & Bye, 2007).
The National Early Literacy Panel (NELP) (2009) has identified alphabet knowledge,
phonological processing, rapid automatic naming of letters, digits, objects, and colors, and the
ability to write one’s name as some of the key indicators of school readiness related to early
literacy skills. Alphabet knowledge has been the strongest indicator of early literacy skills since
the 1960’s (Chall, 1967) and it continues to be the most salient modern indicator of early literacy
skills (NELP, 2009). Phonological processing skills, or the ability to break down and analyze the
smallest units of spoken language, are also crucial to the development of early literacy skills
(Anthony & Francis, 2005). Other variables that are moderately correlated with early literacy
skills are concepts of print, print knowledge, reading readiness, oral language, and visual
processing skills (NELP, 2009).
Developmentally appropriate social-emotional skills are also a critical component of
school readiness skills. In fact, social-emotional skills have been cited as being more important
than academic skills in relation to school readiness (Huey-Lin, Lawrence, & Gorrell, 2003).

6

Kindergarten teachers perceive children’s social skills as the most important school readiness
skills, above and beyond academic skills (Lin, Lawrence, & Gorrell, 2003). Current research
provides substantial evidence for the link between early social-emotional skills and short-term
and long-term academic success, reinforcing the reciprocal link between academic and socialemotional skills in children’s school readiness skills (Arnold, Kupersmidt, Voegler-Lee, &
Nastassja, 2012; Brennan, Shaw, Dishion, & Wilson, 2012; Dice & Schwanenflugel, 2012;
Razza, Martin, & Brooks-Gunn, 2012; Raver, 2004; Vallotton & Ayoub, 2011).
Children who have the ability to interact pro-socially with peers and form and maintain
friendships are more likely to be engaged in the classroom, enjoy attending school, and
maximize academic success (O’Connor & McCartney, 2007; Vitiello, Booren, Downer, &
Williford, 2012). Self-awareness, self-management, social awareness, and responsible decisionmaking are all components of social-emotional competence (Denham, 2010). Students who have
the skills to share, cooperate, and interact with other students are more likely to be successful in
kindergarten than students who have not already acquired those skills (Walker & Henderson,
2012). Children who lack appropriate social-emotional skills at the time of kindergarten entry
exhibit more externalizing behaviors and struggle more academically than their peers who have
acquired social-emotional skills (Raver, 2004).
In order to meet the increased cognitive demands that standardized tests require of
children in the later elementary years and beyond, kindergarten expectations have become more
rigorous and abstract in nature. For example, a typical kindergartner should be able to ask and
answer questions about details in text with support, compare and contrast the experiences of
characters in a story, and ask and answer questions about unknown words in text (MDE, 2013d).
In mathematics, kindergarten students should be able to count objects in a set, compare numbers,

7

and have a conceptual understanding of addition and subtraction. In addition, kindergarteners
should be able to create and identify shapes and analyze and compare shapes (MDE, 2013d). In
order to meet these heightened expectations, educators often recommend that children who lack
school readiness skills attend a year of DK prior to kindergarten.
In an increasingly competitive world, the increased academic outcomes often associated
with DK and “the gift of time” are compelling arguments to delay a child’s entry into
kindergarten even though the child meets the chronological age requirements. Developmental
kindergarten programs are used as one type of intervention to support young children’s academic
growth and transition to kindergarten, despite the lack of empirical evidence to support the
intervention. Little research on DK exists although DK programs continue to be popular in the
state of Michigan and other states. In a review of three types of kindergarten retention
(traditional kindergarten retention, DK, or transitional first grade), researchers found positive
academic effects during the intervention year but the positive effects faded over time (Karweit &
Wasik, 1992). Children who struggled with school readiness skills continued to struggle in
school, despite the kindergarten transition intervention (Karweit & Wasik, 1992).
Moreover, the evidence on programs such as DK is further complicated by research
indicating that for young children some skills are a result of schooling whereas others are a result
of biological maturation (Skibbe, Connor, Morris, & Jewkes, 2011). This makes it difficult to
disentangle the effects of an educational intervention such as DK from the effects of everyday
experiences children have as they grow older. Providing children with an additional “gift of
time” through intervention programs such as DK may or may not have all of the positive effects
educators and parents intend.

8

The purpose of this research study is to examine the influence of DK on later literacy and
social-emotional growth by comparing the growth of students who attended DK to those who did
not attend DK. Currently there is little empirical research to support the effectiveness of DK, a
specific type of early childhood intervention. Although the data were gathered from a large DK
program in a suburban school district in Michigan, the results of this study are intended to
provide objective data about the influence of DK and other variables commonly associated with
the transition to kindergarten on later literacy and social-emotional growth using a population of
students with minimal risk factors. In order to inform the research questions and methodology of
this study the following areas were addressed in the literature review: (a) historical early
childhood programs, (b) developmental kindergarten programs, (b) age of kindergarten entry, (c)
school readiness skills, (d) social-emotional skills and the relation to academic skills, and (e)
common curriculum based measurements used to measure academic progress.

9

CHAPTER 2
LITERATURE REVIEW
The goal of this study is to better understand the association between attendance in a DK
program and later literacy and social-emotional growth. This chapter provides an overview of
models of early childhood education, a rationale for the model chosen for this study, and a
review of selected historical early childhood programs. Next, DK programs are introduced and
then an overview of kindergarten age effects is presented. After that, the concept of school
readiness is introduced, followed by summaries of research of specific variables associated with
school readiness. Last, a summary of the development of early literacy skills is presented,
followed by an explanation of curriculum-based measurements and standardized tests used to
measure literacy achievement in kindergarten and beyond. The chapter concludes with a
reiteration of the purpose of the present study, its purported significance, and specific research
questions and hypotheses.
Definitions
Defining early childhood interventions is a complex task since educational
interventions vary at the local, county, state, and federal level. Some of the same early childhood
intervention terms such as pre-kindergarten (Pre-K) or DK have different meanings even in the
same Michigan county, making it difficult to use terms consistently in this literature review.
Throughout this paper, developmental kindergarten (DK) refers to an educational intervention
for children who are age-eligible for kindergarten but are delaying kindergarten entry by one
year.
Developmental kindergarten programs in Michigan are similar to Young Five’s
programs in Michigan, except DK programs are comprised of children who will be six years old

10

at some point in the school year. In contrast, Young Five’s programs are specifically designed
for children who turn five years old between September 1 and December 1 of the calendar year
(Michigan Department of Education, 2013b). Unlike other states, the state of Michigan does not
offer any type of transitional kindergarten prior the kindergarten year on a statewide basis.
Instead, the options vary based on the local school district.
The state of Michigan is in the process of revising the age requirements for
kindergarten entry. Prior to enacting the new legislation, children had to turn five by December 1
to enroll in kindergarten. Beginning the in 2013-2014 school year, children had to turn five by
November 1 to enroll in kindergarten. Children must turn five by October 1 to enroll in
kindergarten in the 2014-2015 school year, and beginning in the 2015-2016 school year, children
must turn five by September 1 to enroll in kindergarten. During this three-year time period,
parents or legal guardians may submit a written request to enroll their child in kindergarten if he
or she is too young to meet the revised age requirement but turns five by December 1. However,
the state of Michigan does not provide state aid to school districts for four-year old children
enrolled in kindergarten (MDE, 2013). Although awareness of early childhood education has
become more apparent, formalized plans for statewide prekindergarten have yet to be established
(Synder, 2014).
Other states such as California or Hawaii do have statewide transitional kindergarten
programs. For example, in California, in order to be eligible for the transitional kindergarten
program, a child’s fifth birthday must occur between October 2 and December 2 during the
2013-2014 school year and between September 2 and December 2 during the 2014-2015 school
year and subsequent school years. Parents who wish to enroll a child who is age-eligible for
kindergarten must make a specific request in writing if they wish to enroll their child in the

11

transitional program. The transitional kindergarten program is a two-year kindergarten program.
The first year is a modified kindergarten curriculum that is considered age appropriate and
developmentally appropriate. The transitional kindergarten school day parallels the kindergarten
school day in length and student to staff ratio, and the transitional programs are housed in public
schools alongside kindergarten classrooms. Funding for the transitional program is provided
through the same means as K-12 funding in the state of California (California Department of
Education, 2013).
Hawaii also currently funds an intervention prior to the kindergarten year. Under Act
219, parents residing in Hawaii had the option of enrolling their children who turned five years
old between August 2 and December 31 in Junior Kindergarten. The statewide Junior
Kindergarten program is a full-day program housed in public schools that uses a modified
kindergarten curriculum that is considered to be more age appropriate and developmentally
appropriate for younger children (Hawaii State Department of Education, 2013). In Hawaii, the
recent passage of Act 178 changed the kindergarten age-cutoff date beginning in the 2014 – 2015
school year from December 31 to July 31. Whereas Hawaii once had the latest kindergarten agecutoff date in the United States, they now have one of the earliest cutoff dates. Beginning in the
2014-2015 school year, the Junior Kindergarten program will no longer be available. Details of a
new plan and potential interventions prior to kindergarten will be available at the end of the 2013
legislative year (Hawaii State Department of Education, 2013).
Each of the 50 states has its own unique policies and programs related to the transition
to the formal K-12 education system. The three aforementioned states (Michigan, California, and
Hawaii) illustrate examples of differences in transitional programming across states. Moreover,
the current changes in Hawaii highlight the instability of many transitional early childhood

12

programs based on policy and funding changes at the state level. Rarely are programs formed
and revised based on applicable scholarly research in the early childhood literature; rather they
are often shaped and formed by the availability of resources and the perceptions of politicians. In
order to elucidate the complexity of early childhood definitions within the same state, a table is
provided below (Table 1) to highlight some of these differences and similarities in terms.
Although this is not a comprehensive list of all early childhood interventions available in all
counties in Michigan or other in states, it provides a snapshot of typical early childhood
interventions prior to kindergarten that are available in one Michigan county. In addition, it
highlights the multiple meanings associated with early childhood interventions.

13

Table 1
Early Childhood Interventions Available in one Michigan County
Program Name
Comprehensive Interventions

Definition

Funding Source

Typical Location

Michigan Early On

Designed for families with children 0 – 36 months
old. Children suspected of having a disability are
provided with screening and evaluation services.

Public

Varies based on evaluation
services needed

Early Head Start

Intervention provided to low-income expectant
mothers and to low-income families with children
under age 3. The program provides 90 minute
weekly home visits and bi-monthly socialization
opportunities.

Public – Must meet one of
several income requirements
or have a child in foster care
or a child with a disability

Home-based services; social
gatherings in community centers

Head Start

Preschool intervention for 3 and 4 year old
children from low-income families designed to
meet the physical, emotional, medical, and
educational needs of children and their families.

Public – Based on income
eligibility

Public Schools, community
centers, or faith-based
organizations

Bright Beginnings

Intervention designed for families of children from
birth to kindergarten that involves personal home
visits, playgroups and parent meetings,
developmental screenings and resource networks

Public – Free to all who
reside in the county

Homes and community centers

Private – Grants,
scholarships, and other
financial assistance
available for low-income
families to access daycares
that may otherwise be too
costly.

Faith-based organizations, private
businesses, homes

Non-academic Early Childhood Interventions
Childcare/Daycare

Safe spaces for children that meet their emotional
and physical needs from birth to kindergarten
entry.

Table 1 (cont’d)
Early Childhood Educational Interventions
Preschool

Any structured school experience for children ages
3 or 4 that may occur in a variety of settings for
varying lengths of time

Private

Faith-based organization or
private companies; also located in
homes and community centers

Early Childhood Special
Education (ECSE)

Under IDEA Part C (Birth – 2 & Ages 3 -21).
Early childhood education services for children
with developmental delays. Funding is provided
through IDEA. Services are available for children
from birth to age 21. Programs are usually housed
in public schools.

Public – Children must meet
eligibility requirements

Public Schools

Michigan Great Start
Readiness Program (GSRP)

Half-day preschool combined with half-day
daycare for at-risk 4-year olds. At-risk is defined
as living in a family with an income lower than
three times the poverty level.

Public schools or community
centers

Pre-Kindergarten

A half-day or full-day pre-kindergarten experience
designed for 4-year old children prior to the
kindergarten year.

Public – Limited number of
slots available and
preference is given to
children with the greatest
need
Private or public schools. In
public schools, there is
usually a limited number of
slots available and
preference is given to
children with the greatest
need.

Public

Public Schools

Also a half-day or full-day pre-kindergarten
experience prior to the kindergarten year for
kindergarten-age-eligible children who may lack
the school readiness skills associated with success
in kindergarten.
Young Five’s

A full day kindergarten experience that occurs the
year before kindergarten and is designed for
children who were born late in the calendar year
who may benefit from delaying kindergarten entry
by one year.

15

Public or private schools or
community centers

Table 1 (cont’d)
Developmental Kindergarten

Accelerated Kindergarten

Kindergarten

A half-day program designed for children who are
age-eligible for kindergarten that occurs prior to
the kindergarten year. The program is designed for
kindergarten-age eligible children who may lack
the school readiness skills associated with success
in kindergarten.
Kindergarten classrooms composed of children
who are age-eligible for kindergarten. Children are
grouped into classes based upon the period of the
year in which they were born. Accelerated content
is based on the age of the children, with the oldest
children experiencing the most advanced content.

Public

Public Schools

Public

Public

First year of formal education available to all
students who turn 5 years old by November 1
(2013 – 2014 school year), October 1 (2014-2015
school year), and September 1 (2015 – 2016
school year).

Public or Private

Public or Private Schools

*Please note. This table is not representative of all Michigan counties. Early childhood interventions vary at the local, county, state, and federal level.

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Theoretical Models
The formation of federal and state policies related to the transition to kindergarten has
been formed and shaped during the past century by several different models. The major models
associated with the kindergarten transition are outlined below and are intended to help the reader
contextualize current transitional kindergarten practices in light of one of the most contemporary
frameworks.
Maturational Model. The oldest model of child development is the maturational model
which originated from the work of Charles Darwin (Gessell, 1929). According to the
maturational model, children are ready to begin the formal education process after they have
achieved certain developmental milestones (Hothersall, 2004). The maturational model espouses
that development follows a predetermined course and sequence as long as the environment
supports the established biological sequence (Hothersall, 2004). Examples of programs resulting
from the maturational model of early childhood development include programs such as
transitional kindergarten or DK.
Comprehensive model. Research from the 1940’s and 1950’s provided evidence for the
effectiveness of early intervention for children with learning disabilities, challenging the
maturational model (Kirk, 1958). Data indicated educational interventions had the ability to alter
the course of biological development. According to the comprehensive model (Cook, Klein,
Tessier, & Daley, 2011), a child’s physical, emotional, and medical needs must be met alongside
the child’s educational needs. Under this model, comprehensive services are provided to both
children and their families to provide children with the supports and services they need to
maximize their success (Cook et al., 2004). Comprehensive models of early childhood education
programs were established during the 1960’s in response to President Lyndon B. Johnson’s War

17

on Poverty and other policy initiatives. Examples of programs using the comprehensive models
of early childhood education are the Carolina Abecedarian Project, Chicago-Parent Centers, and
Head Start.
Bronfenbrenner’s Bioecological Model. Urie Bronfenbrenner developed a
bioecological theory of child development in the late 1970’s that combined elements of the
maturational and comprehensive models of child development. Bronfenbrenner’s bioecological
theory of development continues to be a prominent theory in child development and education.
His bioecological theory was first published in 1979 and a more recent edition of the book,
Making Human Beings Human: Bioecological Perspectives on Human Development, was
published in 2005. According to Bronfenbrenner’s bioecological theory, “The characteristics of
the person at a given time in his or her life are a joint function of the characteristics of the person
and of the environment over the course of that person’s life up to that time” (Bronfenbrenner,
2005, p.108). Development is determined by the genetic characteristics of a person, as well as his
or her environment. Ecological niches, or places in the environment that are particularly
favorable or unfavorable to development depending on the specific characteristics of individuals
are instrumental in shaping development (Bronfenbrenner, 2005).
Developmental Model of Transition. The model chosen for this study is the
developmental model of transition (Pianta & Kraft-Sayre, 2003). The developmental model of
transition specifically focuses on the transition from prekindergarten educational and social
experiences to the more formal social and academic expectations of kindergarten and beyond.
The developmental model of transitional (Figure 1) incorporates the same consideration of a
child’s biological characteristics and the social forces in multiple contexts highlighted by
Bronfrenbrenner’s bioecological theory; however, the unique aspect of the developmental model

18

of transition is the changes in the relationships among and between contexts and individuals
across settings during the transition from prekindergarten experiences to kindergarten. Under this
model, the transition to kindergarten is a process girded by four tenets: schools being ready for
children, community collaboration and support, family participation and knowledge, and the
availability of high quality early childhood care settings (Pianta & Kraft-Sayre, 2003).

Figure 1
Developmental Model of Transition
From Pianta & Kraft-Sayre (2003, p.8)
Historical Early Childhood Programs
In order to understand contemporary dilemmas and debates in early childhood, it is
important to understand the evolution of early childhood education in the United States of
America. American citizens realized the benefit of public education for children beginning
around 1825, and the field of education has experienced several paradigm shifts since that time
(Merrell, Ervin, & Gimpel-Peacock, 2012). Although almost 120 years have passed since the
first child’s guidance clinic was formed – often considered the earliest early childhood
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intervention (Merrell et al., 2012) - many scholars, educators, policy makers, and American
citizens are more formally invested in maximizing young children’s learning outcomes. More
recently, the evidence-based movement has drawn attention to the importance of early childhood
education. The 1983 report, “A Nation at Risk,” brought attention to the achievement gap
between American students and students in other industrialized countries. In 1989, the National
Education Goals 2000 initiative was drafted and in the early 1990’s, the National Goals Panel
broadened the definition of school readiness. In 2001, the No Child Left Behind Act was passed,
mandating more accountability in education (Winter & Kelley, 2008).
As American policy makers and educators grappled with funding and implementing the
most effective early childhood interventions in the twentieth century, earlier programs were
influential in providing a research base to support the existence of early childhood education. A
handful of large-scale early childhood interventions implemented in the twentieth century have
shaped the way in which scholars, educators, and practitioners think about early childhood
educational programs and the transition to formal schooling in relation to the evidence-based
movement. A summary of some of the most notable American early childhood interventions
follows including the High/Scope Perry Preschool Project, Carolina Abecedarian Project,
Chicago Parent Centers, and Head Start.
High/Scope Perry Preschool. The High/Scope Perry Preschool Project was a study in
Ypsilanti, Michigan that lasted two years. The project was created in the early 1960’s to address
the high percentage of young children in the school district who were retained in the early
elementary years. Participants in the study were 123 African American children age three to four
years old living in poverty. Children attended preschool for half a day every weekday, and
received home visits during the school year. Children were in classes with a small teacher to

20

student ratio, and all teachers had a master’s degree and training in child development. The
approximate cost per child was $12,884 per year (Schweinhart, 2003).
When children in the study reached 27 years of age, results of longitudinal analyses
indicated that for every one dollar spent on the program over seven dollars were saved in public
tax expenditures (Barnett, 1996). Many of these cost savings were associated with increased
educational attainment and employment. For example, compared to children in the control group,
children in the High Scope Perry Preschool project spent less than half of the time in classrooms
for students with cognitive impairments. In addition, children in the High Scope Perry Preschool
Project out-performed the control group on a school achievement test at age 14 and a literacy test
at age 19 (Schweinhart, 2003). At age 40, the children who attended the preschool were more
likely to have completed high school, hold a job, and earn more than a comparison group of
children who did not attend the preschool (Schweinhart, 2003).
Carolina Abecedarian Project. The Carolina Abecedarian Project was designed to
provide low-income children with high quality early childhood care (Campbell & Ramey, 1994).
Researchers recruited participants between 1972 and 1977. One hundred nine families (111
infants) took part in the study and participants were assigned to the experimental group or the
control group. All participants met poverty guidelines and 98% of participants were African
Americans. Most mothers were young (i.e. average age was 20 years), unmarried, had less than a
high school education, lived in a multigenerational house, and did not have any reported income.
The experimental group was divided into two groups. One group received an early childhood
intervention only, whereas the other group received an early childhood plus a school-age
intervention. The early childhood intervention consisted of all day, year round childcare with
developmentally appropriate activities. Families receiving the school-age intervention had a

21

home-school resource teacher who served as a liaison between the school and the family. Parents
received curriculum packets to enhance skills that their children needed more assistance with.
One hundred five children were available for a follow-up study at age 21. The young
adults who received either of the interventions as children had higher cognitive scores, higher
academic achievement scores, completed more years of schooling, were more likely to delay
childbearing, and were twice as likely to attend a four year college or university than children in
the control group (Campbell & Ramey, 1994). Taken together, results of the study indicated that
not only did children in the study experience an increased quality of life during childhood, the
children achieved higher educational and occupational outcomes as adults than the comparison
group.
Chicago Child-Parent Centers. The Chicago Child-Parent Center intervention is
considered a “program that works” on the Promising Practices Network
(www.promisingpractices.net, 2012). The program was created in 1967 and continues to provide
comprehensive educational services to preschool children living in low-income neighborhoods in
Chicago. The program is part of the Chicago Public School System and fosters preschool
children’s cognitive and social growth through individualized education programs that require
parental involvement (www.promisingpractices.net, 2012).
Participants in the first Chicago-Parent Centers study were 1,539 low-income minority
children (93% Black, 7% Hispanic) who were born in 1979 or 1980. The intervention consisted
of a half-day preschool program for three and four year old children, a half day or all-day
kindergarten program, and two or three years of interventions in elementary schools (Reynolds &
Temple, 2008). Results of the study provided relevant insight into factors mediating long-term
school performance including attending a high-quality elementary school, experiencing low

22

mobility, having higher literacy scores in kindergarten, and being promoted to the next grade
(Reynolds & Temple, 2008). For example, the effect of preschool was negligible if a student
attended a high-quality elementary school as opposed to a low-quality elementary school. The
effect of preschool also diminished if children remained in the same elementary school instead of
attending multiple elementary schools.
Results of longitudinal analyses indicated participants who participated in the Chicago
Parent Center Preschool attended school longer and had lower rates of juvenile arrests.
Compared to the comparison group, children receiving the intervention had a 29% higher rate of
high school completion, 41% reduction in special education placement, and 40% reduction in
grade retention. Moreover, children in the control group earned more as adults (Reynolds, 2000).
Head Start. Head Start is a national program that promotes positive child development
outcomes by enhancing the social, emotional, cognitive, and physical development of children
through the provision of educational, health, nutritional, social and other services to students and
their families (Office of Head Start, 2010). Head Start programs have been in existence since the
1960’s and continue to maintain a steadfast presence in early childhood interventions. The Head
Start Reauthorization Project (2007) provides increased funding for Head Start and allows for
future expansion of the program. In 2013, federal funds for Head Start were appropriated at $7.5
billion and provided enrollment for nearly one million American children (Head Start, 2013).
In addition to securing funding, the Head Start Reauthorization Project (2007) also
seeks to improve Head Start teacher quality and teacher retention. Currently, approximately onethird of Head Start teachers have a Bachelor’s degree, and one-fourth of teachers have an
Associate’s degree. Over time, all newly hired teachers will have a Bachelor’s Degree and

23

current teachers who do not have a bachelor’s degree will receive financial assistance to return to
school (National Association for the Education of Young Children, 2009).
In addition to educational experiences, Head Start students receive preventative medical
care and nutritious meals and snacks. Students interact with their peers during structured
preschool activities as well as creative-play and gross motor activities. Parents or guardians of
children in Head Start also receive support services through parent education courses, family
nights, access to social workers, and interactions with Head Start staff. Family nights provide
families with information about creating healthy parent and child relationships and ways to
enhance student learning in the home setting (Head Start, 2013).
Research on the effects of Head Start has indicated positive educational, occupational,
and quality of life outcomes. In a non-experimental study examining income data, adults who
attended Head Start in the late 1960’s and early 1970’s had different outcomes than their peers
who did not attend Head Start. Caucasian adults who attended Head Start were more likely to
finish high school, attend college, and report higher earnings than their peers who did not attend
Head Start. Former Head Start students of African American descent were less likely to be
charged with a crime, and more likely than their siblings who did not attend Head Start to finish
high school (Garces, Thomas, & Currie, 2000).
Recently, researchers completed the first longitudinal study of children enrolled in Early
Head Start. The longitudinal study began in 1995 with 3,001 children and families enrolled in an
Early Head Start Program (Kisker, Paulsell, Love, & Raikes, 2002). Researchers assessed
student outcomes when students finished pre-kindergarten, and they will assess students again
when they have completed fifth grade. Current trends in this longitudinal study on Early Head
Start students pointed to several positive trends in child outcomes. Children receiving Head Start

24

services exhibited greater cognitive and language development and social-emotional
development. In addition, parents reported more positive parental behaviors (Kisker et al., 2002).
It is important to note that many of the previously mentioned large-scale interventions
such as Head Start have several commonalities that all early childhood programs may not
possess. For example, the large-scale programs began early in the child’s life, had well-educated,
well-trained, and well-compensated staff, utilized small class sizes and high teacher-child ratios,
and provided intensive services. In addition, the interventions had a distinct purpose, focused on
the whole child, provided children with direct instruction as well as experiential learning
opportunities, and provided teachers time to reflect on their own teaching practices and their
students’ progress (Galinsky, 2006).
Developmental Kindergarten Programs
In an era of education reform and an emphasis on accountability, the presence of early
childhood transitional programs stands in the middle of several social, political, and educational
debates (Zigler, Gilliam, & Barnett, 2011). Although DK programs vary in structure, length,
curriculum, and theoretical orientation, the overarching purpose of DK programs is to create a
smoother transition into the more structured and demanding kindergarten classroom. Transitional
kindergarten programs are known by many different names, such as “DK,” “Pre-Kindergarten”
(Pre-K), “Begin-a-garten,” and “Young Fives” (Meisels, 1992). Kindergarten marks the first year
of formal schooling in the K – 12 school system and is associated with increased academic rigor,
higher student to teacher ratios, increased social expectations, and less dependence on the teacher
and other adults in the classroom (Rimm-Kaufman et al., 2000).
This study focuses on one very specific type of transitional program - DK. The purpose,
existence, and age requirements of DK programs vary from state to state. For example, students

25

in many DK programs are typically age-eligible for kindergarten but were not yet “ready” to
begin kindergarten for a variety of reasons (see Table 2). In the district under investigation
within this study, the district requirements for DK were slightly different. Specifically, students
who are not age-eligible for kindergarten are not eligible to enroll in the DK program. These
requirements are more consistent with the maturational view of child development. In other
states such as Oklahoma, Pre-K programs are universal preschool programs for all four-year-old
children residing in the state. These children are not age-eligible to begin kindergarten
(Oklahoma State Department of Education, 2013). However, in everyday conversation, the terms
Pre-K and DK are often used interchangeably even though they may mean different things
depending on the state and local context.
Table 2
Similarities and Differences Between Pre-K and DK
Both Pre-K and DK are
Pre-K is…
designed to…
Foster and develop school
readiness skills
Ease the transition to
kindergarten

Enhance learning in
kindergarten and beyond

The DK program in this study is…

Designed for children who
are not yet age-eligible for
kindergarten
Designed for children who
are three or four years old,
depending on the program

Designed for children who are ageeligible for kindergarten

A type of preschool
followed directly by
kindergarten

Often occurs between preschool and
kindergarten (although preschool
attendance is not required to attend
DK)

Designed for children who are
already five years old (or will turn
five years old by the fall
kindergarten cutoff date)

Provide children with
Typically in private or
developmentally appropriate public schools
structure and activities

Typically in public schools

Serve as an early childhood
intervention.

Delaying a child’s entry into
kindergarten.

Not delaying a child’s
entry into kindergarten.

26

For example, Magnuson, Ruhm, and Waldfogel (2007) used data from the Early
Childhood Longitudinal Study (ECLS) to study the effects of Pre-K programs across the country.
Results of the study indicated Pre-K programs were more effective for disadvantaged children
than non-disadvantaged children. Overall results indicated that Pre-K attendance did not have
long-lasting effects on children’s skills by the end of the first grade year. However, Pre-K
attendance was associated with long-term adverse effects on aggression and self-control
(Magnuson et al., 2007).
In a multi-state study of Pre-K programs, Clifford et al. (2005) found that Pre-K
programs vary in structure, content, and quality. For example, results of the study indicated that
approximately half of Pre-K programs are half-day programs, whereas the other half are full day
programs; half of publicly funded Pre-K programs are housed in public schools, while the other
half of programs are housed in churches or community centers (Clifford et al., 2005).
In another effort to learn more about existing Pre-K programs, the National Center for
Early Development & Learning (NCEDL) conducted a survey (Bryant et al., 2002). One hundred
twenty five respondents were interviewed between August 200 and March 2001. Results of the
survey indicated that 34 states had state-funded Pre-K programs serving approximately 740,000
children, but the programs varied widely across states. The programs served three and four year
old children and most of the programs were intended for at-risk children. Pre-K programs were
located in a variety of venues, including public schools, community centers, and daycares. Pre-K
classes were held for as little as 2.5 hours to as long as 10 hours a day for nine to ten months per
year. Teacher qualification requirements ranged from a two-year Child Development Associate
certificate to a bachelor’s degree with teacher certification (Bryant et al., 2002). Although the

27

data gathered from this survey is important, it does little to further the research for DK programs
designed for children who are eligible for kindergarten based on age requirements.
In another study with a sample of 2800 randomly selected four-year-old Pre-K students
across 11 states, researchers found differences based on classroom quality. Data for the study
were obtained from the National Center for Early Development and Learning Multi-State Study
of Pre-Kindergarten and the State-Wide Early Education Programs Study. Individual measures of
academic achievement were obtained using the Peabody Picture Vocabulary Test, the Oral &
Written Language Scale, and the Woodcock Johnson Test of Achievement: Applied Problems
Subtest. Children from both advantaged and disadvantaged families made small academic gains
but overall literacy scores at the end of the Pre-K year were still below the national average.
Children showed the greatest gains in academic skills when they were in high quality Pre-K
classrooms or had a close relationship with the teacher (Howes et al., 2008).
LoCasale-Crouch and colleagues (2007) examined the classroom quality of 692 Pre-K
classrooms in 11 states. Classroom teachers were rated on the level of social emotional support
and instructional quality and each classroom was placed in one of five categories. Results of the
study indicated only 15% of classrooms fell in the highest quality profile (high level of
instruction and high level of emotional support) and 19% of classrooms fell in the lowest quality
profile (lowest level of instruction and lowest level of emotional support). The lowest quality
classrooms contained classrooms with the highest percentage of minority children and the lowest
level of maternal education, indicating the most at-risk students were in the lowest quality
classrooms (LoCasale-Crouch et al., 2007).
Burchinal and colleagues (2010) used data from the National Center for Early
Development and Learning’s Multi-State Pre-K study to better understand the effect of program,

28

classroom, and teacher characteristics that predict classroom quality and teacher child
interactions. The study included 238 Pre-K classrooms in six states. High quality classrooms
were most closely associated with specific teacher and child attributes, such as teacher attitudes
and beliefs. Low classroom quality was associated with greater than 60% of the students in the
classroom living in poverty, low level of teacher education, and authoritarian teaching styles
(Burchinal et al., 2010). The works of Howes et al. (2008), LoCasale-Crouch et al. (2007), and
Burchinal et al. (2010) further illustrate the complexity of factors that influence the outcomes of
early childhood interventions.
Oklahoma is considered the nation’s leader in adopting a universal Pre-K program (Rose,
2011). From the early 1980’s to the late 1990’s, the state of Oklahoma implemented the
universal program quietly and slowly (Rose, 2011). The Oklahoma Pre-K program is particularly
remarkable since Pre-K teachers receive the same compensation as K-12 teachers and the Pre-K
programs are seamlessly meshed with the existing K-12 system (Phillips, Gormley, &
Lowenstein, 2009). Oklahoma’s prekindergarten classrooms are also recognized for their high
quality instructional and emotional supports (Phillips et al., 2009). Few states, if any, have
matched Oklahoma’s high-quality, universal Pre-K program.
In a study designed to examine the effects of attending Oklahoma’s Pre-K program,
researchers sampled 1,567 pre-K children who just began attending the Pre-K program and 1,461
children who recently completed the Pre-K program. Results of the study indicated that students
who just completed Pre-K scored 3 points higher on the word-identification score, 1.86 points
higher on the spelling score, and 1.94 points higher on the applied problems score of the
Woodcock Johnson Achievement Test. Scores improved for Hispanic, Black, White, and Native
American children (Gormley, Gayer, Phillips, & Dawson, 2005). Although children who

29

attended the Pre-K program scored higher on achievement tests measures, the increased scores
may not be practically significant. As states continue to work with smaller and smaller
educational budgets, the practical significance of effect sizes of early childhood programs is of
more and more importance.
In contrast to Oklahoma’s grass roots Pre-K program, the Supreme Court’s decision in
Abbott v. Burke (1985) mandated preschool education for all three and four year old children in
31 school districts across the state of New Jersey. These Pre-K classrooms were named the
Abbott Pre-K programs. The court decision was a landmark decision since it was the first court
ruling mandating early childhood education (Frede, Jung, Barnett, & Figueras, 2009). In 2002,
Governor James McGreevy required the state of New Jersey to develop a plan to monitor and
commit to continuous quality improvement initiatives, and the state developed the Early
Learning Improvement Consortium (ELIC) to collect and analyze data pertaining to the Pre-K
program (Frede et al., 2009). Results of studies of the Abbott Pre-K program indicated classroom
quality improved over time. At the end of second grade, students enrolled in the Abbott Pre-K
program were less likely to be retained and have increased mathematics and language scores than
a comparison group of children (Frede et al., 2009).
Some states with Pre-K programs have published documents available online that outline
the program goals and content. In Nevada, early childhood specialists from states across the
country are working with the Council of Chief State School Officers to align state Pre-K
standards with the common core standards. Nevada has statewide Pre-K content standards in the
following domains: cognition and general knowledge, language development and
communication, personal and social-emotional development, creative expressions/experiences,
and physical development and health (Nevada Pre-K Standards, 2010).

30

New Mexico educators emphasize the importance of providing developmental
kindergarten students with developmentally appropriate structure and activities, helping to
facilitate a smooth transition from developmental kindergarten to kindergarten (New Mexico’s
Early Learning Outcomes, 2006). Michigan has published standards for developmental
kindergarten programs in the document, Early Childhood Standards of Quality for
Prekindergarten (Michigan State Board of Education, 2005). Examples of some of these
standards are outlines in Table 3. The Collaborative for Academic, Social, and Emotional
Learning (CASEL, 2013) has the social-emotional learning standards available for transitional
kindergarten programs for the 48 states that have published social-emotional standards.

31

Table 3
Examples of Michigan Early Childhood Standards of Quality for Pre-Kindergarten
Domain
Program Standard
Statement of Philosophy
Program Standard: A written philosophy
statement for the early childhood education
and care program is developed and utilized
as the basis for making program decisions
and establishing program goals and
objectives.
Community Collaboration and Financial
Support

Program Standard: The program shows
evidence of participation in cooperative
efforts within the community and has
membership on the community’s early
childhood collaborative council.

Physical and Mental Health, Nutrition and
Safety

Program Standard: Programs address the
need for continuous accessible health care
(mental, oral, physical health, and fitness)
for children.

Staffing and Administrative Support and
Professional Development

The Partnership with Families

Indicator Example
Develops a philosophy that
incorporates suggestions from the
program’s staff (teachers,
administrators, and support staff),
governing board, families, and
community representatives.
Participates in the development of
a common community philosophy
of early childhood expectations.

Provides information and referral
for parents of children to health
care partners for preventive and
primary health and mental health
care needs and coverage.
Program Standard: Teachers are qualified to Employs teachers with bachelor’s
develop and implement a program consistent degrees in early childhood
with the program philosophy and appropriate education, or child development,
to the developmental and learning needs of
including coursework and
the children and families being served,
supervised field experience.
including the development of a continuing
parent education and family involvement
component.
Program Standard: Families have multiple
opportunities for regular involvement with
the program and its staff including
32

Enables the family to take part in
the decision making process
related to the child’s participation

Table 3 (cont’d)
placement, planning for individualization
and evaluation related specifically to their
child.
The Learning Environment

Program Standard: The curriculum is
designed to include experiences related to
children’s social, emotional, intellectual,
language, creative, and physical
development.

Child Assessment and Program Evaluation

Program Standard: The program uses
information gained from a variety of
assessment measures to plan learning
experiences for individual children and
groups.

in the program, so program goals
and expectations and goals for
their child and family can be met.
Assures that children have
experiences to enhance their social
development, including the
acquisition of interpersonal skills,
self-discipline, caring, and respect
for others.
Uses sound developmental
learning theory to plan and conduct
child assessment.

Michigan State Board of Education: Early Childhood Standards of Quality for PreKindergarten (2005)

33

Despite the increased availability and visibility of standards for some transitional
kindergarten programs, the purpose of transitional programs is often difficult to ascertain.
Transitional kindergarten programs that exist under the guise of kindergarten retention or
delayed entry into kindergarten are distinctly different than those that exist as universal
preschool for three or four year old children. It is important to advance the research base for DK
programs that are used as an intervention year when the child is already five years of age in order
to have a better understanding of the most effective types of early childhood programs.
Although studies of well-known, intensive early childhood programs indicate that the
programs are successful in both long-term and short-term outcomes, there are still inconclusive
results about the specific components of early childhood programs that maximize results (Zigler,
et al., 2011). In addition, little is known about the specific types of early childhood programs that
work the best for different specific groups of children. For example, results of the 2009 Head
Start Family and Child Experiences Survey indicated that children in Head Start enter and exit
the program with scores in English language, literacy, and math that are below national norms
(Aikens, Kopack, Tarullo, & West, 2013).
Additionally, it is difficult to accurately assess the current cost-benefit ratios for early
childhood programs since some programs have the capability to complete more long-term
longitudinal studies than others (Kilburn & Karoly, 2008). The benefits of early childhood
programs may decline over time and paying close attention to the amount of time required for an
early childhood intervention to maximize long-term outcomes is important. Although calculating
cost/benefit ratios is not the purpose of this study, adding to the research base pertaining to the
long-term outcomes of DK is important to assist in future policies and programs shaping the
transition to kindergarten.

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Age at Kindergarten Entry
Redshirting. The age at which children begin kindergarten is changing and is an
important factor in the kindergarten entry decision-making process. The availability of
transitional kindergarten programs and societal expectations have delayed some children’s entry
into kindergarten. “Redshirting” is the original term used to describe delaying a college athlete’s
participation in athletics until the athlete was bigger and stronger. Many parents choose to
“redshirt” their preschool-aged child and delay kindergarten entry by one year in order to
potentially boost their child’s academic and/or athletic success and provide their child with “the
gift of time” (Deming & Dynarksi, 2008). The practice of redshirting is considered a “zero-sum”
game because it is inevitable that one child will be the youngest and one child will be the oldest
in any given class (Deming & Dynarksi, 2008). Nearly every state has increased the age at which
children can enter kindergarten, even though research indicates that beginning school later is
associated with decreased educational attainment. Although many point to the mandated
standardized testing movement of the 1990’s as the proponent of redshirting, redshirting began in
the 1980’s; surprisingly, 75% of the decisions to redshirt students are due to parent and educator
choice as opposed to changes in state law regulating the age of kindergarten entry (Deming &
Dynarksi, 2008).
The practice of delaying kindergarten entry has become more widespread. For example,
in the 1970’s, approximately 10% of 18-19 year-olds were enrolled in high school. In 2005,
approximately 18% of 18-19 year-olds were enrolled in high school. Older high school graduates
often have several characteristics in common. The majority of 18-19 year-old high school
students are male, from affluent families, and of Caucasian or Asian descent (Deming &
Dynarski, 2008).

35

There are several interpretations to the large age gap among kindergarten children.
Cascio (2008) outlined three common interpretations of the entry-age achievement gap. The first
interpretation is that older kindergarten students have an advantage since they are physically
larger and smarter than their peers. The older students tend to be tracked into top-performing
reading groups and continually experience more advanced academic material in the early years
than their classroom peers. Another interpretation is that older students have been exposed to
enriching environments and academic material for a longer time than their younger peers and are
better equipped to succeed when they enter school. Last, those who enter school late are older
when they take standardized tests and their enriched and longer life experiences may contribute
to success on standardized measures of academic performance (Cascio, 2008).
Perceived Gains Fade Over Time. Although studies have drawn various conclusions
about the age at kindergarten entry, most of the initial gains due to birthday fade over time
(Robertson, 2011). Researchers used data from the Early Childhood Longitudinal Study (ECLS)
(Kindergarten class of 1998-1999) to examine the effects of age on academic achievement
(Domaleski & Oshima, 2006). First-time kindergarten students with early birthdays (June, July,
and August) were compared to first-time kindergarten students with late birthdays (September,
October, and November). The age gap of these students was approximately seven to eleven
months. Analyses indicated that the effect size (ES) for children with older birthdays compared
to children with younger birthdays was .38 for reading, .55 for mathematics, and .50 for general
knowledge. There was a rapid decrease in the ES for children up to third grade, a more gradual
decline in fourth and fifth grade, and virtually no difference in scores in middle school. Reading
scores were higher for girls than boys across kindergarten through eighth grade and gender
differences were not apparent in mathematics scores (Domaleski & Oshima, 2006).

36

Additional studies have documented the same decline in birthday effects over time. In a
study of 237 children from low-income families from three diverse sites (rural, predominantly
Caucasian; urban, predominantly African American; and urban, predominantly Latino),
researchers found that children who entered kindergarten younger than their peers performed less
well academically initially. However, by third grade there was not a difference in academic
achievement based on age (Stipek & Byler, 2001).
Lincove & Painter (2006) used data from the National Educational Longitudinal Survey
to determine the effects of age of entry on later academic performance. Results of their study
indicated redshirting does not improve student outcomes and age has little long-term effects on
academic or social success. Furthermore, students who enter kindergarten early may have an
advantage because they have an additional year in the workforce (Lincove & Painter, 2006).
Parents and teachers are often more aware of the salient short-term effects of delayed
kindergarten entry that are evident in the early elementary years and less aware of the negligible
or negative long-term effects of delayed kindergarten entry.
In another study by Cascio & Schanzenbach (2007), data were used from the United
States – Tennessee’s Project STAR (Student Teacher Achievement Ratio) study to better
understand the effects of relative age among kindergarten students. Unlike other studies
examining the effects of age at kindergarten entry in which parents or administrators may have
lobbied for a student to wait a year to begin kindergarten, Project STAR students were randomly
assigned to kindergarten classrooms. Results of the study indicated that students who entered
kindergarten at a younger age benefitted more than students who entered kindergarten at an older
age. The younger children benefited positively from the “spillover” effects of being in class with
older peers. Compared to older students, the younger students performed similarly on

37

achievement tests across elementary and high school, were not any more likely to be retained,
and just as likely to take future standardized tests such as the ACT or SAT. Moreover, the study
found that the positive effects associated with age were more related to the absolute age of the
child as opposed to the relative age advantage in comparison to other children in the classroom
(Cascio & Schanzenbach, 2007).
Elder & Lubotsky (2009) used data from the Early Childhood Longitudinal Study
kindergarten cohort (ECLS-K), and the National Educational Longitudinal Survey of 1988
(NELS:88) to better understand the correlation between age at which children begin kindergarten
and later academic achievement. The positive association between age at kindergarten entry and
academic achievement was due to skills acquired prior to entering kindergarten and not due to
older peers’ ability to learn more rapidly than their younger peers during the school year. In
addition, Elder & Lobotsky (2009) found that the relationship between age at kindergarten entry
and later academic achievement is greater for children from more privileged backgrounds than
children from less privileged backgrounds. Results of the study also suggested that the spillover
effects of attending school with older peers increased test scores, but also increased the
probability that a student would be retained or diagnosed with a learning disability. Researchers
concluded that delaying entry into kindergarten postpones learning and does not have any longterm benefits, especially for children from low SES backgrounds whose primary learning
opportunities occur in public school classrooms (Elder & Lobotsky, 2009).
Kindergarten Retention
Kindergarten retention is a unique construct. Unlike retention in later grades, the delay of
entry into kindergarten can be considered a form of kindergarten retention. As previously
discussed, “redshirting” is a common phenomenon some parents use to give their children a

38

perceived advantage in kindergarten. Other children might experience delayed entry into
kindergarten due to a lack of school readiness skills and attend a transitional program (such as
DK) to prepare for kindergarten. In essence, delaying a child’s entry into kindergarten –
regardless of the reason- is a form of retention.
Comprehensive reviews of retention research spanning nearly a century indicate that
retention does not have positive effects (Holmes & Mathews, 1984; Holmes, 1989; Jimerson et
al., 2006, Allen et al., 2009) and early grade retention is one of the best predictors of later school
withdrawal (Jimerson, Anderson, & Whipple, 2002). Despite the research evidence, retention is
still an accepted practice due to political influences extending back to the Clinton
Administration. President Bill Clinton called for an end to social promotion in his State of the
Union addresses in 1997, 1998, & 1999 and the No Child Left Behind Act of 2001 enacted during
the George W. Bush Administration has also led to increased accountability and retention (Hong
& Raudenbush, 2006).
Interestingly, demographic characteristics are more associated with retention than actual
academic achievement. Decades of retention research indicate that boys are twice as likely to be
retained as girls, and children who are retained are more likely to have mothers with lower IQ
scores, poor attitudes toward school, and low parental involvement. In addition, African
American and Hispanic students are more likely to be retained than Caucasian students, and
students who have social-emotional difficulties are more likely to be retained than students who
do not (Hong & Yu, 2007; Jimerson et al., 2006).
One of the largest kindergarten retention studies to date by Hong & Raudenbush (2006)
consisted of 471 kindergarten retainees and 10,255 promoted students in 1,080 schools drawn
from the ECLS-K data set. Researchers used hierarchical linear modeling to account for

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schooling effects. Results of the study indicated that kindergarten retention did not improve
reading or math achievement regardless of whether a child attended a school with a high or low
retention rate. Children who were retained in kindergarten learned less than their similarly
performing peers who were not retained in kindergarten (Hong & Raudenbush, 2006). Hong &
Raudenbush (2006) concluded that there was no empirical support for kindergarten retention and
the kindergarten retainees would have learned more if they would have been promoted to first
grade.
However, some advocates of retention believe that retaining kindergarteners will allow
them to excel in the long run. Hong & Yu (2007) sought evidence using the ECLS-K data to
either provide support for or refute this claim by comparing the math and reading achievement in
3rd and 5th grade of students who were either promoted or retained in either kindergarten or first
grade. Data for the study were compiled from six waves of ECLS-K longitudinal data
(n=21,409). Due to attrition, the sample size for the study consisted of 471 kindergarten retainees
and 10,255 kindergarten students promoted to first grade, and 201 first grade retainees and
10,707 first graders promoted to second grade. Hong & Yu (2007) found that the achievement
gaps were the largest when the kindergarten retainees finished their second year of kindergarten.
At the end of their second year of kindergarten, the kindergarten retainees were 1.58 standard
deviations behind their promoted counterparts in reading and 1.35 standard deviations behind
their promoted counterparts in math. Five years later, the achievement gap diminished to 0.78
standard deviations in reading and 0.65 standard deviations in math. Whereas the achievement
gap diminished over time for the kindergarten retainees, the achievement gap remained
consistent in third and fifth grade for the first grade retainees. Results of the study suggest that
kindergarten retention may be less harmful to children than retention in first grade; however

40

results of the study also indicated that both the kindergarten and first grade retainees would have
learned more overall if they would have been promoted instead of retained (Hong & Yu, 2007).
Aside from researchers’ inability to randomly assign students to a retained or promoted
group and inability to account for consistent demographic differences in retained versus
promoted students, kindergarten retention is an even more complex issue to address due to the
rapidly evolving cognitive, physical, and social capabilities of young children. Research on the
effects of schooling and young children indicates that some skills young children demonstrate
are a result of schooling whereas other skills are a product of maturation and independent of
schooling. Disentangling skills and competencies associated with biological maturation and
environmental input is important to better understand the effects of schooling and the most
appropriate interventions for students. Educators risk retaining students for failing to acquire
skills that are a function of age and independent of years of schooling.
Skibbe et al. (2011) examined the schooling effects of children who were essentially the
same age but varied in years of schooling due to age cutoffs. The small sample (n=76) consisted
of children who were born two months before or two months after the school cutoff date. The
slightly older children in the sample had two years of preschool while the younger children only
had one year of preschool. Children were tested in the fall and spring of the school year using
measures of self-regulation, decoding, letter knowledge, and vocabulary. Results of the study
indicated that although children who attended preschool for two years had higher scores in
decoding and letter knowledge, children in both their first and second year of preschool
demonstrated the same growth in knowledge over the school year. Children’s chronological age,
rather than number of years of schooling, was associated with vocabulary and self-regulation
scores. These results suggest that although additional schooling may have a cumulative effect on

41

academic outcomes, other variables such as biological maturation or the home environment may
also affect children’s self-regulation and vocabulary skills (Skibbe et al., 2011).
Bisanz, Morrison, & Dunn (1995) completed a similar study comparing the effects of age
and schooling on conservation of number and mental arithmetic. Kindergarten and first grade
children (n=56) were divided into three groups: different age but same level of schooling;
different amount of schooling but same age; and different in age and schooling. Results of the
study indicated that mental arithmetic competence improved with schooling. However,
children’s understanding of conservation of number was independent of schooling and only
dependent on age (Bisanz et al., 1995). This study further illustrates certain skills are not a result
of schooling but of biological maturation.
Results of meta-analyses suggest (Allen et al., 2009; Holmes, 1989; Holmes & Mathews,
1984; Jimerson et al., 2006) retention is not an effective educational intervention for struggling
students. However, that does not imply that struggling students do not require additional support
and remediation. Empirically supported interventions for struggling students involve the use of
additional supports prior to or during the school years. Several of these empirically supported
interventions involve alternative or “non-traditional” ways of thinking that are not currently
supported by public policy. Examples of empirically supported interventions include preschool,
comprehensive school-wide programs, summer school and after school programs, looping and
multi-age classrooms, school-based mental health programs, parent involvement, early reading
programs, effective instructional strategies and classroom management, and behavior/cognitive
modification (Jimerson et al., 2006).
A recent study by Im et al. (2013) was the first study in published literature to use
propensity scores to compare the academic, behavioral, and engagement outcomes of students

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who were retained compared to their promoted counterparts. The retained and promoted students
scored similarly on all outcomes, indicating that although retention may not be beneficial it is not
as harmful as once thought (Im et al., 2013). In a review of grade retention research, Reschley
and Christenson (2013) emphasis the importance of focusing on the larger picture – the need to
identify evidence-based interventions that work for children who are struggling academically - as
opposed to focusing on the narrower, dichotomous view of retention versus promotion. Retention
should not be an automatic default when children are struggling or lack skills. Rather, re-thinking
early childhood interventions and implementing empirically supported interventions with fidelity
is necessary to maximize young children’s educational attainment.
Negative Effects Associated with Being Young in Kindergarten
Special Education Rates. Although there is a significant amount of evidence largely
dismissing the differential effects of age at kindergarten entry, special education placement rates
have been linked to the age at kindergarten entry. Dhuey & Lipscomb (2010) used data from the
ECLS-K class of 1998-1999 and NELS:88 to examine the special eligibility placement rate in
relation to student age at kindergarten entry. Results of the study indicated that the relative age of
a student at the age of kindergarten entry was predictive of future special education placement
for learning disabilities but not for physical disabilities. Findings of the study highlight the
subjective nature of the learning disability evaluations in the school setting and indicate that
special education eligibility may be used as an intervention for young students (Dhuey &
Lipscomb, 2010). When students who have attended DK enter kindergarten, the former DK
students are typically a full year older than their peers. In light of the results of the Dhuey &
Lipscomb (2010) study, students who attend DK may be less likely to be classified with a
learning disability later during their school career.

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A study by Martin and colleagues (2004) corroborates the findings of Dhuey & Lipscomb
(2010). In a study of 2,768 Georgia kindergarten students, students with summer birthdays were
more likely to struggle academically in kindergarten. Analyses of school records indicated a
disproportionate number of students with summer birthdays (June, July, and August) were
diagnosed with a specific learning disability (Martin et al., 2004).
In a study designed to account for the within child factors in kindergarten age entrance,
Datar (2006) analyzed the kindergarten and first grade math and reading achievement scores of
13,818 children in the ECLS-K dataset based on children’s age relative to the kindergarten cutoff
date in their respective state. Results of the study indicated that older children had a statistically
significant advantage compared to their younger peers during kindergarten and first grade. Boys
and students with disabilities benefited the most from entering kindergarten one year later (Datar,
2006). Data were not available to determine if the academic benefits persisted over time. Based
on the results of this study, DK may be more advantageous for boys and students who already
have an identified disability.
The study of the effects of age in relation to kindergarten entry is not limited to the
United States. A study by Bedard & Dhuey (2006) demonstrated that age of kindergarten entry
has a long-term effect on later academic achievement across nineteen countries. Using data from
the Trends in International Mathematics and Science Study (TIMSS), younger students scored
lower on nationally standardized tests than older students at the end of fourth grade and eighth
grade. Young students were at a four to twelve percentile disadvantage at the end of fourth grade
and at a two to nine percentile disadvantage at the end of eighth grade. Older students were also
more likely to take college preparatory classes in their later high school years and attend a
flagship postsecondary institution (Bedard & Dhuey, 2006).

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Even after controlling for the effects of preschool, age at the time of kindergarten has an
effect on children’s long-term outcomes. In a study of 1474 economically disadvantaged firsttime kindergarten students, researchers examined whether or not preschool mediated the effects
of being young for one’s grade. Findings of the study indicated that preschool attendance was
associated with higher literacy scores, but students who were young for their grade were at a
higher risk for retention after controlling for literacy scores and preschool attendance (Huang &
Invernizzi, 2013).
Results of the studies relating to age at kindergarten entry are mixed. Although a large
body of literature exists that indicates the initial gains due to birthday fade over time (Robertson,
2011; Domaleski & Oshima, 2006), other studies have found negative effects related to being
young for one’s grade. Children who are young for their grade are more likely to receive special
education services (Domaleski & Oshima, 2006) or more likely to be retained (Huang &
Invernizzi, 2013). The mixed results of the studies related to redshirting or delaying kindergarten
entry reinforce the need to increase the evidence base in this area.
School Readiness
School readiness skills are a critical component of the transition to kindergarten. The
concept of school readiness has been around since 1836 when compulsory education laws were
first passed (Snow, 2010). “School readiness refers to the state of child competencies at the time
of school entry that are important for child success” (Snow, 2010, p.9). Although great variation
exists among school readiness definitions, all share the common theme of acknowledging the
acquisition of competencies that are linked to later school success (Snow, 2010). School
readiness is partly due to knowing (e.g., letters, numbers, and shapes) and partly due to ways of

45

being (e.g. willingness to share with others). In addition, there is cultural variation in terms of
school readiness, and school readiness factors vary based on geographic location (Graue, 2010).
School readiness was originally based on a maturationist perspective, indicating children
needed to reach a certain level of maturation prior to entering school (Pianta, Cox, & Snow,
2007). From a maturationist viewpoint, American school readiness was defined in terms of a
threshold, “Something you need x amount of to be able to profit from kindergarten” (Graue,
2010, p.47). However, many scholars and educators are calling for a more ecological view of
school readiness. Instead of expecting children to be ready for school, schools should be ready
for children (Graue, 2010).
Predictive Validity of School Readiness Measures. Both standardized and nonstandardized measures of school readiness are used to determine whether a child is “ready” for
kindergarten. However, defining the construct of school readiness is difficult, as well as creating
measurement tools with adequate reliability and validity (Graue, 2010). School readiness
assessments are particularly difficult to create considering the differences in experiences children
have based on parental income level, as well as differences in experiences based on culture and
ethnicity. Current kindergarten screening assessments have limited predictive validity, and
research indicates that delaying school entry based on school readiness may not be beneficial for
all (Snow, 2010).
In a meta-analysis of 70 longitudinal studies measuring the effect sizes of standardized
and non-standardized measures of early academic and social-emotional skills and early academic
and social-emotional outcomes measured after kindergarten and in first or second grade,
researchers found approximately 25% of variance in later academic outcomes could be attributed
to school readiness measures of academic and social-emotional skills and less than 10% of

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variance in later social-emotional outcomes could be attributed to school readiness measures of
social-emotional outcomes (La Paro & Pianta, 2000). Notably, correlations between the initial
kindergarten screening assessment and subsequent assessments ranged from .03 to .87, indicating
substantial variability across studies (La Paro & Pianta, 2000). Interestingly, correlations in the
La Paro & Pianta (2000) varied widely for both standardized and non-standardized measures of
school readiness, further illustrating the difficulty of selecting kindergarten screening measures
with high effectiveness and overall utility.
Calls have been made to shift the burden of school readiness from the individual child to
the school (Raforth et al., 2004). In contrast to the traditional within child measures of school
readiness, some argue the most effective school readiness tools would be designed for teachers to
use to adapt their daily classroom routines based on the needs of their students (Graue, 2010).
Others have emphasized creating standardized tests of school readiness that match a student’s
areas of need with specific interventions (Hair et al., 2006).
Table 4
Characteristics of School Readiness
Ability to follow structured daily routines
Ability to dress independently
Ability to work independently with supervision
Ability to listen and pay attention to what someone else is saying
Ability to get along with and cooperate with other children
Ability to play with other children
Ability to follow simple rules
Ability to work with puzzles, scissors, coloring, paints, etc.
Ability to write their own name or to acquire the skill with instruction
Ability to count or acquire the skill with instruction
Ability to recite the alphabet (or quickly learn with instruction)
Ability to identify both shapes and colors
Ability to identify sound units in words and to recognize rhyme
Raforth et al., 2004.
National Association of School Psychologists

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Perceptions of School Readiness. Parents and teachers view school readiness
differently. Parents emphasize counting and alphabet knowledge as the most important skills for
school readiness, whereas teachers emphasize social-emotional competencies as essential for
school readiness (Snow, 2010). “Social competence in children manifests in emotional selfregulation, social cognition, positive communication, and prosocial relationships with family
members, peers, and teachers” (Bornstein et al., 2010, p.718).
In an effort to understand kindergarten teachers’ perception of school readiness, Lin and
colleagues (2003) used data from 3,305 kindergarten teachers in the ECLS-K cohort in the 19981999 school year. When kindergarten teachers were asked to rate a list of 13 items that indicated
school readiness, a student’s ability to state his or her needs and thoughts, not be disruptive, and
follow directions were rated as the top three items, respectively. A key finding from the study is
that kindergarten teachers perceive social skills to be more important to school readiness than
academic skills (Lin et al., 2003).
Data from the School Readiness survey of the 2007 National Household Education
Surveys Program were used to assess the school readiness of children three to six years of age
(O’Donnell, 2008). Data were gathered from phone calls to 2,633 randomly selected parents.
Results of the survey indicated that 93% of children had speech that a stranger could recognize,
63% could count to 20 or higher, 60% could write their first name, 32% could recognize the
entire alphabet, and 8% could read words in books. Parents planned to delay kindergarten entry
for 9% of boys and 4% of girls (O’Donnell, 2008). The national survey did not survey parents
about social-emotional factors related to school readiness skills.
Risk Factors Relating to School Readiness. A high percentage of young children
lack school readiness skills prior to entering kindergarten. A national sample of kindergarten

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teachers (N=3,595) surveyed in the National Center for Development and Learning’s Transition
Practices Survey provided insight into how kindergarten teachers perceive children at the time of
kindergarten entry. Teachers reported that almost half of students (46%) had difficulty
transitioning to kindergarten. The rates of reported transition problems were related to school
minority composition, district geographic composition, and average household income level of
the district (Rimm-Kaufman et al., 2000). Children in the lowest socioeconomic group had
cognitive achievement scores that were 60% below those of the most affluent socioeconomic
group (Lee & Burkam, 2002) and disparities in achievement increased over time (Klein &
Knitzer, 2006). In a recent study of 781 children of Latino/a descent, school readiness risk
factors included being male, lack of preschool experience, and poor English proficiency (Quirk,
Nylon-Gibson, & Furlong, 2013).
In another study examining risk factors related to school readiness skills, researchers used
data from the ECLS-K Class of 1998-1999 (N=17,219) (Hair et al., 2006). Students were divided
into four groups: comprehensive positive development (30%), social-emotional and health
strengths (34%), social-emotional risk (13%) and health risk (23%) at the time of kindergarten
entry. Student academic outcomes and social adjustment outcomes were analyzed when the
students completed first grade. Results of the study indicated that children with a comprehensive
positive development profile scored the highest on the social-emotional and academic outcomes
at the end of first grade and children with one of the two risk categories scored the lowest on the
same outcomes. Children’s placement into one of the two risk categories was related to
economic disadvantage (Hair et al., 2006).
In one of the largest studies examining school readiness factors, researchers analyzed six
large-scale longitudinal data sets (Duncan et al., 2006). Two data sets were nationally

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representative of U.S. children, two data sets contained data from multi-site studies of U.S.
children, and two contained data from multi-site studies of children in Great Britain and Canada.
The study built upon previous school readiness research, examined multiple dimensions of
academic achievement, and controlled for ecological variables commonly related to
achievement. Results of the study indicated that academic achievement prior to attending school,
attention, and social-emotional skills had similar effects for boys and girls from families of both
high and low socioeconomic status. Early math skills were more predictive of later reading
achievement than early reading skills, but both early math and reading skills were associated
with higher levels of academic performance. Early attention abilities were more predictive of
later academic success than early social-emotional skills (Duncan et al., 2006).
School Readiness in Relation to Family Income. There are several risk factors
related to school readiness skills, and most of the risk factors are related to poverty. In a review
of risk factors related to the transition to kindergarten, Hernandez et al. (2007) cited inconsistent
parental work opportunities, low parental education, low parental pay, parental limited English
proficiency, and general family poverty status as common risk factors for young children’s
school readiness.
In order to better understand the relationship between school readiness skills and income,
data from two nationally representative birth cohort studies were used from the United Kingdom
and the United States. Data from the United States was gathered from the Early Childhood
Longitudinal Study – Birth Cohort (ECLS-B), and data from the United Kingdom was obtained
from the Millennium Cohort Study (MCS) (Waldfogel & Washbrook, 2011). Interviews were
completed at three points in time from age zero to five. Each data set was divided into five
income quartiles. Income-related gaps were noted in literacy, mathematics, and language skills.

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American children who attended Pre-K scored 6.8 percentiles higher on the ECLS-B literacy
assessment than children who did not attend Pre-K. Parenting style and learning environment
were the greatest two factors, respectively, in explaining the school readiness gaps across income
groups (Waldfogel & Washbrook, 2011).
Data from the Family and Children’s Experiences Survey was used to examine the school
readiness of low-income children enrolled in Head Start (McWayne, Cheung, Wright, Green,
Hahs-Vaughn, 2012). Children in the sample fell into five profiles: average academic and social
skills, low average behavior problems (28%); high behavior problems at school, low-low average
social and academic skills (17%); high behavior problem at home (15%); high social skills
(21%); high cognitive skills (19%). Differences in school readiness were evident across the five
profiles. Children who exhibited behavior problems at school were more likely to be boys,
children of color, and the youngest children in the class compared to the children with behavioral
problems at home. Children with behavior problems at home tended to have average to high
skills in the social and cognitive domains. Children with high cognitive skills made more
academic gains by the end of the school year than children with high social skills, but the
achievement gap between the high social skills and high cognitive skills groups decreased over
the school year (McWayne et al., 2012).
School Readiness Skills and Prior Preschool Experience. Prior high-quality preschool
experiences are associated with increases in school readiness. In a recent analysis of 123
comparative studies of early childhood interventions, Camilli et al. (2010) found that preschool
attendance was most strongly positively associated with increased cognitive outcomes. Preschool
attendance was also positively associated with children’s social skills and overall progress in
school (Camilli et al., 2010). Data from the ECLS-K dataset that included 7,748 children who

51

entered kindergarten in the fall of 1998 indicated that kindergarteners who attended preschool
entered kindergarten with higher academic skills than their peers who did not attend preschool
(Magnuson et al., 2007). Large-scale studies of state-funded preschool programs indicate that the
preschool programs are associated with increased gains in math and reading in the early school
years and reductions in kindergarten grade retention (Huang & Invernizzi, 2013; Magnuson et
al., 2007). Head Start has also been associated with modest benefits in children’s cognitive
abilities (United States Department of Health and Human Services, 2010).
Domitrovich et al. (2013) analyzed the effects of an enhanced, two-year preschool
program for three and four year old children compared to a one-year program for four-year-old
children. Propensity scores were used to account for the selection bias of children assigned to
each of the two groups. Results of the study indicated that children who participated in the twoyear preschool program had enhanced literacy and mathematics outcomes compared to the
children who participated in the one year preschool program (Domitrovich et al., 2013). This
study was particularly important since the research on dosage effects of preschool and other
transitional programs is limited.
Differential Gains from Preschool Programs. Over forty years ago, evidence emerged
indicating students from lower socioeconomic backgrounds benefited more from an extended
day kindergarten program than students from higher socioeconomic backgrounds attending
school in the same school district (Winter & Klein, 1970). Results of a recent meta-analysis
indicate that early childhood preschool programs benefit children from all socioeconomic
backgrounds but children from low socioeconomic backgrounds benefit differentially more from
a small number of early childhood programs than peers from higher socioeconomic backgrounds
(Burger, 2010). Differential gains from early childhood programs are typically due to risk factors

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such as socioeconomic status, level of maternal education, English language proficiency, and the
level of quality of the preschool program (Barnett, 2008).
Overall, preschool is associated with higher levels of cognitive and social development
for all children (Sylva et al., 2004), but differences in effectiveness vary based on specific
attributes of preschool programs. For example, children benefit the most from high-quality
preschool programs that meet throughout the year (Sylva et al., 2004). The quality of preschool
programs is often associated with geography. As a community’s resources increase, so does the
quality of early childhood education (Hatfield, Lower, Cassidy, & Faldowski, 2014). Children
from high-income backgrounds typically attend pre-kindergarten programs that provide richer
and more engaging experiences than pre-kindergarten programs serving children from lowincome backgrounds (Early et al., 2010). Moreover, as a child’s socioeconomic status increases,
the probability that he will attend preschool increases (Tucker-Drob, 2012).
Although preschool has been associated with positive effects for all children into later
adulthood (Goodman & Sianesi, 2005), several studies have shown direct links to differential
benefits for children from disadvantaged backgrounds. In a study of 600 twin pairs in which one
twin did not attend preschool and the other twin did attend preschool, researchers analyzed the
effect of genes, the shared environment, and the non-shared environment on cognitive and
achievement scores. For children who attended preschool, shared environmental influences
accounted for 47% of the variance in math scores and 43% of the variance in reading scores at
five years of age. For children who did not attend preschool, shared environmental influences
accounted for 72% of the variance in math scores and 73% of the variance in reading scores at
five years of age (Tucker-Drob, 2012). These results demonstrate the buffer effect that preschool

53

environments can have on environmental variables that may hinder children’s early
development.
Data from the state-wide North Carolina Pre-Kindergarten program (formerly known as
North Carolina More at Four) evaluation indicated that the pre-kindergarten program had
differential effects based on a child’s level of risk. Risk was divided into four levels and based on
eligibility for free or reduced price lunch, presence or absence of an identified special need,
limited English proficiency, and presence of a chronic health condition. Results indicated that
children in the highest risk group had lower baseline levels of language/literacy skills and
general knowledge, but equivalent levels of prosocial behaviors. Results measuring students’
growth in skills over the course of the school year indicated children in the highest risk group
made statistically significant greater gains in receptive language, applied math skills, color
knowledge, and social awareness over the course of the year whereas the lowest risk group made
statistically significant greater gains in rhyming (Peisner-Feinberg & Schaaf, 2007).
Bumgarner & Lin (2014) used the ECLS-K dataset to determine whether socioeconomic
status moderated the association between center-based early childhood education and English
proficiency at the time of kindergarten entry for first and second-generation Hispanic immigrant
children. Results indicated that Hispanic children in the lowest income group were twice as
likely to be proficient in English if they received a center-based early childhood education.
Center-based early childhood education was not a statistically significant predictor of English
proficiency for children in the higher income group (Bumgarner & Lin, 2014).
Maximizing the potential of children from disadvantaged backgrounds through early
childhood programs is complex, even though evidence indicates children from disadvantaged
backgrounds typically differentially benefit from attending high quality preschool programs.

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Research also indicates that children from disadvantaged backgrounds learn more while in
preschool programs if they attend a preschool with children from diverse socioeconomic
backgrounds. These results are not limited to American classrooms, as results of a longitudinal
study in New Zealand indicated preschool quality and preschool socioeconomic mix moderated
the influence of preschool on outcomes at age 16 over and above individual or family
characteristics (Hogden, 2007).
Integration of students from a variety of economic backgrounds is seldom mentioned, but
research indicates that the benefits of integration in preschool for children from disadvantaged
backgrounds are substantial. Positive peer spillover effects in reading and mathematics are
associated with preschool attendance (Neidell & Waldfogel, 2010). In a study by Schechter &
Bye (2007) preschool children from low-income backgrounds were assigned to attend a
preschool with peers from similar backgrounds or an integrated preschool with peers from higher
income backgrounds. Baseline receptive language scores for both groups of low-income children
were equivalent. At the end of the school year, the children from low-income backgrounds who
attended the integrated preschool had statistically significant higher receptive language scores
than their peers from low-income backgrounds and equivalent receptive language scores to their
peers from higher-income backgrounds (Schechter & Bye, 2007).
Social-emotional Skills in Relation to Academic Skills
School readiness skills are comprised of both social-emotional and academic skills for
valid reasons. Social-emotional skills are considered the most critical elements of academic
learning (Wang, Haertel, & Walberg, 1997). According to the National Research Council and the
Institute on Medicine, “The elements of early intervention programs that enhance socialemotional development are just as important as the components that enhance linguistic and

55

cognitive competence” (Shonkoff & Phillips, 2000, pp.398-399). Self-awareness, selfmanagement, social awareness, and responsible decision-making are all components of socialemotional competence (Denham, 2010).
Social interactions are the building blocks of learning and engagement in infancy
(Shonkoff & Phillips, 2000), and social-emotional skills continue to shape development
throughout the lifespan. Children who lack appropriate social-emotional skills at the time of
kindergarten entry exhibit more externalizing behaviors and struggle more academically than
their peers who have acquired social-emotional skills (Raver, 2004). In adolescence, healthy
social-emotional skills are associated with increased school attendance, greater engagement in
schoolwork, increased grade point averages and standardized test scores, and decreases in
substance abuse (Payton et al., 2008). The outcomes of social-emotional learning (SEL)
interventions also lend evidence to the importance of social-emotional skills. A recent metaanalysis of SEL interventions indicated all SEL interventions are associated with improved
social-emotional skills, improved attitudes about one’s self and others, positive social behavior,
reductions in conduct problems and emotional distress, and increases in student achievement
scores (Guerra, Graham, & Tolan, 2011).
In a longitudinal study of first born children in 118 American families, social competence
and externalizing and internalizing behaviors were assessed when each child was four, ten, and
14 years old (Bornstein et al., 2010). Data were collected from children and their mothers at all
three time points; classroom teachers provided data at the latter two time points. Results of the
study indicated that children with lower social competence skills at 4 years of age were more
likely to demonstrate externalizing behaviors at ten years of age and internalizing behaviors at 14
years of age. Social competence in early childhood was negatively correlated with overall

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behavioral adjustment in adolescence (Bornstein et al., 2010). When the results of this study are
coupled with the fact that behavioral adjustment problems in children are negatively associated
with cognitive abilities, the reciprocal relationship between social and academic skills in young
children is even more apparent (Bornstein et al., 1996).
Preschool Social-Emotional Learning. The Collaborative for Academic, Social, and
Emotional Learning (CASEL) divides social-emotional learning into five competencies: selfmanagement (mange emotions and behaviors to achieve goals), self-awareness (recognizing
emotions), responsible decision-making (making safe, healthy behavioral choices), relationship
skills (forming positive relationships and getting along with others), and social awareness
(demonstrating sympathy and empathy for others) (www.casel.org, 2013). Although each of
these competencies is important in the development of social-emotional skills, the development
of self-regulation skills (self-management) and relationship skills are particularly relevant to
preschool-age children.
Self-Management. Self-management requires a preschool child to regulate her
behavior and emotions in order to accomplish a goal. Achieving goal-directed behavior requires
self-regulation skills – including the ability to regulate one’s attention. Children who are able to
regulate their own behavior and maintain focused attention are less likely to be excused from the
classroom setting for behavioral issues and more likely to maximize learning outcomes through
interactions with their peers.
“Self-regulation is widely recognized as a critical social emotional skill underpinning
children’s abilities to act pro-socially with peers and adults, participate productively in learning
activities, and adapt successfully to new or challenging situations” (Vallotton & Ayoub, 2011,
p.169). Cumulative risk factors in childhood predict lower levels of self-regulation skills;

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however, self-regulation skills are an important protective factor for at-risk children (Lengua,
2002).
Vallotton and Ayoub (2011) used a longitudinal data set from the Early Head Start
program to better understand the relationship between children’s language skills and selfregulation. Data were collected from mothers and children when the children were 14, 24, and 36
months old. Eighty-five percent (N=105) of mothers were Caucasian and the average income of
each respondent was $17,463. Children’s talkativeness and vocabulary were used as predictors of
self-regulation. Results indicated that vocabulary was the greatest predictor of self-regulation
skills, even after controlling for cognitive ability; the effect of vocabulary on self-regulation was
stronger for boys than girls (Valloton & Ayoub, 2011).
The results of this study highlight the importance of vocabulary acquisition in young
children and toddlers. Although vocabulary is usually associated with cognitive ability, it is
noteworthy that in young children, vocabulary development is associated with the development
of appropriate social-emotional skills. For toddlers and young children, vocabulary skills allow
them to express their needs to adults and negotiate relationships with peers. Interestingly,
Valloton and Ayoub (2011) noted that scores on the Bayley Scales of Infant Development were
usually very similar across sociodemographic groups in the first year of life. However, within a
few short years, the vocabulary skills and standardized test scores of toddlers and young children
varied greatly based on socioeconomic status. As children grow older, family income plays an
increasingly important role in their development.
The findings in the Valloton & Ayoub (2011) study are supported by the seminal work by
Risley, Hart, & Bloom (1995) that revealed the vast differences in the volume of words young
children were exposed to based on socioeconomic status. By the time the children of

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professionals were three years old, the professionals’ children’s vocabulary surpassed the
vocabulary of parents receiving welfare assistance (Risley et al., 1995). Expressive and receptive
language skills are critical to the development of age-appropriate self-regulation skills and
interactions with peers.
In another study designed to examine the influence of peer effects on children’s selfregulation skills, researchers used the Head-Toes-Knees-Shoulders to measure the self-regulation
skills two cohorts of ethnically diverse first graders (N=1,078) (Skibbe et al., 2012).
Sociodemographic status was based on the percentage of students who received free and reduced
lunch. Results of the study indicated sociodemographic status was correlated with self-regulation
skills. Children in classrooms with lower means of self-regulation developed fewer selfregulation skills during the school year. As the overall affluence of a classroom decreased, the
mean self-regulation skills of children decreased. In addition, children in classrooms with lower
mean levels of self-regulation had poorer gains in passage comprehension and vocabulary
acquisition across the school year than children in classrooms with higher levels of selfregulation. Overall, peer regulation was positively associated with literacy gains (Skibbe et al.,
2012).
The Skibbe et al. (2012) study was unique because few studies have examined young
children’s self-regulation skills in relation to the overall level of children’s self-regulation skills
in their classroom. When these results are considered in the context of the results of the
Vallatoon & Ayoub (2011) study, it seems apparent that young children’s school readiness skills
are the result of a “domino” effect. Young children who are born into poverty are less likely to
develop the appropriate vocabulary skills to help them develop self-regulation skills, and they are

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less likely to experience “spillover effects” from peers with strong self-regulation and vocabulary
skills.
The ability to negotiate peer relationships and engage in the problem-solving process is
associated with young children’s ability to self-regulate. Walker and Henderson (2012) examined
whether preschool children’s social problem solving (SPS) skills mediated temperament and
later academic achievement in kindergarten and first grade. Participants were 1,117 children
enrolled in the National Institute of Child Health and Human Development Study of Early Child
Care. Results of the study indicated that inhibitory control (a SPS) predicted better academic
achievement in kindergarten and first grade than shyness (temperament). Promoting good SPS in
early childhood may help alleviate future academic problems in children with extreme
temperaments (Walker & Henderson, 2012). However, children must possess the appropriate
vocabulary skills to be able to engage in the problem solving process.
Attention. Attention also affects young children’s ability to learn. In a study by
Dice and Schwanenflugel (2012), researchers hypothesized that a child’s early reading skills
mediated the relationship between attention and decoding abilities in late kindergarten. The
diverse sample included 250 children attending kindergarten or Pre-K at a lottery-based public
school program. Thirty-nine percent of the students in the sample received free or reduced lunch.
Of the parents reporting ethnicity, 65% identified as African American, 32% identified as
Caucasian, 3% reported as Hispanic, Asian, or Bi-racial, and 19% did not report ethnicity. Fiftyfour percent of mothers completed high school, 12% attended some college, 12% had a
bachelor’s degree, and 6% had advanced degree. Contrary to popular belief, results indicated that
attention contributed more to the development of early reading skills than maternal education
(Dice & Schwanenflugel, 2012).

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In another study, researchers used a longitudinal design to explore the link between
attentional regulation in preschool and academic outcomes at age nine. The study included 2,595
diverse preschool students from the Fragile Families and Child Wellbeing Study. Focused
attention at age five was predictive of academic achievement outcomes at age nine, and
impulsivity at age five was predictive of behavioral outcomes at age nine. Income status,
maternal warmth, and infant temperament did not moderate the outcome (Razza, Martin, &
Brooks-Gunn, 2012).
Brennan and colleagues (2012) examined the predictive validity of parent ratings of
toddler aggression, oppositionality, inattention, and hyperactivity-impulsivity to predict
academic achievement when the children were 7.5 years of age. Participants were recruited from
Women, Infants, and Children Nutrition Programs in three metropolitan areas (N=566 children).
All participants in the sample had two of the following three risk factors: child behavior
problems (e.g., conduct problems, aggression), family problems (e.g., maternal depression,
substance abuse), or low socio-economic status. Results of the study indicated that aggression at
age two or three had the most association with academic achievement at age 7.5 (Brennan et al.,
2012). Although this study found that toddler aggression was more related to later academic
achievement than hyperactivity or impulsivity, it is difficult to ascertain how much toddler
aggression in the home setting may be replaced with hyperactivity in the school setting.
Furthermore, if aggressive toddlers are frequently removed from preschool or kindergarten
classrooms, perhaps the absence of instruction causes their academic achievement to diminish
over time.
Ducan et al. (2006) used six longitudinal data sets (ECLS-K, The Children of the
National Longitudinal Study of Youth, The National Institute of Child Health and Human

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Development Study of Early Childcare Youth Development, The Infant Health and Development
Program, The Montreal Longitudinal-Experimental Preschool Study, and The 1970 British Birth
Cohort) to estimate the effects of three components of school readiness (school-entry academic
skills, attention, and socioemotional skills) and later school reading and math achievement. All
children in the study were five or six years of age. Interestingly, the strongest predictors of later
academic success were school-entry math skills, school-entry reading skills, and attention,
respectively. The influence of each of these three variables did not differ based on gender or
socioeconomic status. Contrary to the authors’ original hypotheses, social-emotional behaviors
were not associated with later academic outcomes. The authors completed many follow-up
analyses to verify or refute their findings based on additional factors and variables, but all
evidence supported the initial findings (Duncan et al., 2006).
In another study, Belsky, Fearon, & Bell (2007) tested the assumption that attentional
control processes mediate the effect of parenting on later externalizing behaviors. Data for this
study were collected as part of the NICHD Study of Early Childcare and Youth Development.
Data were consistently collected from 1,364 mothers of children from the time of the child’s
birth, and researchers followed children from 54 months of age to fifth grade. Data were
gathered through videotapes coded for maternal sensitivity, the Continuous Performance Test
(CPT), and selected subscales of the Achenbach Teacher Report Form (TRF). Results of the
study indicated that greater maternal sensitivity at 54 months and first grade predicted more
attentional control over time, and more attentional control in first and third grade predicted less
externalizing behaviors over time (first, third, and fifth grade) (Belsky et al., 2007).
In a study of 467 preschool children (average age 55.9 months) enrolled in a Head Start
program or a daycare program with a similar demographic composition, researchers examined

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the relationship between academic development and social-emotional functioning (Arnold et al.,
2012). Standardized measures were used to assess preliteracy, language, and mathematics.
Children reported their feelings about school using the Feelings about School Measure and the
IOWA Conners Teacher Rating Scale was used to measure attention and aggression. Results of
the study indicated attention difficulties were associated with poorer academic outcomes and
social-emotional skills were associated with better academic outcomes (Arnold et al., 2012).
Results of these studies highlight that self-management skills are both directly and
indirectly essential to preschool-age children’s academic success. Children learn more when they
are engaged in classroom activities with their teacher and peers, and have the ability to listen to
and follow directions and participate in classroom activities. Expressive and receptive language
skills enhance children’s ability to regulate their behavior and interactions with others. When
children are removed from the classroom for behavioral reasons or lack the ability to regulate
their attention while in the classroom, their academic achievement suffers. Academic skills are
cumulative, and children with appropriate self-management and attention skills are at a shortterm and long-term advantage academically compared to their peers.
Relationship skills. Interactions with same-age peers are important predictors of later
mental health and wellbeing (Denham, 2010). Peer relationships in the preschool years are
dependent upon appropriate social-emotional skills and also influence academic outcomes. A
child is able to maximize his or her classroom experience through positive interactions with
teachers and peers (Vitiello et al., 2012). Preschool children who have warm, affectionate
relationships with their mothers have higher levels of achievement in elementary school (Pianta
& Harbors, 1996). Positive student-teacher relationships are associated with increased academic
success, prosocial behavior, and increased social skills in all grades (O’Connor & McCartney,

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2007; Palermo, Hanish, Martin, Fabes, & Resier, 2007; Pianta & Stuhlman, 2004). In contrast,
students who consistently have negative interactions with teachers and peers during elementary
and middle school score lower on academic measures than students who do not have consistently
negative interactions with teachers and peers (Hamre & Pianta, 2001).
The ability to form friendships in preschool is a foundational skill in order for children to
continue to develop and sustain friendships over time. In a study of 166 three to six year old
preschool children, researchers interviewed children about their friendships (Lindsey, 2002).
Results of the study indicated that children with at least one mutual friend were better liked by
their peers, and teachers rated those children as more competent than the children who did not
have one mutual friend. In addition, children with mutual friends in preschool were better liked
by their peers the following year (Lindsey, 2002).
In the same manner that positive peer relationships are associated with increased
academic performance, negative peer relationships are associated with decreased academic
performance. In 2001, Buhs and Ladd completed a study to examine the peer relations processes
that might mediate the relationship between peer rejection and children’s emotional adjustment
and academic outcomes. The sample included 399 mid-western kindergarteners from a variety of
socioeconomic backgrounds. Results of the study indicated that children who were rejected by
their peers were more likely to be treated negatively by their peers, were less engaged in
classroom activities, more likely to want to avoid school, and demonstrated decreased
achievement on academic measures (Buhs & Ladd, 2001). In a study of 380 children who were
part of a large study on children’s psychological and school adjustment, Buhs and colleagues
(2006) followed the children from kindergarten to fifth grade to further examine the effects of

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exclusion in later grades. Results of the study indicated that decreased classroom participation
due to chronic peer exclusion was associated with the greatest decline in student achievement.
Classroom interactions with peers are an essential element of children’s academic
learning. Bierman and colleagues (2009) used a diverse sample of 356 four-year-old children
who were attending Head Start to examine the degree to which classroom participation, prosocial
behavior, and aggression control were related to children’s academic knowledge and executive
functioning. Classroom participation was assessed with a school readiness inventory developed
specifically for the study, prosocial behavior was assessed with the Social Competence Scale,
aggressive behavior was assessed with the Teacher Observation of Child Adaptation-Revised,
cognitive ability was assessed with the block design subtest on the Wechsler Preschool and
Primary Scale of Intelligence – III, academic knowledge was assessed with the Test of Preschool
Early Literacy, and executive functioning was assessed with the Peg Tapping Task. Results of
the study indicated prosocial and aggressive behaviors were negatively correlated (r= -.69),
prosocial behavior and classroom participation were positively correlated (r= .82), and classroom
participation and aggression were negatively correlated (r=-.65). The overall academic
achievement composite and Block Design score were positively correlated with class
participation and prosocial behavior and negatively correlated with aggressive behavior
(Bierman et al., 2009).
Interestingly, in the study by Bierman and colleagues (2009), children with the most
pronounced deficits in prosocial skills also had lower cognitive scores, lower levels of classroom
participation, less academic knowledge, and lower executive functioning skills than children who
did not have prosocial skills deficits. Prosocial behavior with peers was highly correlated with
classroom participation and also correlated with academic knowledge and executive functioning

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skills (Bierman et al., 2009). One unexpected finding of the study was that children with
aggressive behavioral tendencies and low prosocial behaviors had more gains in academic
achievement than children with low prosocial behaviors alone. This finding highlights the
importance of classroom participation in academic achievement (Bierman et al., 2009).
Children who are able to form friendships and interact prosocially with their peers and
adults in the classroom are more likely to enjoy school, spend more time engaged in academic
activities, and maximize their learning potential. Moreover, social-emotional skills are also
beneficial to preschool children – independent of academic outcomes (Arnold et al., 2012,
CASEL, 2013). Providing young children with opportunities to develop appropriate socialemotional skills is an important part of early academic experiences; however, delaying children’s
entry into kindergarten may not be the most appropriate way to foster social-emotional
development in young children.
Early Literacy Skills
In addition to social-emotional skills, early literacy skills are an important component of
school readiness skills. Early literacy skills are foundational in the attainment of later literacy
skills (West, Denton, & Reaney, 2000) and instrumental in shaping a child’s quality of life as an
adult. For example, low literacy skills are associated with poor school attendance, grade
retention, teen pregnancy, and poor management of health issues (Kutner, Greenberg, Jin, &
Paulsen, 2006; Matson & Haglund, 2000). In 2011, only 42% of 4th graders scored at the “at or
above Proficient” or “at Advanced” level of reading proficiency and only 37% of 8th graders
scored at the “at or above Proficient” or “at Advanced” level of reading proficiency (Kutner et
al., 2006).

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The importance of literacy in overall wellbeing has placed literacy attainment at the
forefront of American education. In 2000, the National Reading Panel reviewed over 100,000
studies to identify the most important components of reading. The five most important skills
were phonemic awareness, phonics, fluency, vocabulary, and text comprehension. Although the
Report of the National Reading Panel: Teaching Children to Read is a seminal work in literacy
research, the findings do not apply to children from birth to five years of age. In order to address
this gap in research, the National Early Literacy Panel (NELP) was formed to review the
literature pertaining to literacy skills in early childhood (NELP, 2009). Five hundred research
articles that met strict search criteria were used in the meta-analyses. Results of the study
indicated that after controlling for cognitive ability and socioeconomic status, six skills were
strongly correlated with later literacy skills. These six skills included: alphabet knowledge,
phonological awareness, rapid automatic naming (RAN) of letters or digits, RAN of objects or
colors, writing letters or writing one’s name, and phonological memory. Five additional variables
were moderately correlated with later reading ability: concepts of print, print knowledge, reading
readiness, oral language, and visual processing (NELP, 2009). Each of these 11 variables are
intertwined and often correlated with one another.
Children’s abilities in each of these areas prior to entering kindergarten vary greatly
(West et al., 2000). Environmental factors, such having books available to read, parenting style,
socioeconomic status, and parental proficiency in English are all key factors in children’s early
literacy development and explain many of the later literacy gaps among groups of older children
(Waldfogel, 2012). An overview of each of these variables follows. The areas of print knowledge
and reading readiness are not outlined since print knowledge includes the constructs of decoding,
alphabet knowledge, and concepts of print and reading readiness includes the constructs of

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alphabet knowledge, concepts of print, vocabulary, and phonological awareness (NELP, 2009).
The explanation of each of these variables is followed by models associated with early literacy
skill development and an overview of parental contributions to early literacy learning.
Early Literacy Skills Associated with Later Academic Achievement
Alphabet Knowledge. Alphabet knowledge is defined as “Knowledge of the names and
sounds associated with printed letters” (NELP, 2008, p.3). Letter knowledge is one of the oldest
and long-standing positive predictors of later reading ability with research dating back to the
1960’s (NELP, 2008). In 1961, Jeanne Chall, a well-respected reading researcher, spent three
years visiting classrooms, completing meta-analyses, scouring textbooks, and interviewing
educators to enhance the reading literature base. Chall concluded that for beginning readers,
alphabet knowledge was more important to reading achievement than a child’s cognitive ability
(Chall, 1967). Although more recent research continues to confirm alphabet knowledge as the
most powerful predictor of reading ability (Catts, Fey, Tomblin, & Zhang, 2002; Lonigan,
Burgess, & Anthony, 2000; Muter, Hulme, Snowling, & Stevenson, 2004), alphabet knowledge
at kindergarten entry may be more predictive of parental investment and guidance prior to
kindergarten entry (Hecht, Burgess, Torgeson, Wagner & Raschotte, 2000).
Drouin, Horner, & Sondergeld (2012) used Rasch model analyses to examine multiple
elements of the construct of alphabet knowledge including letter recognition (lower case and
upper case), letter naming (lower case and upper case), and letter sounds. Participants (N=378)
were preschoolers enrolled in 15 different childcare facilities. Results of the study indicated that
the three alphabet tasks were measures of a single ability and supported the notion of a unitary
alphabetic construct. However, letter recognition was easier than letter naming and letter naming

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was easier than letter sounds. Children identified uppercase letter names easier than lowercase
letter names (Drouin et al., 2012).
A study by Justice, Pence, Bowles, & Wiggins (2006) lent further evidence to the notion
that letter learning is not random. Participants in the study included 339 four year-year-old lowincome children attending public preschool. Children were more likely to recognize letters that
were in their own name, were in the beginning of the alphabet, corresponded to the sound of the
letter, or corresponded to the earliest acquired sounds during infancy (Justice et. al, 2006). In
another study composed of an urban and suburban sample, researchers concluded that lowercase
letters are more difficult for preschoolers to identify than uppercase letters and lower case letters
improve the validity of studies of alphabet knowledge (Bowles, Pentimonti, Gerde, & Montroy,
2014).
Phonological Processing. Phonological processing refers to the ability to process sounds
in one’s native language. There are three distinct, yet interrelated phonological processing
abilities including phonological awareness, phonological memory, and phonological access to
lexical storage (Anthony & Francis, 2005).
Phonological Awareness. Phonological awareness is defined as “The ability to
detect, manipulate, or analyze the auditory aspects of spoken language (including the ability to
distinguish or segment words, syllables, or phonemes) independent of meaning” (NELP, 2002,
p.3). Decades of literacy research and statistical and technological advances support
phonological awareness as a unitary construct that evolves over time. “Phonological awareness is
a single cognitive ability that manifests behaviorally in a variety of skills” (Anthony & Francis,
2005, p.256). Four longitudinal studies of preschoolers provide further support for phonological
awareness as a unitary ability (Anthony & Lonigan, 2004). The direct link between literacy skills

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and phonological awareness has been firmly established in research. In a meta-analysis
preceding the National Reading Panel: Teaching Children to Read, phonemic awareness and
letter-sound knowledge were considered the most powerful predictors of word reading skills
(Adams, 1990). Results of the Report of the National Reading Panel (2000) indicated
phonological awareness skills had an effect size of 0.86 (National Reading Panel, 2000). Direct
instruction in phoneme segmentation and manipulation is a critical component of reading
instruction, especially for children at-risk of reading difficulties (Vaughn, Wanzek, Woodruff, &
Linan-Thompson, 2008).
Phonological Memory. Phonological memory is defined as “The ability to
remember spoken information for a short period of time” (NELP, 2002, p.3). Although
phonological memory has not been studied as much as phonological awareness, the two concepts
are intertwined with one another (Anthony & Lonigan, 2004). Phonological memory increases
between four and twelve years of age and corresponds to increases in verbal skills (Alloway,
Gathercole, & Pickering, 2006). Nithart and colleagues (2011) studied the development of
phonological abilities and the influence of phonological development on reading acquisition.
Forty-four preschool children (mean age = 5 years) were tested at the end of kindergarten before
they received any formal reading instruction and again at the end of first grade. Results of the
study indicated that phonological awareness skills were more highly correlated with reading
skills at the end of kindergarten. However, at the end of first grade, phonological memory skills
were more highly correlated with reading skills. Phonological discrimination, awareness, and
memory were all correlated with one another, but phonological memory developed with
children’s short-term memory capacity (Nithart et al., 2011).

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Development of Phonological Processing Skills. The development of
phonological awareness skills follows a typical pattern, and children are continuously refining
previous knowledge while acquiring new knowledge (Anthony & Francis, 2005). Children
usually begin to develop phonological processing skills around two to three years of age when
they begin to play with sounds and monitor their own speech during unstructured play times
(Snow, Burns, & Griffin, 1998). As children grow older, their ability to detect smaller and
smaller parts of words increases. Children are able to detect similar and dissimilar words (e.g.
map, book) before they are able to detect sounds within individual words. Children develop the
ability to detect onsets and rimes (e.g. m/ap, l/ap) prior to being able to detect the individual
sounds in words (e.g. m/a/p/). The ability to blend phonological information typically precedes
the ability to segment phonological information. It is important to note that the attainment of
phonological skills is influenced by both biological and environmental factors (Anthony &
Francis, 2005).
Rapid Automatic Naming. Rapid automatic naming refers to “The ability to rapidly
name a sequence of random letters, numbers, or repeating sets of pictures of objects or colors”
(NELP, 2002, p.3). Rapid automatic naming fluency predicts word identification skills (Bowey,
Storey, & Ferguson, 2004; Miller et al., 2006), reading fluency skills (Georgiou, Parrila, &
Kirby, 2006), and reading comprehension skills (Katzir et al., 2006). Tasks that require rapid
naming of numbers or letters are called graphological tasks, whereas tasks that require rapid
naming of colors or objects are non-graphological tasks (Wolf, Bally, & Morris, 1986). The
predictive validity of graphological and non-graphological tasks changes over time and is
debated in the literature (Hammill, Mather, Allen, & Roberts, 2002). For example, graphological
and non-graphological rapid naming tests used at the beginning of kindergarten predicted of

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reading abilities at second grade, but the same tasks were not predictive of when they are used
just prior to first grade (Smith, Scott, Roberts, & Locke, 2008). Kirby and colleagues (2003)
assessed the rapid naming skills (color naming and picture naming) of 115 kindergarten children.
Five years later, researchers assessed the overall reading ability of the same children when they
were in fifth grade. Results of regression analyses indicated that rapid naming skills had little
effect in the early elementary years on overall reading ability, but the effect of rapid naming
skills on predicting overall reading ability increased in the later elementary years (Kirby, Parilla,
& Pfeiffer, 2003).
Writing Letters and Writing Name. This skill refers to writing letters in isolation upon
request and possessing the ability to write one’s name (NELP, 2009). One of young children’s
first writing activities is writing their name, a behavior that extends across boundaries of culture
and socioeconomic status (Levin, Both-DeVries, Aram, & Bus, 2006). Vygotsky (1978)
considered a child’s ability to write his or her name a developmental milestone, since it required
a child to connect oral and written language. Name writing and letter knowledge usually develop
at similar times and the two skills are related to one another (Blair & Savage, 2006). Puranik &
Lonigan (2012) studied the effect of name-writing ability on preschool children’s other early
literacy abilities. In the study of 296 preschoolers age four to five, name writing proficiency was
a statistically significant predictor of alphabet knowledge and spelling ability. Results of the
study indicated that the length of the child’s name did not matter in predicting alphabet
knowledge or spelling ability; however, proficiency in name writing did matter (Puranik &
Lonigan, 2012).
Other studies have downplayed the importance of name writing ability in preschool
children’s literacy abilities. In a study of 114 typically developing preschool children, name

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writing skills were related to letter knowledge (Drouin & Harmon, 2009). However, children
often were able to write letters as part of their name but unable to identify those same letters out
of context. In contrast, some children were able to recognize the letters in their name, but they
were not able to write them. The children with excellent letter recognition (but unable to write
their name) had greater letter recognition scores than children who had excellent name writing
skills (but unable to identify as many letters). Results of the study indicated that children’s name
writing skills may be a better proxy of mechanical skills than conceptual literacy knowledge
(Drouin & Harmon, 2009).
In a study examining which emergent literacy skills contribute to preschool children’s
writing abilities, Puranik, Lonigan, & Kim (2011) found that print knowledge and letter-writing
skills were related to name writing, whereas a different set of skills including alphabet
knowledge, print knowledge, and name writing were related to letter writing. Interestingly, only
letter writing ability was association with spelling ability. Results of the study indicated that
children’s overall letter writing skills, as opposed to the ability to write their name, is more
predictive of preschool literacy skills (Puranik et al., 2011).
Diamond, Gerde, & Powell (2008) designed a study to examine the relationship among
preschool children’s early writing skills, knowledge of letter names, sensitivity to initial sounds
in words, and understanding of concepts of print. Participants in the study were preschool
children enrolled in 35 Head Start classrooms. Results of the study indicated that the preschool
children who could write letters in the fall were on a different growth trajectory for recognizing
letter names than the children who could not any letters in the fall. For children who could write
one or more letters in their name at the beginning of the school year, growth in writing skills was
directly related to growth in letter knowledge. However this bidirectional relationship between

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letter knowledge and writing skills did not exist for children who were not able to write one or
more letters in their name at the beginning of the school year (Diamond et al., 2008).
In another study of 103 children ages three to five years old, researchers analyzed the
effect of letter knowledge, decoding, motor skills, problem behaviors, and the home literacy
environment on children’s ability to write their name. Researchers found that children’s
knowledge of capital letters and their gross motor skills accounted for the greatest variance
(almost one-fourth of the total variance) in children’s ability to write their name (Gerde, Skibbe,
Bowles, & Martoccio, 2012).
Concepts of Print. Concepts of print refer to knowledge of text conventions of print,
such as the way text is written in a book as well as concepts of text such as where to locate the
author’s name (NELP, 2002). Concepts of print knowledge is considered a constrained skill
(Paris, 2005), but young children’s acquisition of print knowledge is important and is related to
later reading success (Levy, Gong, Hessles, Evans, & Jared, 2006; NELP, 2002). The
development of concepts of print at an early age is particularly important because it indicates
children have begun to control and direct their attention and attend to print in a specific way
(Clay, 2000). Children’s concept of print is developed gradually through multiple warm
interactions and experiences with caregivers and books (Clay, 2000). Although it is important
not to rush the process, a child’s knowledge of concepts of print knowledge is heavily dependent
upon adult interaction (Lovelace & Stewart, 2007).
In a study of 474 children ages 48 to 83 months, researchers examined the developmental
trajectory of print knowledge, and analyzed the relationship between concepts of print and early
reading skills (Levy et al., 2006). Parents of the children were also given a questionnaire about
home literacy activities. Results of the study indicated children begin recognizing word shapes,

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followed by recognizing correct letter orientations, and then common spelling patterns.
Researchers found that the development of print knowledge is not a passive process. Rather,
children must be actively engaged letter printing, letter naming, and developing language skills.
Understanding correct word and letter orientation was related to reading achievement on a
standardized measure, after accounting for age variation and phonological abilities (Levy et al.,
2006).
In another study of print awareness, 128 children (ages 3 – 5) were given the Preschool
Word and Print Awareness Measure (PWPA). Children were from urban, suburban, and rural
regions of southeast Ohio and 34% were from low SES backgrounds. All participants in the
study were native English speakers, passed a hearing test, and did not have a history of any type
of impairment. During the testing process, 34 children were identified and tested for a potential
language impairment. Results of the study indicated that children from low SES backgrounds
performed similarly on the PWPA to students with a language impairment (Effect Size -1.5 for
SES and -1.2 for language impairment). The environmental and developmental risk factor each
exerted nearly the same effect on concepts of print knowledge. Researchers also discovered that
there was a lack of a cumulative effect when both the developmental and environmental risk
factors were present (Justice, Bowles, & Skibbe, 2006).
Oral Language. Young children’s oral language skills are also important to the
development of literacy skills. Oral language skills involve producing language (expressive
language skills) and comprehending language (receptive language skills) (NELP, 2009).
Measures of long-term outcomes attest to the importance of children’s oral language skills. For
example, children with an expressive or receptive language impairment in kindergarten are much

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more likely to be diagnosed as a student with a learning disability by second grade (Catts et al.,
2002).
Children’s oral language skills provide insight into their overall literacy development. In
a study of the relationship between oral language, print knowledge, and phonological sensitivity
skills at during the preschool years and later elementary school, researchers followed 96 children
(mean age 41 months) during the preschool year, and 97 children (mean age 60 months) from
preschool to kindergarten or first grade. Results of the study indicated letter knowledge and
phonological sensitivity were predictors of later decoding skills, and children’s phonological
skills were relatively stable across time (Lonigan et al., 2000).
There is a substantial body of literature documenting the differences in the oral language
skills of preschoolers. On average, children living in poverty have fewer enriched language
opportunities than their more affluent peers (Risley et al., 1995). Although the language
development of children living in poverty is usually described in general terms, Cabell and
colleagues (2011) studied the oral language development of 492 preschoolers enrolled in a Head
Start program. Researchers administered eight measures of emergent literacy, including four
measures of oral language. Five profiles of emergent literacy skills emerged, indicating great
variability among at-risk children (Cabell et al., 2011).
Visual Processing. The orthographic nature of print requires the ability to visually
process information in order to read text (NELP, 2009). Although there is less research
investigating visual processing ability than other skills related to early reading, visual processing
skills are a predictor of later reading success. As children grow older and the volume of text
increases, visual processing skills become increasingly important to read text fluently and
accurately (Badian, 2001). In a longitudinal study of 96 kindergartens, children’s pre-reading

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skills were assessed using a variety of measures, including the Orthographic Processing
measure, six months prior to kindergarten entry. Results of the study indicated visual processing
skills accounted for an increasing proportion of the variance in reading ability as the children
grew older (Badian, 2001).
Models of Emergent Literacy Development. There are several frameworks for
understanding the development of early literacy skills and are beyond the scope of this paper.
The following are selected developmental, component, interactional, and more general
frameworks of emergent literacy development.
The development of emergent literacy skills begins when children begin to observe the
environment around them. Linnea Ehri’s (1995) phases of word recognition development model
outlines the phases children progress through as they acquire increasingly sophisticated literacy
skills. Children begin in the pre-alphabetic stage and “read” or recognize common logos or signs.
Children begin to realize that print serves a purpose and then begin to interact with print. Next,
children transition to the pre-alphabetic stage and recognize some sounds and letters in words,
and often guess a word based on the first and last letters of the word. Then, children progress to
the full alphabetic stage, which requires letter and sound recognition. During this phase, children
decode words slowly, but accurately. The next phase is the consolidated alphabetic phase, a
phase in which children are able to retain multisyllabic words in their memory and process words
quickly. The final phase is the automatic phase. During this phase, children are proficient, fluent
readers and implement multiple strategies to figure out unfamiliar words. Children are able to
focus on comprehending text instead of decoding text (Ehri, 1995).
Developmental frameworks of emergent literacy emphasize the notion that the
relationship between print and meaning occurs prior to understanding forms of print. The

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Goodman (1986) framework posits that children first learn to recognize print in their own
environment and then they translate that to other forms of discourse such as magazines or
newspaper. Finally, children develop metacognition related to reading and they are able to
articulate that they are reading a page of a book or point to a specific word in the text (Goodman,
1986). The McCormick & Mason (1986) framework acknowledges children’s emergent literacy
skills as a hierarchy and children first learn to recognize the function of print and then learn to
recognize forms of print. Last, children integrate the function and form of print (McCormick &
Mason, 1986).
The Strommen & Mates (2000) framework emphasizes the social aspect of reading.
Children first look at the illustrations in a book and then begin to tell a sequenced story through
the pictures in the book, then progress to retelling the story while retaining the original meaning,
and then children attempt to refer to the print to retell the story. Finally, children use multiple
strategies to attempt to decode the print and read the story (Strommen & Mates, 2000).
Component frameworks of early literacy skills focus on the particular components of
early literacy. The Storch & Whitehurst (2002) framework divides children’s early literacy skills
into code-related skills (e.g. concepts of print and writing one’s name) and oral language skills
(e.g. expressive and receptive vocabulary). Another component literacy framework, the van
Kleeck framework (1998), is centered on four major components: (1) the context processor (e.g.,
word knowledge, book conventions), (2) the meaning processor (e.g., word awareness,
vocabulary development), (3) the orthographic processor (e.g. letter knowledge), and (4) the
phonological processor (e.g., onsets and rhymes). Each of these “processors” helps young
children to acquire emergent literacy skills.

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Contemporary Models of Emergent Literacy Development. The most contemporary
frameworks for emergent literacy development, the child and environmental influences
perspective, acknowledge the interaction between the child’s biology and environment in the
development of emergent literacy skills. These frameworks are closely aligned with
Bronfenbrenner’s bioecological theory of child development and recognize the multiple
influences that lead to outcomes in a child’s development. The McNaughton (1995) socialization
model emphasizes the role of the family in literacy acquisition and includes four family literacy
components: (1) family practices, (2) child and family activities, (3) systems for learning and
development, and (4) relationships between settings in the child’s environment. Family practices
include cultural expectations the family holds pertaining to reading, such as expecting that
children will learn to read. Child and family literacy activities include such things as writing
thank-you notes to friends and relatives or taking trips to the public library. The systems that
reinforce literacy development include continuous book sharing with a sibling or consistently
engaging in literacy tasks of increasing difficult with a parent. Children maximize their
acquisition of literacy skills when family practices are reinforced in multiple environments such
as the homes of extended family members, daycare centers, and preschools (McNaughton, 1995).
The Wasik & Hendrickson (2004) framework also emphasizes the role of the family. The
authors identified four family variables in the research that have the most support children’s
literacy development. The four key variables in the model are (1) parental characteristics (e.g.,
culture, ethnicity, parental beliefs, SES), (2) child characteristics (e.g., cognitive ability,
motivation), (3) home literacy environment (e.g., parents’ attitude toward literacy activities), and
(4) parent-child relationships (e.g., warm supportive relationships lead to better literacy
outcomes). Results of the National Institute of Child Health and Human Development Study

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(NICHD) (2000) revealed that family and parent features were more strongly associated with
early cognitive and language development than the features of early childhood care centers. The
literacy activities, literacy tools, and developmentally appropriate parental scaffolding related to
literacy tasks are directly correlated with young children’s literacy abilities (Aram & Levin,
2001). Moreover, research indicates parenting practices are the strongest predictor of young
children’s literacy skills (NICHD ECCRN, 2003). Warm, positive, and caring relationships
between caregivers and children (Clay, 2000) and marital couples (Froyen, Skibbe, Bowles,
Blow, & Gerde, 2013) increase children’s early literacy acquisition. A child’s home environment
provides his or her first experiences with language development, a print-rich environment, and
continuous interactions with text (Neuman & Dickinson, 2011).
Development of Early Literacy Skills. The development of early literacy skills is a
complex, dynamic process that research continues to unravel (Figure 2). Early literacy skills
refer to the behaviors young children exhibit that demonstrate they have an understanding of
reading and writing before they have the ability to read or write (Schickedanz & Collins, 2013).
The development of early literacy skills begins as soon as an infant hears sounds prenatally, as
early literacy development occurs in tandem with language development. For young children, the
functions of early literacy (e.g. inviting a friend over or ordering a meal) are just as important as
traditional forms of literacy (e.g. recognizing letters or words or looking through books) (Teal &
Sulzby, 1986).
Although research is still unraveling the mechanisms young children use to develop
emergent literacy skills, certain over-arching principles have been uncovered. For example,
children who are surrounded by books and are read to develop print awareness quicker than
children who do not have these experiences (Honig, Diamond, & Gurlohn, 2008). The

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development of phonological processing skills are critical to children’s later reading success, as
it is estimated that 90% of children with reading difficulties have a core deficit in processing
phonological information (Honig et al., 2008).
Home
Warm, positive
relationships between child
and caregiver
Print-rich environment
Promotion of literacy
activities
Opportunities to read and

School
Direct instruction in
phonological processing
skills
High quality teacher
Print rich environment
Time spent in literacy
instruction

Child
Exposure to print
Cognitive ability
Vision and hearing abilities
Self-regulation skills
Attention skills
Ability to interact with
others while engaged in

Specific Skills
Alphabet Knowledge
Phonological Processing
Skills
Rapid Automatic Naming
of letters, digits, objects or
colors
Writing Letters & Writing

Figure 2
Summary of Factors Associated with Early Literacy Development
Curriculum-Based Measurements
The use of curriculum-based measurements (CBMs) has increased as a result of
legislative efforts (e.g. No Child Left Behind, 2001) to increase accountability in American
public schools and comply with the new special education guidelines and requirements outlined
in the Individuals with Disabilities Education Improvement Act (IDEIA) of 2004. The Dynamic
Indicators of Basic Early Literacy Skills (DIBELS) are a commonly used curriculum-based
measure to assess student growth in reading in the early grades. The DIBELS measures are
designed to measure the over-arching ideas that are key to early literacy success (Phonological
Awareness, Alphabetic Principle, Fluency, Vocabulary, and Comprehension) in a cost-effective
and efficient manner (University of Oregon, 2013). The DIBELS measures are frequently used
to assess the literacy progress and general outcomes of children in kindergarten through sixth
grade. Due to the overlapping nature of the DIBELS measures and the over-arching ideas that are
key to early literacy success, DIBELS measures are frequently used to assess kindergarten

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children. Kindergarten children are assessed in initial sound fluency, letter naming fluency,
phoneme segmentation fluency, and nonsense word fluency (University of Oregon, 2013).
The DIBELS measures are frequently used in schools for several reasons. The DIBELS
measures are flexible and appropriate for individual and group use and can be administered in a
matter of minutes. In addition, the DIBELS measures are designed to help teachers tailor
instruction to best meet the needs of their students and monitor student growth across time. It is
important to note that the DIBELS were designed to be indicators of a student’s literacy skills
and overall reading competence as opposed to a finite measure of literacy skills or reading
competence. On a group level, DIBELS measures can be used to allocate intervention resources
and refine and reform curriculum based on students’ needs (Kaminski et al., 2008).
Recently, the validity of CBMs has been called into question since CBMs are often used
to make high-stakes decisions in Response to Intervention Models (Catts, Petscher,
Schatschneider, Bridges, & Mendoza, 2009; Schatschneider, Wagner, & Crawford, 2008).
However, CBMs were not originally designed to be used to make high-stakes decisions. The
DIBELS oral reading fluency (ORF) measures have a strong validity base when the ORF
measures are used for their original intention – to indicate a child’s overall reading competence.
Despite the recent emergence of DIBELS in schools across the country, the oldest ORF
validity study was published over 30 years ago by Deno, Mirkin, & Chiang (1982). Researchers
examined the relationship between several curriculum-based measures of reading. Data from 88
typical students and 56 students with a learning disability in first through sixth grade indicated
that the ORF CBM was most strongly correlated with standardized tests of reading (r=.71 to
.91). Fuchs, Fuchs, & Maxwell (1988) also published a historical validity study of CBMs using a
sample of middle school students receiving special education services. Oral reading fluency

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CBMs were more highly correlated with selected Stanford Achievement Subtests than other
CBMs (Fuchs et al., 1988).
More recent studies have also supported the validity of CBMs in reading. Ninety-seven
students in third grade general education classrooms were given the Iowa Test of Basic Skills
(ITBS), reading subtests of the Woodcock-Johnson III (WJ-III BR), and four R-CBM probes to
determine the predictive validity of CBM versus a standardized achievement test in predicting
reading achievement (Ardoin et al., 2004). Results of the study indicated that scores on the WJIII BR were strongly correlated with student performance on the R-CBM (r=.70). The R-CBM
predicted WJ-III BR scores equally as well as the total reading score on the ITBS. However,
regression analyses indicated that R-CBM explained more of the variance in a student’s total
reading achievement on the WJ-III, but the ITBS comprehension task explained more of the
variance in comprehension skills measured by the WJ-III. These results suggest that although RCBM and the ITBS predicted students’ basic reading skills equally well, educators need to
carefully consider what type of information they are seeking during universal screenings (Ardoin
et al., 2004).
In another study, oral reading fluency data from approximately 9,600 students enrolled in
34 Oregon Reading First schools was used to predict student performance on the Stanford
Achievement Test – Fourth Edition (SAT-10) and the Oregon State Reading Assessment
(OSRA) (Baker et al., 2008). Grade 1 winter ORF probes correlated .72 in the winter and .82 in
the spring with the Grade 1 SAT-10. Grade 2 spring ORF probes correlated .80 with the Grade 2
SAT-10. The ORF level and ORF slope explained 70% of the variance on the SAT-10 reading
test administered at the end of second grade. Overall, ORF rates from first to third grade were

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associated with performance on the SAT-10 reading test in grade two and the OSRA test in grade
three, with most correlations ranging from .60 to .80 (Baker et al., 2008).
Recently, researchers completed a comprehensive review of Curriculum-Based
Measurement in Reading (CBM-R) (Ardoin, Christ, Morena, Cormier, & Klingbeil, 2013). The
review included 171 journal articles and other written sources. Overall results of the review
indicated that there is limited psychometric or empirical support for using CBM-R probes to
make high-stakes decisions about individual children. Research is inconsistent in the number of
data points that should be collected and whether growth outcomes should be measured using data
points or the trend line. However, curriculum-based measurements in reading are considered
appropriate for measuring relative rates of student growth, identifying whether students are
meeting benchmark reading objectives, and assessing the effect of reading instruction on large
groups of students (Ardoin et al., 2013).
In another recent article, researchers used a new methodology to answer questions related
to CBMs in arguably the most efficient and effective way possible (Christ, Zopluoglo,
Monaghen, &, Pike-Balow, & Van Norman, 2013). Researchers completed five studies using
simulation methods to better understand the reliability and validity of CBM in oral reading.
Simulations involved several different progress monitoring durations, schedules, and data set
quality types. Overall results of the study indicated that validity was greater than .70 after eight
to sixteen weeks of progress monitoring, depending on the quality of the dataset. Reliability was
greater than .70 and sufficient for low-stakes decisions after ten to eighteen weeks of progress
monitoring, depending on the quality of the dataset. High stakes decisions (reliability greater
than .90) required 14 weeks of progress monitoring with a very high quality data set. Very poor
data sets were not reliable enough for any type of decision-making. One of the most important –

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and unexpected- findings of the study was that student growth is best demonstrated with progress
monitoring tools over a long period of time with a small number of data points rather than a short
period of time with several data points. In addition, the quality of the passage is extremely
important (Christ et al., 2013). Although the use of CBMs has evolved over time for purposes
not originally intended by the creators, it is important to remember that policy is often ahead of
research.
“When something has a low level of evidence, it does not mean that it is bad or poor
practice. What is suggested is that there is a need for increased research about the
practice and the use of the practice needs to be done with appropriate cautions”
(Christ, 2013, p.62).
In this study, the DIBELS measures are used provide a gauge of a student’s general
reading competence and reading skill set – consistent with the original purpose of CBMs and the
original validity studies supporting the use of ORF CBMs to gauge reading progress.
Current Study Research Questions and Hypotheses
Making the transition from early childhood care to the more formal, structured, and
demanding kindergarten classroom is an important milestone for young children and their
families. Research clearly indicates that overall, early childhood education provides positive
outcomes for all children although children from disadvantaged backgrounds stand to benefit
more from high quality early childhood programs (Burger, 2010). Ensuring that children are
equipped with appropriate school readiness skills prior to transitioning to kindergarten helps
promote their wellbeing. Children’s early literacy skills include foundational elements such as
alphabet knowledge, phonological awareness, rapid automatic naming (RAN) of letters or digits,
RAN of objects or colors, writing letters or writing one’s name, and phonological memory

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(NELP, 2009). Early social-emotional skills, particularly self-management and relational skills,
are clearly linked to academic success and mental health and wellbeing in elementary school and
beyond. The acquisition of school readiness skills is influenced by a children’s environment and
several demographic variables have been linked to the acquisition of school readiness skills
including socioeconomic status, level of maternal education, and English language proficiency
(Barnett, 2008). Many types of kindergarten transitional programs exist to foster school readiness
skills and promote children’s short and long-term success in school, and determining which types
of transitional kindergarten programs are the most effective for specific early childhood
populations is an ongoing endeavor.
The majority of the literature pertains to early childhood programs designed for children
who are not yet age-eligible for kindergarten entry. There is a lack of research pertaining to DK,
a specific type of early childhood intervention designed for children who are age-eligible for
kindergarten. Moreover, there is even less evidence documenting the effects of DK on children
from advantaged backgrounds. This study addressed a gap in the literature by examining the
long-term literacy and social-emotional growth of typically developing children who attended
DK compared to children from the same population who did not attend DK.
Research Questions and Hypotheses
1. What is the influence of age at kindergarten entry, gender, income, prior preschool
attendance, developmental kindergarten attendance, special education eligibility, and
school readiness skills (i.e., ability to follow structured daily routines, ability to work
independently with supervision, ability to listen and pay attention to what someone else is
saying, ability to get along with and cooperate with other children, ability to play with
other children, ability to follow simple rules, ability to work with puzzles, scissors,

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coloring, paints, etc., ability to write their own name, ability to count, ability to recite the
alphabet, ability to identify both shapes and colors) on children’s literacy growth
trajectories (i.e., MEAP scores, DIBELS scores)?
Hypothesis: The influence of age at kindergarten entry, gender, income, prior preschool
attendance, developmental kindergarten attendance, special education status, and school
readiness skills on literacy growth will fade across second, third, fourth, and fifth grade.
Rationale: The academic advantages associated with delayed entry into kindergarten are
typically salient during the first two years after the intervention but fade over time.
Domaleski and Oshima (2006) found that the academic advantage older kindergarten
students had over younger kindergarten students rapidly decreased during first, second,
and third grade and by middle school, the differences between the old and young group
were negligible. Stipek & Byler (2001) found that initially, older kindergarten students
had an academic advantage over younger students, but the advantage disappeared by the
time children were in third grade. In another study of old-for-grade kindergarten students
and young-for-grade kindergarten students, Lincove and Painter (2006) did not find any
differences in the long-term academic outcomes of the two groups.
2. What is the influence of age at kindergarten entry, gender, income, prior preschool
attendance, developmental kindergarten attendance, special education eligibility, and
school readiness skills (i.e., ability to follow structured daily routines, ability to work
independently with supervision, ability to listen and pay attention to what someone else is
saying, ability to get along with and cooperate with other children, ability to play with
other children, ability to follow simple rules, ability to work with puzzles, scissors,
coloring, paints, etc., ability to write their own name, ability to count, ability to recite the

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alphabet, ability to identify both shapes and colors) on children’s social-emotional
growth trajectories (i.e., social-emotional report card measures)?
Hypothesis: The influence of age at kindergarten entry, gender, income, prior preschool
attendance, developmental kindergarten attendance, special education eligibility, and
school readiness skills on social and emotional measures will remain constant across
time.
Rationale: Data from the ECLS suggested that attendance in a Pre-K program was
associated with reduced aggression and increased self-control in later years (Magnuson
et al., 2007). Children with developmentally appropriate social and emotional skills at
the time of kindergarten entry demonstrate fewer externalizing behaviors in later years
(Raver, 2004). Children’s social competence at kindergarten entry is correlated with
social competence in later years (Bornstein et al., 2010). Developmental kindergarten is
designed to foster children’s school readiness skills and enhance children’s social and
emotional competence. If this aim is achieved, children who attend developmental
kindergarten will have stronger social and emotional skills than their peers who did not
attend developmental kindergarten but shared other demographic characteristics.
3. Do school readiness skills at the time of kindergarten screening predict later literacy
(i.e. DIBELS scores and MEAP scores) and/or social-emotional growth (i.e. socialemotional report card measures)?
Hypothesis: School readiness skills at the time of kindergarten screening will predict later
literacy and social-emotional growth due to the stability of demographic factors
associated with the development of school readiness skills. The kindergarten screening
measure will have higher predictive validity for literacy outcomes than social -

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emotional outcomes.
Rationale: Kindergarten screeners designed to measure school readiness skills have little
predictive validity, lack empirical support, and vary based on context (Graue, 2010).
Children’s school readiness skills tend to vary more with group demographic
characteristics than individual characteristics prior to kindergarten entry (Hernandez et
al., 2007). Children from less affluent and minority backgrounds are more likely to have
lower school readiness skills and experience difficulty transitioning to kindergarten than
their more affluent and privileged peers (Rimm-Kaufman et al., 2000). Risk factors
related to school readiness are usually related to economic disadvantage (Hair et al.,
2006) and gaps in school readiness tend to increase over time (Klein & Knitzer, 2006).
As a result of the stability of the risk factors associated with school readiness skills
measured by kindergarten screeners, school readiness scores at the time of kindergarten
screening will predict academic and social-emotional outcomes; based on the results of
the study by La Paro & Pianta (2000) it is expected that the predictive validity of the
kindergarten screener will be higher for academic outcomes than social- emotional
outcomes. In a meta-analytic review of 70 longitudinal studies consisting of
predominantly homogenous Caucasian populations, social and emotional competencies
measured on kindergarten screeners accounted for less than 10% of the variance in later
elementary outcomes and academic competencies accounted for approximately 25% of
variance in early school/academic cognitive performance (La Paro & Pianta, 2000).

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Chapter 3
METHOD
Participants
The data for this study were collected from student CA-60 files housed at eight
elementary schools in one suburban school district in Michigan. The school district is located in
a community of approximately 6,000 residents and has received national academic distinctions.
According to the 2008-2012 American Community Survey, median household income in the
community is $55,000, median home value is approximately $150,000, and 44% of citizens
between 25 and 64 years of age have at least a bachelor’s degree (United States Census Bureau,
2014).
At the time of data collection, all children were currently enrolled in kindergarten, first,
second, third, fourth, or fifth grade. The sample consisted of 1082 students including 526 boys
(49%) and 556 girls (51%). Thirty percent of the sample (N=325) attended DK. Fifty-seven
percent of students enrolled in DK were boys (N=184) and 43% of students enrolled in DK were
girls (N=141). Ages of children in the entire sample ranged from 66 months to 147 months
(M=103.36, SD=21.18 months). Average age at kindergarten entry for all children was 67.72
months (SD=4.53). The average age at kindergarten entry for children who did not attend DK
was 65.65 months (SD=3.56) and the average age at kindergarten entry for children who
attended DK was 72.52 months (SD=2.41). Significant differences between children who did and
did not attend DK are outlined in Table 5.
Ten percent of the sample (N=103) qualified for free and reduced price lunch (FRPL)
during the 2012-2013 school year. Nine percent of children (N=67) who did not attend DK
qualified for FRPL and 11% (N=36) of children who did attend DK qualified for FRPL during

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the 2012-2013 school year. During this same school year, 19% of all students in the school
district qualified for FRPL and 48% of students across the state of Michigan qualified for FRPL
(Center for Educational Performance and Information, 2013), reflecting the high level of
financial resources in the community.
Preschool information was obtained from parental self-report in a questionnaire given to
parents on the day of kindergarten screening. Seventy-five percent (N=809) of all children
attended preschool, ten percent (N=106) did not attend preschool, and fifteen percent of children
(N=167) did not have information on file. Of the children who did not attend DK, 77% (N=579)
attended preschool prior to the kindergarten screening, 8% percent of children (N=59) did not
attend preschool prior to the kindergarten screening, and preschool information was not available
for 16% (N=199) children. Of the children who attended developmental kindergarten the school
year after the kindergarten screening, 71% (N=230) attended preschool prior to the kindergarten
screening, 15% (N=47) of children did not attend preschool, and 15% (N=48) did not have
preschool information on file.
Four percent of children (N=41) became eligible for special education services at some
point between kindergarten and fifth grade. Fifty-nine percent (N=24) of the children who
became eligible for special education services did not attend DK and forty-one percent (N=17) of
children who became eligible for special education services attended DK. Five children (<1%)
who did not attend developmental kindergarten were retained in kindergarten. All children who
attended developmental kindergarten were promoted in kindergarten and subsequent grade
levels.

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Table 5
Significant Differences Between Groups Based on Percentage

Demographic
Gender
Girls
Boys
Qualify for FRPL
Preschool
Attendance
Eligibility for
Special Education
Services after
kindergarten
Average Age at
Kindergarten Entry
(months)

Did not Attend DK
(N = 757)

Attended DK
(N = 325)

p

<.001
55.0 (415)
45.0 (342)
9.0 (67)

43.0 (141)
57.0 (184)
11.0 (36)

76.0 (579)

3.0

(24)

66.0

.25

71.0 (230)

<.003

5.0

.10

73.0

(17)

<.001

Note. P values are based on Chi Square Tests of Independence. The p value for average age at
kindergarten entry is based on an Independent-Samples T Test.
Table 6
Sample Size by Grade Level and School ID
ID
N (K)
N (1st)
N (2nd)
N (3rd)
N (4th)
N (5th)
N (Total)
1
22
26
34
34
29
32
177
2
27
11
30
5
16
17
106
3
30
26
24
36
13
129
4
24
14
38
5
11
33
22
26
16
28
136
6
22
17
26
19
15
18
117
7
28
27
32
28
19
27
161
8
41
41
41
32
23
32
210
Total
205
181
209
194
131
154
1074
Note. This sample size is smaller than the original sample due to missing outcome data.
Inclusion criteria. Children were included if they attended school in the same school
district in DK or kindergarten through fifth grade, a kindergarten screener was present in the CA60, and they were not eligible for special education services prior to kindergarten.

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Description of DK Program. From fall 2008 to spring 2012, the DK program was a
half-day (three and one-half hours) program held five days a week for approximately seventeen
and one-half hours each week with an average class size of 20 students. Due to changes in state
policy, the DK program became a full day program in fall 2012. Children attend DK
approximately 35 hours a week. The DK program is integrated with the K-12 programming in
the school district, and all children have the option of free public transportation to and from
school. All developmental kindergarten teachers (N=16) have bachelor’s (38%) or master’s
(62%) degrees and valid teaching certificates in the state of Michigan. Each DK classroom has
one paraprofessional to assist with classroom activities for one-half of each school day.
Acknowledging the teacher quality in the DK classroom is important to note, as several studies
have identified teacher quality as an important component of early childhood educational
environments (Howes et al., 2008; LoCasale-Crouch et al., 2007; National Association for the
Education of Young Children, 2009). An established DK curriculum does not exist. Each DK
teacher creates his or her own lesson plans that promote student mastery of the DK objectives on
the progress report (Appendix D).
Variables Considered in the DK Placement Process. Children in this study were
screened in April prior to kindergarten entry to see if their school readiness skills were
appropriate for kindergarten placement or necessitated a year of DK (typical of a maturational
model). The decision to enter DK or kindergarten is made by a team of individuals using a
kindergarten screener that asks assessors to obtain both objective and subjective data. Examples
of objective data include a child’s documented awareness of concepts of print, answers to
comprehension questions based on a short story, the ability to write one’s name, and
demonstrating one-to-one correspondence categorizing objects into groups based on prompts

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(e.g., color, function, material). Examples of subjective data include a child’s ability to pay
attention to a story, behavior in a large group setting, or interactions with other children during
free-play activities. Although educators conducting the kindergarten screenings collect both
qualitative and quantitative data related to kindergarten readiness skills and share their placement
opinion with parents, parents have ultimate authority in determining their child’s placement.
Description of Kindergarten Program. From fall 2008 to spring 2012, all kindergarten
classes from were held for approximately 18 hours each week, with each week consisting of two
full days and one half day of school. In fall 2012, kindergarten classes were held all day, every
day for approximately 35 hours per week with an average class size of 25 students. All
kindergarten teachers have bachelor’s or master’s degrees and valid teaching certificates in the
state of Michigan. The average number of years of teaching experience is 14 years. Each
kindergarten classroom has one paraprofessional to assist with classroom activities for one-half
of each school day.
All children were involved in the same spring kindergarten screening process prior to the
beginning of the kindergarten or DK school year. School personnel and parents make the
decision in April to enroll each student in either DK or kindergarten the following September
marking the beginning of the new school year. Children who attended DK began kindergarten
the following school year.
Measures
Kindergarten Screening Measure. Few standardized measures of kindergarten
readiness exist and most kindergarten screeners are developed based on the needs and values of
individual school communities. As a result, creating kindergarten screening measurement tools
with adequate reliability and validity is challenging (Graue, 2010) since it is difficult to create an

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assessment for a construct that lacks a standard operational definition. Despite the widespread
use of community-based kindergarten screening measures, the measures have limited predictive
validity and researchers caution using the screeners to determine placement decisions (Snow,
2010). However, a kindergarten screener was scored and used as part of this study since the
screener is an integral part of the kindergarten placement process at this suburban Michigan
school district. School staff created the kindergarten screening measure used in this study. In
order to obtain a measure of predictive validity, the literacy scores on the kindergarten screener
were correlated with third grade reading and math scores. During the kindergarten screening
process, teachers read students a short story and ask children comprehension questions about the
story. In addition, children are tested on concepts of print and phonemic awareness and name,
number, and color recognition. Children are also asked to write their name, use scissors to cut on
a straight line, and answer general questions such as, “Tell me about your family” (Appendix A).
Kindergarten screening staff recorded children’s answers on the kindergarten screening measure
and noted any behavioral concerns during the screening process, such as inattentiveness during
the story, inattentiveness during the entire screening process, deficits in verbal abilities, difficulty
interacting with other children, or separation anxiety from caregivers. Kindergarten screening
staff members use the kindergarten screening measures to suggest placement decisions (DK or
kindergarten) to parents/guardians.
Scoring the Kindergarten Screener. For the purposes of this study, the author and a
graduate student used a rubric to score the kindergarten screener (Appendix B). Scoring criteria
were established using the early reading competencies identified by the National Early Literacy
Panel (2008) and social-emotional skills that evaluators consistently monitored during group
activities. These reading competencies include: alphabet knowledge, phonological awareness,

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RAN of letters or digits, RAN of objects or colors, writing letters or writing one’s name,
phonological memory, concepts of print, print knowledge, reading readiness, oral language, and
visual processing (NELP, 2008). Scores on the scoring rubric range from 0 to 26.
DIBELS Scores. Dynamic Indicators of Basic Early Literacy Skills – Next (DIBELS
NEXT) was used to assess individual literacy growth across time. The DIBELS measures are
used to measure selected components of the Big Ideas in Beginning Reading set forth by the
National Literacy Council in 2005. The DIBELS is an appropriate, standardized measure for
assessing English language literacy development for students in grades K-6 (Kaminski &
Cummings, 2007). The DIBELS measures are frequently used in research to assess literacy skills
and the effectiveness of different types of early childhood instruction (Zvoch, Reynolds, &
Parker, 2008; Zvoch & Stevens, 2013). Although the DIBELS is a widely used measure of
literacy proficiency, it is important to note that scores on the DIBELS measures have correlated
with the construct of cognitive control (Coldren, 2013). For example, verbal inhibitory executive
functioning skills are associated with performance on tests of phoneme awareness, letter
knowledge, and word reading (Foy & Mann, 2013). Self-regulation skills such as effortful
control, false belief understanding, and attention-shifting abilities are associated with math
reading ability in three to five year old children (Blair & Razza, 2007).
Although the cognitive demands with each DIBELS task may affect a child’s measured
output the DIBELS are considered an effective measure in the school setting. The Initial Sound
Fluency (ISF) and Phoneme Segmentation Fluency (PSF) measures both test phonemic
awareness skills, the Nonsense Word Fluency (NWF) measure tests mastery of the alphabetic
principle, and the Oral Reading Fluency (ORF) measure tests a child’s ability to read accurately
and fluently. Field tests of the DIBELS Next measures indicate that a composite score for the

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beginning, middle, and end of the kindergarten year and the beginning of the first grade year are
the most accurate measure of a student’s literacy skills (University of Oregon, 2012). After the
beginning of first grade, there is a negligible difference in the ability of the ORF score or the
composite score in predicting literacy achievement on the Stanford Early School Achievement
Test – 10th Edition (University of Oregon, 2012). For this reason, a DIBELS composite score
will be used to measure kindergarten and first grade literacy skills and the ORF score will be the
only score used to measure literacy skills in later grades. Due to the timing of progress
monitoring implementation in the school district, kindergarten DIBELS scores were not available
for current fourth graders, and kindergarten and first grade DIBELS scores were not available for
current fifth graders.
Letter Naming Fluency. The LNF test does not measure one of the five big ideas in
beginning reading, but it does measure a child’s level of risk. During this test, the examiner
presents the child with one page of upper and lowercase letters and asks the child to read as
many letters as he or she can. If a child does not know the letter, the examiner provides the child
with the letter. The score is the number of letters the child names correctly in one minute. The
test is administered during the beginning, middle, and end of kindergarten and first grade. The
one-month alternate reliability form of the LNF measure is .88 in kindergarten. The LNF
measure has .70 median criterion validity with the Woodcock-Johnson Psycho-Educational
Battery Readiness Cluster score in kindergarten and .65 in first grade (Good et al., 2004).
Initial Sound Fluency. The DIBELS ISF measure is designed to assess a child’s ability
to recognize and produce the first sound of a word presented orally. The examiner shows four
pictures to the child, names each picture, and asks the child to point to the picture that begins
with the sound the examiner states. The child is also asked to state the beginning sound of a word

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that the examiner orally presents to the child; the beginning sound matches one of the beginning
sounds in the four pictures. A child’s score is based on the number of correct sounds he or she
states in one minute. The ISF test is administered at the beginning, middle, and end of
kindergarten (University of Oregon, 2013). The alternate form reliability of the ISF measure is
.72 in the middle of the kindergarten year (Good et al., 2004). When the measure is administered
four times in kindergarten, the alternate form reliability increases to .91 (Nunnally, 1978). The
concurrent criterion-related validity of the ISF with the Woodcock-Johnson Psycho-Educational
Battery Readiness Cluster score is .36 in the middle of the kindergarten year and .36 at the end of
the first grade year (Good et al., 2004).
Phoneme Segmentation Fluency. The PSF task is designed to assess a child’s ability to
divide a word into phonemes. The examiner states a word with three to four phonemes, and asks
the child to segment the word. For example, if the examiner says “sun,” the child would say “/s/
/u/ /n/” to receive three points for the word. The number of correctly produced phonemes in one
minute determines the child’s final PSF score. The PSF test is administered at the beginning,
middle, and end of kindergarten and first grade. The two-week PSF alternate reliability is .88
(Kaminski & Good, 1996), and the one-month alternate-form reliability is .79 at the end of
kindergarten (Good et al., 2004). At the end of kindergarten, the concurrent criterion validity of
the PSF is .54 with the Woodcock-Johnson Psycho-Educational Battery Readiness Cluster score.
The predictive validity of the first grade PSF with the Woodcock-Johnson Psycho-Educational
Battery Readiness Cluster score is .68 (Good et al., 2004).
Nonsense Word Fluency. The NWF task measures a child’s mastery of the alphabetic
principle. During this task, children are tested on letter-sound correspondence and their ability to
blend letters in words. Children are presented with randomly ordered vowel-consonant and

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consonant-vowel-consonant words (e.g., yit, uv) and asked to produce as many letter-sounds as
he or she can or read as many words as he or she can. Children receive a score for the number of
correct letter sounds read and/or the number of correct whole words read. The NWF test is given
at the beginning, middle, and end of kindergarten, first grade, and second grade. The one-month
alternate form reliability of the NWF measure in the middle of first grade is .83 (Good et al.,
2004). The concurrent criterion-related validity of the NWF measure with the WoodcockJohnson Psycho-Educational Battery Readiness Cluster score ranges from .36 to .59 in first
grade. The predictive validity of the NWF measure is .82 in the middle of first grade with the
DIBELS ORF measure, .60 at the end of second grade with the DIBELS ORF measure, and .66
with the Woodcock-Johnson Psycho-Educational Battery Readiness Cluster score (Good et al.,
2004).
Oral Reading Fluency. The most well established predictor of reading ability is oral
reading fluency (ORF) (Deno et al., 1982; Shinn, 1989; Burke & Hagan-Burke, 2007). During
the ORF test, students are asked to read a grade-level appropriate passage. The number of words
read correctly in one minute determines the student’s score. The DIBELS ORF measure has
strong reliability and validity; inter-rater reliability ranges from .94 – 1.00, composite score
alternate form reliability ranges from .66 to .97, and test-retest reliability ranges from .81 - .94
(Good & Kaminski, 2011). Psychometric studies assessing the reliability and validity of
additional DIBELS measures such as Letter Naming Fluency, Phoneme Segmentation Fluency,
and Nonsense Word Fluency have concluded that these measures have adequate reliability and
validity (Burke & Burke-Hagan, 2007). However, further research is needed to determine the
psychometric properties for DIBELS measures in each grade. The ORF measure is given at the
beginning, middle, and end of first through sixth grade.

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Rationale. DIBELS scores collected at the beginning, middle, and end of each academic
year will be used to assess a student’s literacy skills from kindergarten through second grade.
Subtests used in the data analysis were based on the recommended sequence of assessments
published by the University of Oregon DIBELS Data System (University of Oregon, 2012).
Table 3 provides a complete list of DIBELS scores that will be used in the analysis. The school
district uses these DIBELS measures to monitor student progress and determine Response-toIntervention (RtI) eligibility and special education eligibility related to a learning disability in
reading.
Michigan Educational Assessment Program
The Michigan Educational Assessment Program (MEAP) is a standardized assessment
administered to all students in third through ninth grade attending public schools in the state of
Michigan. The MEAP test is administered during the fall and spring of the school year as part of
the regular school day. Content on the MEAP test is derived from the Michigan Grade Level
Content Expectations (GCLE). The MEAP is used to assess each school district’s annual yearly
progress and is a critical component of school accountability in Michigan (MDE, 2013e). The
MEAP test is a criterion-referenced test that assesses student results against a performance
standard. The State of Michigan assumes that students who meet standards on the MEAP are
meeting grade level expectations. Appropriate accommodations are provided to students with
Individual Education Plans (IEP). The Michigan Educational Assessment Program provides a
continuous score for each subtest and assigns a categorical label to each score. The scores are
divided into four levels: Level 1 (Advanced); Level 2 (Proficient); Level 3 (Partially Proficient);
and Level 4 (Not Proficient). According to the 2010-2011 MEAP technical report, it is
appropriate to use MEAP scores to measure students’ academic achievement compared to state

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standards, measure student progress over time, target academic intervention efforts, and
determine if programs and policies are having the desired effect. In addition to providing
information about a student’s achievement relative to content standards, the MEAP also provides
a way to compare a student’s performance to a similar demographic group or the school district.
Michigan Educational Assessment Program scores are also used to determine middle school and
high school Michigan Merit Award recipients.
Reliability. Due to the high-stakes nature of the MEAP test in determining both
individual outcomes (e.g. Michigan Merit Awards) and district-level outcomes (e.g. overall
quality of education and attractiveness of the district to parents), all MEAP scores have
reliability greater than or equal to .90. This level of reliability is considered “high” (Field, 2009).
All testing items are reviewed for item difficulty, item discrimination, and differential item
functioning. Internal consistency reliability on the MEAP subtests are as follows: mathematics
.87 - .91; reading .83 - .87; science and social studies .80 - .89; and writing .89 and .87, (4th grade
and 7th grade, respectfully). Extensive inter-rater reliability processes and coding procedures are
used to ensure that qualitative responses such as the essays are score reliably. Inter-rater
agreement on the qualitative reading comprehension responses ranges from .89 to .98 and interrater agreement on the essay response ranges from .97 to .99 (MDE, 2011). Item response theory
reliabilities indicate that items are equally reliable for multiple subgroups including ethnicity,
gender, socioeconomic status, and limited English proficiency (MDE, 2011).
Validity. Several educational professionals and test development experts across the
country monitor the content of the MEAP test to ensure alignment with content standards the
MEAP test is designed to measure. Items that are not congruent with content standards are
revised or discarded. Currently, there is some evidence for construct validity but no evidence for

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criterion validity (MDE, 2011). Alignment studies for English and Language Arts (ELA)
indicated that alignment with content level expectations increased as grade level increased
because distinctions between objectives and specific grade-level content expectations became
more apparent. Thirteen mathematics reviewers indicated full alignment between the MEAP and
content-level expectations in grade six. Full alignment could be achieved by replacing one item
in grades four, five, and eight or by replacing three items in grade seven. Full alignment in grade
three required replacing six items. A team of nine science experts determined that the science
subtest lacked full alignment due to the difficulty of assessing the standard related to science
reflection or awareness. Overall, the alignment on the grade five and grade eight science tests
were considered acceptable. The process teams of experts used to align the MEAP subtests with
state GCLE provided evidence for content validity. At this time, MEAP criterion-related validity
data is not available, and limited data from 2005 is available to establish construct validity.
Available ELA and mathematics data indicate that the effect size of prior achievement is .60,
while effect sizes of demographic variables are negligible (.005 to .13) (MDE, 2011).
Rationale. Although there are limitations with respect to the validity of the MEAP test,
the MEAP scores were used as a dependent variable in this study because MEAP scores
influence academic decisions on an individual, school, and state level. All students attending
Michigan public schools are required to take the MEAP test, making the practicality and
familiarity of the MEAP test significant across the state. Due to the archival nature of this study,
MEAP test results were available in each student’s CA-60 file. Results of MEAP tests have been
used to measure academic achievement in other studies in peer-reviewed journals (Bettinger,
2005; Jackson et al., 2006; Neuenschwander et al., 2007)

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Data Collection
Permission from the district superintendent and assistant superintendent of the school
district was obtained to access the extant data. The author obtained approval from the Michigan
State University Institutional Review Board (IRB) prior to beginning the study. Data were
obtained from each student’s cumulative student record folder (CA-60), which includes each
student’s kindergarten screening measure. Data were collected from archival data stored in each
student’s CA-60 file and each student’s electronic DIBELS records. One graduate student in a
school psychology program and the researcher collected data on-site during a four-week period
in the summer. Training included an explanation of each piece of data collected and where to
find the data in the CA-60. Specific coding procedures for the kindergarten screener were
explained and coding materials were given to the graduate student. Prior to coding
independently, the graduate student scored ten CA-60s with the author. Then the graduate and
student scored groups of ten files independently and compared the data entered into the database
for each of the ten files. The author and the graduate student scored groups of 10 files
independently until .90 inter-rater reliability was achieved because this level of reliability is
considered “high” (Field, 2009). After the first day, the author and the graduate student randomly
checked two files each day to calculate reliability. If .90 reliability was not achieved, the author
and graduate student discussed the discrepancy and continued to compare data obtained from
files until .90 inter-rater reliability was achieved. Inter-rater reliability remained at .90 across
data collection sessions.
Data Analysis
Research Questions One and Two. To answer research questions one “What is the
influence of age at kindergarten entry, gender, income, prior preschool attendance,

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developmental kindergarten attendance, special education eligibility, and school readiness skills
on children’s literacy growth trajectories (i.e., MEAP scores, DIBELS scores)? and question
two, “What is the influence of age at kindergarten entry, gender, income, prior preschool
attendance, developmental kindergarten attendance, special education eligibility, and school
readiness skills on children’s social-emotional growth trajectories (i.e., social-emotional report
card measures)?, hierarchical linear modeling was used to compare the influence of common
predictors (Table 5) cited in the literature in the growth in literacy and social-emotional
development of the two groups (no DK/DK) across time. Hierarchical linear modeling was
chosen for several reasons. Hierarchical linear model is an advantageous statistical technique in
educational research because it accounts for the nesting effects inherent within schools
(individuals nested within classrooms nested within schools nested within districts) (Stage, 2001;
Francis, Shaywitz, Stuebing, Shaywitze, & Fletcher, 1996; Hart, Berniger, & Abbott, 1997).
Analyses were conducted using the Statistical Package for the Social Sciences (SPSS version 19)
software and HLM software (version 7.0; Raudenbush, Bryk, & Congdon, 2004).
In this study, student literacy growth and social-emotional growth were obtained through
a two-level hierarchical linear model. Students in the sample were divided into cohorts based on
their grade at the time of data collection, thus allowing for more control of changes occurring
across time. For example, the length of the kindergarten week was approximately two and onehalf days for five of the cohorts in the sample and five days a week for one cohort in the sample.
Growth in literacy skills was analyzed using the second, third, fourth, and fifth grade cohorts
individually. Growth in social-emotional skills was analyzed using the third, fourth, and fifth
grade cohorts individually. A minimum of three data points was necessary to calculate growth in

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either literacy or social-emotional skills. First level variables were centered using group mean
centering.
Equations
Level 1:
Growth= Observations) + r
Beta zero represents the intercept and represents observation scores for each individual
student. Observations for level one vary based on grade level. The following literacy
observations were used to calculate literacy growth for the following grades:
Second Grade
Kindergarten observation: End of Year DIBELS Composite (Letter Naming Fluency
+Phoneme Segmentation Fluency+ Nonsense Word Fluency Correct Letter Sounds); First grade
observation: End of Year Oral Reading Fluency; Second Grade: End of Year Oral Reading
Fluency
Please note: For each grade cohort, the raw DIBELS scores were standardized and the
standardized variables were used in the analysis.
Third Grade
Kindergarten observation: End of Year DIBELS Composite (Letter Naming Fluency
+Phoneme Segmentation Fluency+ Nonsense Word Fluency Correct Letter Sounds); First grade
observation, End of Year Oral Reading Fluency; Second Grade: End of Year Oral Reading
Fluency; Third Grade: MEAP Reading Standard Score
Please note: For each grade cohort, the raw DIBELS and MEAP scores were standardized and
the standardized variables were used in the analysis.

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Fourth Grade
Kindergarten observation: End of Year DIBELS Composite (Letter Naming Fluency
+Phoneme Segmentation Fluency+ Nonsense Word Fluency Correct Letter Sounds); First grade
observation: End of Year Oral Reading Fluency; Second Grade: End of Year Oral Reading
Fluency; Third Grade: MEAP Reading Standard Score; Fourth Grade: MEAP Reading Standard
Score
Please note: For each grade cohort, the raw DIBELS and MEAP scores were standardized and
the standardized variables were used in the analysis.
Fifth Grade
Kindergarten observation: End of Year DIBELS Composite (Letter Naming Fluency
+Phoneme Segmentation Fluency+ Nonsense Word Fluency Correct Letter Sounds); First grade
observation: End of Year Oral Reading Fluency; Second Grade: End of Year Oral Reading
Fluency; Third Grade: MEAP Reading Standard Score; Fourth Grade: MEAP Reading Standard
Score; Fifth Grade: MEAP Reading Standard Score
For a description of the social-emotional composite score, please see Table 8.
Please note: For each grade cohort, the raw DIBELS and MEAP scores were standardized and
the standardized variables were used in the analysis.

Level 2:
=00+01(SpecialEducation)+02(Male)+03(FRPL)+04(DKAttendance)+05(AttendPreschool)+
06(AgeKindergarten)+ 07(KindergartenScreener) + 08(Kinderteacher) + 09(School)+ uo
10+14(DKAttendance)+u1
The second level of analysis consisted of student, teacher, and school-level fixed effects.
Student level fixed effects in the model (01 - 07) included 01 special education status (0= never
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eligible for special education services, 1= eligible for special education services between
kindergarten and fifth grade), 02 gender (0=male, 1=female), 03 FRPL (0 = No Free/Reduced
Price Lunch, 1 = Free/Reduced Price Lunch), 04 developmental kindergarten attendance
(0=attended, 1=did not attend), 05 preschool attendance (0=did not attend preschool, 1=attended
preschool), 06 age at kindergarten entry (in months), and 07 kindergarten screener score (raw
score). Kindergarten teacher effects (07) were measured by creating a dummy variable for each
kindergarten teacher. School effects were measured by creating a dummy variable for each
school (08). Student, teacher, and school level variables were uncentered. Developmental
kindergarten attendance was considered a cross level interaction effect.
Research Question Three. To answer the third research question “Do school readiness
skills at the time of kindergarten screening predict later literacy (i.e., MEAP scores and DIBELS
scores) and/or social-emotional outcomes (i.e., social-emotional report card measures)?” a
regression analysis was used for each cohort (kindergarten, first, second, third, fourth, fifth). The
regression analysis is a one-year analysis; the most recent data point corresponding to each
cohort year was used in the regression analysis. For example, to determine the predictive validity
of the kindergarten screening measure for the DIBELS kindergarten composite score, the
DIBELS kindergarten composite scores of the kindergarten cohort were used. Analyses were
conducted using the Statistical Package for the Social Sciences (SPSS version 22).
Regression Analysis:
=0+1(SpecialEducation)+2(Male)+3(FRPL)+4(DKAttendance)+5(AttendPreschool)+
6(AgeKindergarten)+7(SchoolReadinessScreener) + 8(Kinderteacher) + 9(School)+ e

107

Student level predictors in the model (1-7) included 01 special education status (0=
never eligible for special education services, 1= eligible for special education services between
kindergarten and fifth grade), 02 gender (0=female, 1=male), 03 FRPL (0 = No Free/Reduced
Price Lunch, 1 = Free/Reduced Price Lunch), 04 developmental kindergarten attendance (0=did
not attend, 1=attended), 05 preschool attendance (0=did not attend preschool, 1=attended
preschool), 06 age at kindergarten entry (in months), and  school readiness screener score.
(standardized continuous score). Kindergarten teacher effects (08) were measured by creating a
dummy variable for each kindergarten teacher. School effects were measured by creating a
dummy variable for each school (09).
Missing Data. Approximately 5% of cases (N=32) in the second, third, fourth, and fifth
grade data sets had at least one missing literacy value. Due to the low percentage of missing data
statistical techniques to handle missing data were not used (Graham, 2009). Approximately 25%
of cases in the third, fourth, and fifth grade data sets had at least one missing social-emotional
score composite value. Due to the nature of the extant data set and the manner in which the
social-emotional composite score variable was calculated, the analyses were run using the raw
data collected and techniques for handling missing data were not used. Cases containing missing
variables were not used in the analyses.

108

Table 7
Variables Included in the Study
Variable
Information Origin
Age at Kindergarten Entry
Birth Month and Birth Year in CA-60
School Readiness Skills
Kindergarten Screening Score in CA-60 (Score ranging
from 0 – 32)
FRPL
Received from district administrator
Gender
Demographic information located in the front of the CA60
Preschool Attendance
Kindergarten Screening Parent Questionnaire located in
CA-60
Length of Kindergarten Day
Available from district administrator/Based on academic
year
DK Attendance
School year grid located in the front of the CA-60
Special Education Services
Individualized Education Plan paperwork located in the
CA-60
Teacher Education Level
Received from district administrator
Years Teaching Experience
Received from district administrator
School-Wide FRPL Count
Retrieved from Michigan Department of Education
website
Top-to-Bottom Percentile
Retrieved from Michigan Department of Education
Ranking
website
Outcome Measures
Kindergarten
EOY DIBELS Composite (LNF +PSF + NWF CLS)
Report Card Social-emotional Score Composite
First Grade

EOY ORF
Report Card Social-emotional Score Composite

Second Grade

EOY ORF
Report Card Social-emotional Score Composite
MEAP Reading
Report Card Social-emotional Score Composite

Third Grade
Fourth Grade

MEAP Reading
Report Card Social-emotional Scores Score Composite

Fifth Grade

MEAP Reading
Report Card Social-emotional Score Composite

109

Table 8
Proposed Research Questions, Measures, and Analytic Procedures
Research Questions

1. What is the influence
of age at kindergarten
entry, gender, income,
prior preschool
attendance, DK
attendance, special
education status, and
school readiness skills
on the literacy growth of
children in the sample?

2. What is the influence
of age at kindergarten
entry, gender, income,
prior preschool
attendance, DK
attendance, special
education status, and
school readiness skills
on the social-emotional
growth of children in the
sample?

Predictors

Dependent Variables

Measures

Analyses

Level 1: Student scores
at the end of each school
year

Standardized DIBELS
Scores/MEAP Test
Scores

Kindergarten: EOY
DIBELS Composite
(LNF +PSF + NWF
CLS)
First Grade: EOY ORF
Second Grade: EOY
ORF
Third Grade: MEAP
Reading Standard Score
Fourth Grade: MEAP
Reading Standard Score
Fifth Grade: MEAP
Reading Standard Score

HLM

Individual Report Card
Social-emotional
Composite Scores

Kindergarten through
Fourth Grade:
Exhibiting self-control
Showing active
involvement in the
learning process
Showing respect for
adults and children
Following directions
Working cooperatively
Organizing self,
materials, and

HLM

Level 2: Student
predictors (Age at
kindergarten entry,
gender, FRPL, preschool
attendance, DK
attendance, special
education status, school
readiness score),
Teacher Dummy
Variables, School
Dummy Variables
(See Question #1)

110

Table 8 (cont’d)

3. Do school readiness
skills at the time of
kindergarten screening
predict later literacy
and/or social-emotional
growth?

belongings
Using time wisely
Using good judgment in
asking for help
Doing personal best on
classroom work
Block 1: Age at
kindergarten entry,
gender, FRPL, preschool
attendance, DK
attendance, special
education status, teacher
dummy variables, school
dummy variables

Standardized DIBELS
Scores/MEAP Test
Scores & Annual Report
Card Social-emotional
Composite Score

Block 2: Kindergarten
School Readiness
Screener Score

Academic Measures
Kindergarten: EOY
DIBELS Composite
(LNF +PSF + NWF
CLS)
First Grade: EOY ORF
Second Grade: EOY
ORF
Third Grade: MEAP
Reading
Fourth Grade: MEAP
Reading
Fifth Grade: MEAP
Reading
Social-emotional
Measures
See Question 2

111

Regression

CHAPTER 4
RESULTS
Question One. To answer research question one “What is the influence of age at
kindergarten entry, gender, income, prior preschool attendance, developmental kindergarten
attendance, special education eligibility, and school readiness skills on children’s literacy
growth trajectories (i.e. MEAP scores, DIBELS scores)?”, a two level hierarchical linear model
was used. Descriptive statistics for the HLM models used in the analysis can be found in
Appendix F, Tables 21 – 24. The two level model was run in HLM 7 without using the teacher
and school dummy variables due to collinearity effects. Further analysis of the full model using a
regression model in SPSS indicated the model could not be run with the school and/or teacher
dummy variables included due to collinearity effects (Appendix G). The two level model was
run on four separate occasions for the second, third, fourth, and fifth grade cohorts.
Second grade. Results of fixed effects indicated special education eligibility (coefficient
-0.75, p<.002), developmental kindergarten attendance (coefficient (0.36, p=.05), and the
kindergarten screener score (coefficient 0.23, p<.007) were significant predictors of literacy
growth. Developmental kindergarten attendance was significant as an interaction effect
(coefficient -0.12, p=.09). Results of the null model indicated the final estimation of variance
components for Intercept 1: standard deviation = 0.82; variance component 0.68; degrees of
freedom = 207; chi square =1421.83, p<.001. Compared to the null model, the conditional
model accounted for an additional 16% of the variance between students.

112

Table 9
Second Grade Final Estimation of Fixed Effects – Literacy Growth
Fixed Effect
Coefficient
Standard
T-ratio Approx d.f.
Error
INTRCPT, 0
Intercept2, 00
-0.05
0.15
-0.34
200
Special Education, 01
-0.75
0.24
-3.14
200
Male, 02
-0.07
0.11
-0.67
200
FRPL, 03
-0.31
0.18
-1.71
200
DK Attendance 04
0.36
0.19
1.94
200
Attend Preschool, 05
-0.07
0.13
-0.59
200
Age at Kinder Entry, 06
-0.02
0.09
-0.26
200
Kindergarten Screener, 07
0.23
0.07
3.37
200
For SCORE, slope, 1
INTRCPT2, 10
0.08
0.04
1.83
382
DK Attendance, 14
-0.12
0.07
-1.68
382
Final Estimation of Variance Components
Random Effect
Standard
Variance
d.f.
2
Deviation
Component
Intercept 1, ro
0.75
0.57
200
1211.14
Level-1, e
0.56
0.31

p-value
.73
<.002
.50
.08
.05
.56
.80
<.001
.07
.09
p-value
<.001

Third grade. Results indicated special education eligibility (coefficient -0.61, p =.01) and
the kindergarten screener (coefficient 0.21, p =<.001) were significant predictors of literacy
growth. Developmental kindergarten attendance was significant as an interaction effect
(coefficient -0.12, p=.07). Results of the null model indicated the final estimation of variance
components for Intercept 1: standard deviation 0.63; variance component 0.40; degrees of
freedom= 189; chi square = 671.71, p <.001. Compared to the null model, the conditional model
accounted for an additional 18% of the variance between students.

113

Table 10
Third Grade Final Estimation of Fixed Effects – Literacy Growth
Fixed Effect
Coefficient
Standard
T-ratio
Error
INTRCPT, 0
Intercept2, 00
-0.06
0.13
-0.45
Special Education, 01
-0.61
0.23
-2.69
Male, 02
-0.09
0.10
-0.85
FRPL, 03
-0.10
0.13
-0.74
DK Attendance 04
0.07
0.15
-0.49
Attend Preschool, 05
0.19
0.12
1.61
Age at Kinder Entry, 06
0.07
0.07
1.00
Kindergarten Screener,07
0.21
0.05
4.01
For SCORE, slope, 1
INTRCPT2, 10
0.01
0.03
0.40
DK Attendance, 14
-0.10
0.05
-1.79
Final Estimation of Variance Components
Random Effect
Standard
Variance
d.f.
Deviation
Component
Intercept 1, ro
0.57
0.33
182
Level-1, e
0.76
0.58

Approx d.f.

p-value

193
193
193
193
193
193
193
193

.65
.01
.40
.46
.62
.11
.32
<.001

523
523

.69
.07

2
556.74

p-value
<.001

Fourth grade. Results indicated special education eligibility (coefficient -0.98, p=.04)
was a significant predictor of literacy growth. Developmental kindergarten attendance was not
significant as an interaction effect (coefficient -0.02, p=.80). Results of the null model indicated
the final estimation of variance components for Intercept 1: standard deviation 0.71; variance
component 0.51; degrees of freedom 129, chi square 651.48, p<.001. Compared to the null
model, the conditional model accounted for an additional 6% of the variance between students.

114

Table 11
Fourth Grade Final Estimation of Fixed Effects – Literacy Growth
Fixed Effect
Coefficient
Standard
T-ratio Approx d.f.
Error
INTRCPT, 0
Intercept2, 00
0.21
0.21
0.98
122
Special Education, 01
-0.98
0.50
-1.97
122
Male, 02
-0.06
0.14
-0.47
122
FRPL, 03
-0.21
0.32
-0.64
122
DK Attendance 04
0.15
0.23
0.65
122
Attend Preschool, 05
-0.20
0.21
-0.94
122
Age at Kinder Entry, 06
-0.10
0.10
-1.03
122
Kindergarten Screener
0.08
0.08
0.96
122
For SCORE, slope, 1
INTRCPT2, 10
0.00
0.03
-0.03
380
DK Attendance, 14
-0.02
0.07
-0.26
380
Final Estimation of Variance Components
Random Effect
Standard
Variance
d.f.
2
Deviation
Component
Intercept 1, ro
0.70
0.48
122
591.25
Level-1, e
0.70
0.50

p-value
.33
.04
.64
.52
.52
.35
.30
.34
.98
.80
p-value
<.001

Fifth grade. Results indicated attending preschool (coefficient 0.24, p=.05) was a
significant predictor of literacy growth. Developmental kindergarten attendance was significant
as an interaction effect (coefficient -0.11, p=.08). Results of the null model indicated for the final
estimation of variance components for Intercept 1: standard deviation 0.42; variance component
0.18; degrees of freedom 146; chi square 274.08; p< .001. Compared to the null model, the
conditional model did not account for any additional variance between students.

115

Table 12
Fifth Grade Final Estimation of Fixed Effects – Literacy Growth
Fixed Effect
Coefficien
Standard
T-ratio
t
Error
INTRCPT, 0
Intercept2, 00
-0.07
0.13
-0.52
Special Education, 01
-0.38
0.27
-1.36
Male, 02
-0.20
0.10
-1.93
FRPL, 03
-0.14
0.25
-0.52
DK Attendance 04
-0.10
0.16
-0.65
Attend Preschool, 05
0.24
0.12
1.95
Age at Kinder Entry, 06
0.05
0.06
0.78
Kindergarten Screener, 07
-0.09
0.04
-2.23
For SCORE, slope, 1
INTRCPT2, 10
0.04
0.03
1.35
DK Attendance, 14
-0.11
0.07
-1.78
Final Estimation of Variance Components
Random Effect
Standard
Variance
d.f.
Deviation
Component
Intercept 1, ro
0.41
0.17
139
Level-1, e
0.94
0.88

116

Approx d.f.

p-value

139
139
139
139
139
139
139
139

.60
.18
.06
.60
.52
.05
.43
.30

487
487

.18
.08

2
252.93

p-value
<.001

Table 13
Average Raw Scores for Literacy Outcomes Across Time
Literacy Scores By Grade
Kindergarten
First
Second
Third
Fourth
Fifth
(SD=)
(SD=)
(SD=)
(SD=)
(SD=)
(SD=)
Second Grade
Cohort
DK
127 (35)
77 (36)
102 (34)
No DK
125 (40)
71 (35)
99 (36)
Third Grade Cohort
DK
119 (40)
64 (41)
93 (40)
338 (24)
No DK
112 (38)
68 (34)
109 (61)
346 (36)
Fourth Grade Cohort
DK
123 (42)
75 (41)
103 (33)
344 (23)
445 (26)
No DK
118 (33)
76 (37)
109 (37)
346 (24)
446 (27)
Fifth Grade Cohort
DK
110 (30)
74 (36)
130 (87)
341 (17)
450 (35)
501 (159)
No DK
115 (38)
73 (38)
115 (56)
343 (29)
450 (33)
520 (126)
Benchmark Score
100
40
90
300/324
419
521
Note. MEAP Benchmark scores refer to the minimum score necessary to receive a “Proficient” rating. The minimum score for
the fifth grade cohort to receive a “Proficient” rating for the third grade MEAP reading test was 300. For the third and fourth
grade cohorts, the minimum score necessary for a “Proficient” rating on the MEAP reading test was 324. Literacy outcomes are
as follows: kindergarten (Kindergarten DIBELS Composite Score); first and second grade (End of year DIBELS Oral Reading
Fluency); third, fourth, and fifth grade (MEAP Reading Standard Score).

117

Table 14
Percentage of Students Scoring at the Proficient or Advanced Level on the MEAP Test
2012-2013 School Year
2011-2012 School Year
Study Sample
Statewide
Study Sample
Statewide
Third Grade Cohort
.80
.66
-

2010-2011 School Year
Study Sample
Statewide
-

Fourth Grade Cohort

.79

.68

.74

.63

-

-

Fifth Grade Cohort

.94

.71

.86

.67

.94

.64

118

Question Two. To answer research question two “What is the influence of age at
kindergarten entry, gender, income, prior preschool attendance, developmental kindergarten
attendance, special education eligibility, and school readiness skills on children’s socialemotional growth trajectories (i.e. report card social-emotional scores)?”, a two level
hierarchical linear model was used. The two level model was run in HLM 7 without using the
teacher and school-level variables due to collinearity effects. Further analysis of the full model in
SPSS indicated the full model could not be run due to collinearity effects. The two level model
was run on three separate occasions for the third, fourth, and fifth grade cohorts because students
in those cohorts had a minimum of three social-emotional data points.
Third grade. Results indicated that none of the fixed effects were significant predictors of
social-emotional growth. Results of the null model indicated for the final estimation of variance
components for Intercept 1: standard deviation 0.66; variance component 0.44; degrees of
freedom 151; chi square 437.61; p <.001. Compared to the null model, the conditional model did
not account for any additional variance between students.

119

Table 15
Third Grade Final Estimation of Fixed Effects – Social-Emotional Growth
Fixed Effect
Coefficient
Standard
T-ratio Approx d.f.
Error
INTRCPT, 0
Intercept2, 00
-0.33
0.10
3.51
144
Special Education, 01
-0.24
0.37
-0.65
144
Male, 02
-0.25
0.13
-1.82
144
FRPL, 03
-0.24
0.14
-1.79
144
DK Attendance 04
-0.06
0.18
-0.34
144
Attend Preschool, 05
-0.21
0.11
-1.85
144
Age at Kinder Entry, 06
0.03
0.07
0.42
144
Kindergarten Screener, 07
0.07
0.07
0.94
144
For SCORE, slope, 1
INTRCPT2, 10
0.02
0.06
-0.26
204
DK Attendance, 14
-0.04
0.12
-0.39
204
Final Estimation of Variance Components
Random Effect
Standard
Variance
d.f.
2
Deviation
Component
Intercept 1, ro
0.65
0.43
144
405.72
Level-1, e
0.75
0.56

p-value
<.001
.52
.07
.46
.74
.07
.68
.35
.80
.70
p-value
<.001

Fourth grade. Results indicated male gender (coefficient -0.51, p<.004 ) was a significant
predictor of social-emotional growth. Developmental kindergarten attendance was significant as
an interaction effect (coefficient -0.25, p<.002). Results of the null model indicated for the final
estimation of variance components for Intercept 1: standard deviation 0.64; variance component
0.41; degrees of freedom 94; chi square 338.07; p <.001. Compared to the null model, the
conditional model did not account for any additional variance between students.

120

Table 16
Fourth Grade Final Estimation of Fixed Effects – Social-Emotional Growth
Fixed Effect
Coefficien
Standard
T-ratio Approx d.f.
t
Error
INTRCPT, 0
Intercept2, 00
-0.33
0.22
1.51
89
Special Education, 01
-1.11
0.70
-1.57
89
Male, 02
-0.51
0.17
-3.09
89
FRPL, 03
-0.13
0.22
-0.58
89
DK Attendance 04
0.09
0.27
0.37
89
Attend Preschool, 05
-0.13
0.21
-0.61
89
Age at Kinder Entry, 06
0.19
0.10
1.85
89
Kindergarten Screener, 07
0.01
0.09
0.06
89
For SCORE, slope, 1
INTRCPT2, 10
0.08
0.04
1.84
261
DK Attendance, 14
-0.25
0.08
-3.09
261
Final Estimation of Variance Components
Random Effect
Standard
Variance
d.f.
2
Deviation
Component
Intercept 1, ro
0.60
0.36
89
297.40
Level-1, e
0.75
0.56

p-value
.14
.12
<.004
.57
.72
.54
.07
.95
.07
<.002
p-value
<.001

Fifth grade. Results indicated that none of the fixed effects were significant predictors of
social-emotional growth. Developmental kindergarten attendance was not significant as an
interaction effect (coefficient -0.06, p=.20). Results of the null model indicated for the final
estimation of variance components for Intercept 1: standard deviation 0.66; variance component
0.44; degrees of freedom 114; chi square 456.80; p value <.01. Compared to the null model, the
conditional model did not account for any additional variance between students.

121

Table 17
Fifth Grade Final Estimation of Fixed Effects – Social-Emotional Growth
Fixed Effect
Coefficien
Standard
T-ratio Approx d.f.
t
Error
INTRCPT, 0
Intercept2, 00
-0.11
0.22
-0.48
107
Special Education, 01
-0.22
0.22
-1.01
107
Male, 02
-0.25
0.14
-1.77
107
FRPL, 03
-0.02
0.20
-0.01
107
DK Attendance 04
0.16
0.25
0.65
107
Attend Preschool, 05
0.23
0.20
1.14
107
Age at Kinder Entry, 06
-0.05
0.14
-0.35
107
Kindergarten Screener, 07
0.11
0.08
1.48
107
For SCORE, slope, 1
INTRCPT2, 10
0.02
0.03
0.68
308
DK Attendance, 14
-0.06
0.05
-1.27
308
Final Estimation of Variance Components
Random Effect
Standard
Variance
d.f.
2
Deviation
Component
Intercept 1, ro
0.65
0.42
107
416.08
Level-1, e
0.73
0.54

122

p-value
.63
.32
.08
.94
.52
.26
.73
.14
.50
.20
p-value
<.001

Table 18
Average Raw Scores for Social-Emotional Outcomes Across Time
Kindergarten
First
Second
(SD=)
(SD=)
(SD=)
Third Grade Cohort
DK
25.68 (2.09)
34.60 (2.30)
34.08 (3.16)
No DK
25.80 (1.79)
34.40 (3.06)
35.00 (4.52)
Fourth Grade Cohort
DK
25.88 (2.27)
34.18 (2.51)
34.31 (2.88)
No DK
25.65 (2.86)
34.78 (2.42)
34.68 (2.67)
Fifth Grade Cohort
DK
26.16 (1.51)
34.35 (3.16)
No DK
25.78 (1.87)
34.58 (2.42)
Highest Score Possible
27
36
36
Note. * Denotes significance at the 0.05 level.

123

Third
(SD=)

Fourth
(SD=)

-

-

46.28 (3.69)*
48.59 (2.82)*

-

47.76 (3.03)
48.55 (7.06)
55

44.26 (3.74)
44.25 (5.47)
50

Question Three. To answer question three, “Do school readiness skills at the time of
kindergarten screening predict later literacy and/or social-emotional growth?”, a regression
analysis was used. The regression analysis measures the predictive validity of the screener on an
annual basis. Results of the regression analysis using literacy scores as outcomes indicated that
the kindergarten screening measure was not a significant predictor of literacy outcomes for
kindergarten (∆R2= .01, F[1,175 ]=2.81, p =.10 ) first (∆R2=.02, F[27,148 ]=3.36, p=.07), fourth
(∆R2=.04, F[21,64 ]=1.51, p =0.11), and fifth grade (∆R2=.01, F[21,124]=2.25, p =0.14 ) literacy
outcome measures. Results indicated the kindergarten screener was a significant predictor of
second (∆R2=.04, F[23,166 ]=2.34, p <.0001) and third grade (∆R2=.01, F[21,64 ]=1.51,
p =0.04) literacy outcomes.
Table 19
Predictive Validity of Kindergarten Screening Measure Across Time for Literacy Outcomes
Kindergarten
R R2 Adjusted Std. Error of R2
F
df1 df2 Sig F
2
Model
R
the Estimate Change Change
Change
1
.56 .32 .23
.86
.32
3.70
22 176 .00
2
.57 .33 .24
.85
.01
2.81
1
175 .10
First Grade
Model
1
.47 .22 .08
.97
.22
1.53
27 148 .06
2
.49 .24 .09
.96
.02
3.36
1
147 .07
Second Grade
Model
1
.50 .25 .14
.93
.25
2.34
23 166 .00
2
.54 .29 .18
.90
.04
9.81
1
165 .00
Third Grade
Model
1
.76 .58 .51
.69
.58
8.02
27 157 .00
2
.77 .59 .52
.68
.01
4.23
1
156 .04
Fourth Grade
Model
1
.58 .33 .11
.95
.33
1.51
21 64 .11
2
.59 .35 .12
.94
.02
1.58
1
63 .21
Fifth Grade
Model
1
.53 .28 .15
.96
.28
2.25
21 124 .00
2
.54 .29 .16
.96
.01
2.21
1
123 .14
124

Results of the regression analysis using social-emotional scores as outcomes indicated
that the kindergarten screening measure was not a significant predictor of social-emotional
outcomes for second (∆R2= .01, F[1,82 ]=1.09, p =.30 ), third (∆R2=.02, F[1,63 ]=1.51, p=.21),
and fourth grade (∆R2=.00, F[1,93]<.0001, p =0.96 ) social-emotional outcome measures.
Results indicated the kindergarten screener was a significant predictor of kindergarten (∆R2=.05,
F[1,102 ]=7.58, p <.001) and first grade (∆R2=.11, F[1,81 ]=12.25, p <.001) social-emotional
outcomes.
Table 20
Predictive Validity of Kindergarten Screening Measure Across Time for Social-Emotional
Outcomes
Kindergarten
R R2 Adjusted Std. Error of R2
F
df1 df2 Sig F
Model
R2
the Estimate Change Change
Change
1
.57 .33 .18
.85
.33
2.28
22 103 .00
2
.61 .37 .23
.82
.05
7.58
1
102 .01
First Grade
Model
1
.37 .14 .00
1.00
.14
.94
14 82 .52
2
.50 .25 .11
.94
.11
12.25
1
81 .00
Second Grade
Model
1
.44 .20 .02
.69
.20
1.17
18 83 .35
2
.45 .21 .02
.67
.01
1.09
1
82 .30
Third Grade
Model
1
.58 .33 .11
.95
.33
1.51
21 64 .11
2
.59 .35 .12
.94
.02
1.58
1
63 .21
Fourth Grade
Model
1
.69 .47 .37
.79
.47
4.72
18 94 .00
2
.69 .48 .37
.80
.00
.00
1
93 .96

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CHAPTER 5
DISCUSSION
Parents are charged with continually making decisions on behalf of their children, which
can be a particularly daunting endeavor. Decisions surrounding kindergarten entry, an important
milestone in the life of a child raised in America, often leave parents wondering if they made the
right or wrong decision based on a variety of factors including their child’s age, school readiness
skills, ability to interact with other children in social situations, and general observations of their
child in comparison to his peers. As with most decisions, careful analysis of the benefits and
drawbacks in conjunction with peer-reviewed research does not guarantee a parent that he or she
made a right or wrong decision. But data exist to help a parent make an informed decision. The
purpose of this study was to add to the early childhood literature base and help aid educators and
parents in making an informed decision surrounding the potential academic and social-emotional
benefits of DK, a specific type of early childhood intervention. In light of informed decision
making, the homogeneity, affluence, and stability of the sample size used for this study should be
taken into account and carefully compared and contrasted with results of studies that include
samples comprised of children from other demographic and developmental backgrounds.
The primary purpose of this study was to explore the literacy and social-emotional
growth across time of children who attended DK compared to children who did not attend DK as
well as the influence of common student-level predictors associated with success in school. The
secondary purpose of this study was to determine the predictive validity of the kindergarten
screener of later literacy and social-emotional outcomes. The first hypothesis was that the
influence of age at kindergarten entry, gender, income, prior preschool attendance, and

126

developmental kindergarten attendance on literacy growth would fade across time. This
hypothesis was partially supported.
Special education status, developmental kindergarten attendance and preschool
attendance were significant predictors of literacy growth, although these predictors were not
significant across all cohorts. Although special education eligibility was a significant predictor
across second, third, and fourth grade, the effect of special education eligibility on the intercept
fluctuated over time. Special education eligibility is often determined by poor academic
performance, making it logical that special education eligibility status would be correlated with
literacy scores across time. Unlike the results of this study, some studies have demonstrated that
the probability of special education eligibility increases for children who are young-for-grade
(Dhuey & Lipscomb, 2010; Martin et al., 2004). Although this study did not analyze probability
of special education eligibility based on age at kindergarten entry, it is interesting to note that age
at kindergarten entry was not a significant predictor of literacy growth.
The association between preschool attendance and improvements in literacy growth is
expected, as the evidence supporting the advantageous effects of preschool attendance is robust
(Camilli et al., 2010; Gormley et al., 2005; Magnuson et al., 2007). Preschool is associated with
positive effects for children from all backgrounds (Barnett, 2008; Goodman & Sianesi, 2005)
and increased levels of cognitive and social development (Sylva et al., 2004). Although the
academic effects of preschool are often found to be short term (Magnuson et al., 2007),
children’s gains are maximized when they attend high quality preschool programs and have a
positive relationship with the teacher (Howes et al., 2008).
The kindergarten screening measure was a significant predictor of literacy growth for the
second and third grade cohorts but was not a significant predictor of literacy growth for the

127

fourth and fifth grade cohorts. Although school readiness skills are associated with increased
academic outcomes (Snow, 2010) and cognitive abilities (Bornstein et al., 1996), these
associations appear to be stronger when children are younger and fade over time. Age at
kindergarten entry, gender, and income status were not significant predictors of literacy growth
at any point in time.
Across time, the differences in the literacy growth of children who attended DK versus
children who did not attend DK were not statistically significant. The raw scores presented in
Table 13 illustrate that from a statistical and practical perspective, the difference in the two
groups’ scores across time is negligible. The small differences in raw scores among the two
groups, particularly the differences in scores at the end of kindergarten, is a unique attribute of
this sample as typically more significant gains between pre and post kindergarten intervention
groups are evident immediately after the intervention year.
These results reflect the larger body of research on the effect of early childhood
interventions on later academic outcomes. For the majority of cohorts, children who attended DK
had higher literacy scores at the end of kindergarten but these gains faded over time. These
results are consistent with research indicating that the perceived benefits of delayed entry into
kindergarten fade over time (Domaleski & Oshima, 2006; Stipek & Byler, 2001). However,
studies on delayed kindergarten entry frequently focus on the age of children as opposed to the
experiences the children had prior to delaying kindergarten. Results across cohorts in this study
clearly indicated that age at kindergarten entry was not associated with growth in literacy skills
across time. Recent studies have indicated that some advances in skill development are due to
classroom-based experiences, whereas other advances are a result of biological maturation
(Bisanz et al., 1995; Skibbe et al., 2011). Moreover, results consistently indicated that the fixed

128

effects included in the model are not accounting for a significant proportion of the variance in
student growth over time.
The second hypothesis was that the influence of age at kindergarten entry, gender,
income, prior preschool attendance, developmental kindergarten attendance, special education
eligibility, and school readiness skills on social-emotional measures would remain constant
across time. This hypothesis was partially supported. Analyses of fixed effects indicated being
male was associated with a decline in social-emotional skill growth across all cohorts. This
finding is consistent with research indicating statistically significant gender gaps in selfregulation skills (Matthews et al., 2009). In addition, a substantial body of literature indicates
that females are more successful in building strong, positive relationships with teachers
throughout their educational career than males, ultimately improving females’ educational
experience (Duckworth & Seligman, 2006). In contrast, males are more likely than females to be
expelled, suspended, or drop out (Office of Juvenile Justice and Delinquency Prevention, 2006).
Receiving special education services, attending preschool, attending developmental
kindergarten, receiving free and reduced price lunch, and age at kindergarten entry were
negatively associated with growth in social-emotional skills at different points in time.
Although the specific reasons for the differences in predictors associated with lower socialemotional scores across cohorts are unknown, results are consistent with earlier research relating
to risk factors for social-emotional development including poverty, English language
proficiency, and maternal education (Barnett, 2013; Lee & Burkam, 2002; Rimm-Kaufman et al.,
2000). It is plausible that the demographic or skill-based factors associated with DK placement
resulted a negative association between DK attendance and social-emotional growth, but these
results do not imply causality. Consistent with special education placement rate as a significant

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predictor of social-emotional skill growth, reduced participation in classroom learning activities
has been associated with low academic achievement indicating children with lower socialemotional skills may be more at risk for poor academic or behavioral outcomes and potential
special education placement (Bierman, 2009; Raver, 2004). It is important to note that the
student level predictors did not account for any additional variance in social-emotional growth
compared to the null model, indicating that perhaps other student level variables would be more
appropriate for the model.
In general, the social-emotional growth of children who attended DK compared to those
who did not attend DK was not statistically different. It is important to note that based on the raw
scores provided in Table 18, from a practical standpoint, the social-emotional scores of both
groups were equivalent across time. The stability of the results of social-emotional scores across
time found in this study are consistent with the findings of Bornstein et al. (2010) that indicated
social competence in kindergarten was correlated with social competence in later years.
The third hypothesis was that the kindergarten screening measure would predict
academic and social-emotional growth trajectories due to the stability of demographic risk
factors associated with low school readiness skills at kindergarten entry. This hypothesis was not
supported. The kindergarten screening measure predicted literacy outcomes at the end of second
and third grade at a statistically significant level. Results were not significant for the
kindergarten, first, fourth, and fifth grade cohorts.
The kindergarten screening measure predicted social-emotional outcomes at a statistically
significant level at the end of kindergarten and first grade but not for subsequent grade cohorts.
These results are congruent with kindergarten teachers’ long-standing perception that socialemotional skills at the time of kindergarten entry are more relevant than a student’s academic

130

skills at the time of kindergarten entry (Lin et al., 2003). The difference in predictive validity
over time may be due to the evolution of social expectations over time that are measured
differently as children grow older. For example, whereas many of the social-emotional skills
measured on the kindergarten screener assess a child’s peer interactions that are contingent upon
reciprocal involvement with the child and others in his environment, as children grow older
social-emotional measures on the report cards often measure a child’s ability to complete work,
manage materials, and advocate for themselves. Although many of the social skills overlap
across time, the shift from extrinsic to intrinsic motivators to meet expectations. The overall
predictive validity of the kindergarten screener used in this study was less than the results of the
meta-analysis of 70 longitudinal studies done by LaParo & Pianta (2000). However, results of
this study are consistent with the overall notion that kindergarten readiness measures, whether
standardized or unstandardized, tend to lack validity and reliability (Graue, 2010; La Paro &
Pianta, 2000; Snow, 2010) in predicting later outcomes.
The lack of predictive validity across time of the kindergarten screener may be due in
part to the absence of key components of reading (i.e. phonemic awareness, phonics, and
fluency, vocabulary, and text comprehension) identified by the National Early Literacy Panel
(2000) on the kindergarten screener. Close examination of the kindergarten screener indicates
that skills related to phonemic awareness, phonics, and fluency are not directly measured by the
screener and may affect the overall validity of the screener. In contrast, the kindergarten screener
accounted for attention throughout the screening process, a documented mediator of behavioral
outcomes (Dice & Schwanenflugel, 2012; Razza et al., 2012).
It may be that the outcome variables associated with this study do not adequately capture
the skills that the kindergarten screener is designed to measure. For example, perhaps the

131

kindergarten screener is more predictive of mathematics scores across time or the number of
visits to the principal’s office or suspensions. It is also plausible that intensive intervention
efforts being implemented systematically such as Response to Intervention (RtI) or Reading
Recovery may be effective in diminishing the initial school readiness gap and leveling the
academic playing field. School-wide programs to intensively target social-emotional skills are
often less likely to be implemented, which may be a reason why the kindergarten screener was
predictive of students’ social-emotional skills at the end of kindergarten and first grade.
It is also possible that the kindergarten screening measure in this study was not as strong
of a predictor of academic or social and emotional growth because of the demographics of the
majority of children included in this study. Risk factors for school readiness skills are most
strongly associated with poverty including factors such as inconsistent parental work
opportunities, low parental education, low parental pay, and limited English proficiency (Harriet
et al., 2006; Hernandez et al., 2007). The majority of children all children included in this sample
had a school readiness score within one standard deviation of the mean, indicating that only a
small percentage of children in the sample lacked basic school readiness skills. In other studies,
approximately half of children have lacked necessary school readiness skills prior to
kindergarten entry due to factors associated with poverty (Rimm-Kaufman, 2000).
Implications
Although academic, cognitive, or social-emotional gains of an early intervention program
may fade over time, strong arguments have been made against interpreting the lack of long-term
academic or cognitive gains of children who attended early intervention programs as a reason to
discontinue a particular early intervention program. First and foremost, the long-term academic
outcomes can vary greatly based on the outcome measure used. Moreover, the long-term

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“success” of an early intervention program may not be best measured by academic, socialemotional, or overall cognitive ability. For example, perhaps a more relevant long-term outcome
of an early intervention is high school completion, employability, avoiding incarceration, or
overall physical health instead of a standardized academic achievement score or cognitive ability
score at some point in middle school or high school. Although the Abecedarian Preschool
Program was not associated with cognitive gains when children in the intervention and control
group reached middle school and high school, children in the intervention group were physically
healthier on several outcomes than children in the control group (Campbell, 2014).
James Heckman, a Nobel-prize winning economist, has published extensive work that
unequivocally indicates early interventions (interventions occurring from ages zero to five) have
a much higher economic return than interventions that target later stages in the lifespan
(Heckman, 2000). Heckman, as well as other proponents of early education and intervention,
would argue that the sleeping elephant of this overall study is the fact that children from this
community who experienced difficulty with aspects of the kindergarten screener did not have
access to high quality early intervention until they were age-eligible for kindergarten, and the
greatest window of opportunity for intervention was missed. Even after acknowledging the
sleeping elephant in the room, interpreting the results of this study for the intended audience –
school staff members, parents, and members of the community – is a difficult endeavor.
First and foremost, the study used for this sample is at much lower risk than the samples
often used in early intervention program. Results of this study of typically developing children
living in an advantaged community indicate that attending the DK program does not appear to
change the literacy or social-emotional growth of children across time, but it is important to note
that the two groups were nearly equal on literacy and social-emotional measures at the end of

133

kindergarten. Given the methodology of the study, it is not possible to determine the growth the
children who attended the DK intervention experienced during the intervention year that may
have placed them on a more equal playing field with their peers who did not attend the
intervention. Moreover, given the large gaps in raw scores on the 5th grade MEAP test between
the intervention and control group, it is possible that the intervention group’s scores would have
remained equivalent to or surpassed the non-intervention group’s scores if they had continued to
receive intensive intervention during the elementary years.
For the students in this sample, providing children with the “gift of time” or the
opportunity to mature by delaying kindergarten entry does not appear warranted based on the
outcome measures used for this study. However, it is important to note that if other cognitive (i.e.
a standardized intelligence test) or non-cognitive measures (e.g. motivation, persistence,
charisma) were used as outcome measures, the implications of the study might have been
different. The results of this study are congruent with the larger body of research indicating that
overall, the age at kindergarten entry is not associated with later long-term effects on academic
or social-emotional skills (Lincove & Painter, 2006; Stipek & Byler, 2001) and children who are
young-for-grade stand to benefit from attending school with their older peers (Cascio &
Schanzenbach, 2007).
Arguably, given the demographic factors of the school district, the typically developing
children included in this sample are not at the same risk that children in other communities may
be, influencing the overall effect of the DK intervention. This study further reinforces the
differential effects of early childhood programs based on a child’s socioeconomic status found in
other studies (Barnett, 2013; Bumgarner & Lin, 2014; Peisner-Feinberg & Schaaf, 2007; TuckerDrob, 2012; Winter & Klein, 1970). If children from more at-risk communities had access to this

134

same DK intervention and their literacy skill growth were later compared to children in their
same community who did not attend DK, the growth patterns of the DK versus non-DK groups
may be different than the growth patterns found in this study.
The implications of this study may be less related to literacy and social-emotional growth
trajectories and more related to the ability of a school district to improve the outcomes of
children who are at-risk when a small percentage of children in the district are at risk. The
overall percentage of children receiving FRPL in this sample of children was 10% while the
overall state average was 48%. Not only do children from disadvantaged backgrounds learn more
when they are learning alongside children from advantaged backgrounds, early childhood
programs in affluent communities are typically associated with more enriching activities and
overall high levels of quality than early childhood programs in less affluent communities (Early
et al., 2010; Hatfield et al., 2014).
Although the results of this study do not lend support for DK programs for children from
advantaged backgrounds, it is important to note that children from disadvantaged backgrounds
receive maximum benefits from early childhood programs when they attend integrated programs
with children from a variety of socioeconomic backgrounds (Hogden, 2007; Neidell &
Waldofogel, 2010; Schechter & Bye, 2007). Research indicates that the most at-risk children are
typically placed with other at-risk children in the poorest Pre-K quality classrooms (LoCasaleCrouch et al., 2007). Moreover, children tend to demonstrate growth relative to their baseline
skills in academic and social-emotional skills, and growth is often a function of the skill level of
other children in the classroom (Skibbe et al., 2012; Vallatoon & Ayoub, 2011). Thus, when
children are given the opportunity to rise to the skill level of other children around them, they
often do.

135

Focus on the community-level variables at play in this study is particularly important, as
school socioeconomic status has been shown to be just as important as student level
socioeconomic status in achievement growth (Rumberger & Palardy, 2005). It is the author’s
belief that the larger implication of this study is not the individual growth trajectories of children
who did versus did not attend DK, but the effects of strong general instruction, additional
remedial instructional supports, and the high density of resources available to children across
time may have been strong contributors to the literacy and social-emotional growth of the
typically developing children including in this study that reduced the effect of student level
predictors typically associated with school failure.
Although it is clear that early childhood is clearly a foundational and critical component
of human development across the lifespan (Shonkoff & Phillips, 2000), the current research base
and knowledge of the specific programs, mechanisms, instructional strategies, dosage effects,
and broad policies pertaining to young families designed to foster early childhood development
is still evolving. Analyzing the influence of early childhood interventions on later outcomes is
often a politically-charged endeavor, with both proponents and opponents having closely held
ties and direct and indirect personal stakes in the debate. Large-scale, comprehensive early
childhood programs such as the High/Scope Perry Preschool, Carolina Abedecarian Project,
Head Start, and Chicago-Child-Parent Centers all serve as examples of intensive early childhood
programs designed to enhance the quality of life of children and families involved in the
programs. Although, for example, the Chicago-Parent Center Preschool program is associated
with higher rates of high school completion and reductions in special education placement and
grade retention (Reynolds, 2000) these outcomes may or may not be directly related to the
literacy growth of these children in early childhood.

136

Future research is warranted to better understand the effect of DK attendance on the
academic and social-emotional growth trajectories of children identified with developmental
delays prior to kindergarten entry. Traditional statistical techniques, in conjunction with ethical
guidelines, make it difficult to compare trajectories of children who did versus did not receive an
educational intervention. Recent studies have demonstrated that the design quality of a study is
correlated with the outcomes of the study; as the design quality of a study increases, the negative
effects of retention decrease (Allen, Chen, Willson, & Hughes, 2009; Lorence, 2006).
Propensity scores, a relatively new statistical technique, allow researchers to compare
groups of children with different experiences in a manner that closely mimics a randomized,
controlled study. For example, Im et al (2013) compared the academic and behavioral
trajectories of retained versus promoted students using propensity scores and determined that in
the middle school years, the academic and behavioral trajectories of retained students were the
same as the academic and behavioral trajectories of their promoted peers. Wu, West, and Hughes
(2008) used propensity scores to analyze the difference in growth trajectories of first grade
students who were promoted versus retained and found that the effect of retention differed based
on several moderator and outcome variables. Analyzing the data used for this study using
propensity scores would allow each student who attended DK to be matched to a similar student
who did not attend DK and may yield more causal inferences between the literacy and socialemotional trajectories of children in the two groups.
Limitations
There are several limits to the internal validity of this study. Although educators who
administer the kindergarten screener at schools across the district have several years of
experience working with children and are very familiar with the instrument and use it year after

137

year, the district does not have a standardized training or scoring system in place for the
kindergarten screener. Moreover, the kindergarten screener is not a standardized measure of
school readiness. Despite these drawbacks, given the utility of the kindergarten screener in
predicting later literacy and social-emotional outcomes, it would have been useful to have
measured the school readiness skills of children who attended DK prior to the start of the
kindergarten year to better quantify influence of DK programming on school readiness skills.
In addition, the dependent variables of this study (MEAP scores and DIBELS scores) are
not ideal measures of academic achievement. The measures lack the reliability and validity of
other standardized measures such as the Wechsler Individual Achievement Test – Third Edition
or the Iowa Test of Basic Skills. Despite this limitation, the outcome measures used in this study
are influential in high stakes decisions such as a child’s eligibility for special education services
as a student with a specific learning– making these dependent variables appropriate measures to
use for this particular study.
The internal validity of this study is also threatened by the lack of a standardized DK
curriculum across schools and the subsequent instruction that children received after DK. The
longitudinal nature of this study prohibits the analysis of the classroom level variable due to the
exponential number of classroom combinations over such a long period of time. However, the
two level structure of the methodology used in this study is typical of longitudinal educational
studies (Peugh, 2012); it is expected that students will have different teachers over time, making
it very difficult to control for teacher effects (S. Konstantopoulos, personal communication,
April 16, 2013).
There are also several limits to the external validity of this study. The suburban
population used for this study has a low percentage of minority students, and many of the

138

minority students who attend school in this district attend the district through Michigan’s school
of choice program. Consequently, they did not meet the inclusion criteria of the study because
many of them had attended school in another school district or missed the kindergarten screening
date because they had not been selected at that time to attend school in the district. This means
that only students who presented with substantial stability in school attendance were included
within this study. The school is also part of a small group of schools in the state that is known for
academic excellence. This label suggests that students receive excellent instruction in each grade
level, which may diminish the effects of an early intervention such as DK compared to school
districts that are not recognized for academic excellence. It is difficult to generalize the results of
this particular study to samples of children who are at greater risk.
Regardless of school readiness skills or subsequent academic achievement scores, all
students in this sample were part of non-mobile families who remained in the same school
district. This is a protective factor that all students in the sample share and family stability may
have a positive effect on later academic outcomes. Moreover, children attend DK for a variety of
reasons such as low school readiness skills in academic and/or social areas, a late birthday, or a
small physical stature. Some children attend DK due to parent request, while others attend due to
the suggestion of educators and other professionals. Each DK student brings a unique set of
strengths and skills to the classroom and each student has different needs. It is difficult to isolate
the ability of the experiences in a DK classroom to meet those individual needs and set the stage
for later academic success.

139

APPENDICES

140

Appendix A – Kindergarten Screener

141

Appendix B – Kindergarten Screener Rubrics
Early Literacy Skills Rubric
Concepts of Print (Hand book to child upside down/backwards)
NELP Domain: Concepts of Print/Print Knowledge
+
Show me the title or name of this book
+
Find a page that you like
+
Show me the top of the page
+
Show me the bottom of the page
+
Tell me what’s happening on this page (choose one)
+
Show me where the words are in the book
+
If you were going to read these words, where would you start?
2
1
0

5 or more +
2–4+
0 – 1+

Comprehension (Student responses recorded)
What is this story about?
Who gave Sam the chair?
Why do you think Sam was happy to get the chair?
2
1
0

2 or more +
1+
0 answered correctly

Expressive/Receptive Language
NELP Domain: Oral Language
+
Why shouldn’t you play in the street?
+
What do doctors do?
+
Why do you go to the grocery store?
+
Why do you have a car?
+
What kind of clothes do you wear in the winter?
+
What do you do with money?
2
1
0

All answered correctly
All but one question answered correctly
Two or more questions answered incorrectly

142

Speech Language Concerns
NELP Domain: Oral Language
+
Receptive
+
Expressive
+
Articulation
2
1
0

All 3 +
1 area noted as a concern
2 or more areas noted as a concern

Tray Comments (Number, Color, etc.)
NELP Domain: RAN of Digits and Colors (Highly Correlated)
2
No concerns noted
(identified all digits and numbers correctly; able to categorize
objects)
1
Some concerns noted
(identified 3 or more digits or numbers, but unable to identify all
numbers accurately; categorized objects with some support)
0
Serious concerns noted (named 2, 1, or 0 digits or numbers; unable to categorize objects
with support)
Fine Motor (Draw a picture, sign name)
NELP Domain: Writing One’s Name
2
1
0

Able to write full name without prompting or difficulty (common reversals
are counted as correct; name is spelled correctly; shortened names are counted as correct
[e.g.,“Sam” for “Samuel”])
Able to write some letters of one’s name, but not all
Able to write one or zero letters of name

Overall Comments (located on front of kindergarten screener)
2
No early literacy concerns noted
1
Some early literacy concerns noted (References to a lack of some academic readiness
skills, but open to placement in DK or kindergarten)
0
Serious early literacy concerns noted (Reference to overall lack of academic readiness
skills, inability to identify any letters, inability to write name, inability to categorize
objects, or a reference to a combination of these; reference to an overall struggle in
kindergarten)
Score Range: 0 - 14

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Social-emotional Skills Rubric
Book-Story Reading-Listening Behavior
+
+
+

-

Eyes on book?
Restrain impulsive behavior?
Physical?

2
1
0

All “+”
2 – 3 “+”
0 or 1 “+” (Additional notes referencing child’s inability to pay attention, focus, or sit
still during the story)

Social Play (Home center, blocks, playdoh)
1
0

No negative social-emotional comments noted
Negative social-emotional comments noted (reference to playing alone, parallel
play, not interacting with other children, refusal to share with other children, or
negative interactions with other children)

Gross Motor (Activities/bean bag song)
1
0

No negative social-emotional comments noted
Negative social-emotional comments noted (child did not participate in activity,
child reluctant to join the circle with other children, refusal to follow song
directions, did not respond to teacher’s redirection)

Overall Social-emotional Comments (noted on the screening cover page)
2
1
0

No social-emotional concerns noted
Some social-emotional concerns noted
(Reference to being shy, initial difficulty separating from caregiver, mild attention
difficulties that did not interfere with overall performance)
Serious social-emotional concerns noted
(Reference to strongly recommending DK to parents, needing the “gift of time,”
attention difficulties that interfered with performance, or overall immaturity;
difficulty separating from caregiver that remained throughout screening process;
lack of interaction with other children; need for constant prompting, reassurance,
or redirection from teacher)

Score Range: 0 - 6

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Appendix C
Information Obtained from CA-60 Files
Front of CA-60 File
School History (Exclude child if child attended another district)
Child Name
Month and Year of birth
Gender
CA-60 Insert
Grade Level History
Grade attended, year attended, teacher name
MEAP Scores (affixed to back of insert)
Academic Achievement
DIBELS Scores
End of Year Report Card Scores
Additional Educational Information
Special Education Eligibility Documentation
Response to Intervention Documentation
Kindergarten Screening Informational Sheet
Age of Mother at birth of first child (calculated in combination with birth certificate)
Preschool Attendance
Kindergarten Screener
School Readiness Variables

145

Appendix D
End of Year Developmental Kindergarten Progress Report
ATTITUDES AND PRACTICES THAT AFFECT LEARNING
EXHIBITING SELF-CONTROL
SHOWING ACTIVE INVOLVMENT IN THE LEARNING PROCESS
SHOWING RESPECT FOR ADULTS AND CHILDREN
FOLLOWING DIRECTIONS
WORKING COOPERATIVELY
ORGANIZING SELF, MATERIALS, AND BELONGINGS
USING TIME WISELY
USING GOOD JUDGEMENT IN ASKING FOR HELP
DOING PERSONAL BEST ON CLASSROOM WORK
PHYSICAL DEVELOPMENT
PERFORMS SELF DRESSING TASKS
DEMONSTRATES SMALL MUSCLE CONTROL (CRAYONS, PENCILS, SCISSORS)
LITERACY
LISTENS ATTENTIVELY TO STORIES (FICTION/NON-FICTION)
SPEAKS IN SENTENCES USING AGE APPROPRIATE LANGUAGE
PARTICIPATES IN LANGUAGE ACTIVITIES
DEMONSTRATES CONCEPTS ABOUT BOOK (COVER, TITTE, FRONT TO BACK,
TOP AND BOTTOM)
RECOGNIZES RHYMES
RECOGNIZES FIRST NAME
WRITES FIRST NAME
IDENTIFIES LETTERS IN FIRST NAME IN RANDOM ORDER
INCREASING RECOGNITION O FUPPER CASE LETTER NAMES
MATH DEVELOPMENT
COUNT FORWARD 0 – 10
COUNTS FORWARD 0 – 20
USES 1 TO 1 CORRESPONDENCE TO 10
NAMES GEOMETRIC SHAPES (CIRCLE, SQUARE, TRIANGLE)
NAMES GEOMETRIC SHAPES (OVAL, RECTANGLE)
NAMES GEOMETRIC SHAPES (STAR, HEART, DIAMOND)
SORTS 4 OBJECTS BY SIZE
EXTENDS A TWO PART PATTERN
CREATES A TWO PART PATTERN
SORTS OBJECTS BY COLOR
SORTS OBJECTS BY SHAPE
RECOGNIZES COINS: PENNY
RECOGNIZES COINS: NICKEL
RECOGNIZES COINS: DIME

146

Appendix E
Social-emotional Measures from Kindergarten through Fourth Grade Report Cards
EXHIBITING SELF-CONTROL
SHOWING ACTIVE INVOLVEMENT IN THE LEARNING
PROCESS
SHOW RESPECT FOR ADULTS AND CHILDREN
FOLLOWING DIRECTIONS
WORKING COOPERATIVELY
ORGANIZING SELF, MATERIAL, AND BELONGINGS
USING TIME WISELY
USING GOOD JUDGEMENT IN ASKING FOR HELP
DOING PERSONAL BEST ON CLASSROOM WORK
Social-emotional Skills Rubric (for each statement)
3: Excellent
2: Acceptable
1: Not acceptable/Needs Improvement

147

Appendix F
Descriptive Statistics for Level 2 Factors
Table 21
Second Grade Descriptive Statistics
N
Mean
SD
Minimum
Level 2
DK Attendanceb
201
0.30
Maleb
201
0.49
a
Age at K Entry
201
0
1
FRPLb
201
0.11
Special Educationb
201
0.06
Attended Preschoolb
201
0.51
a
Continuous variables converted to z scores
b
Dichotomous variables where mean indicates proportion of participants

Table 22
Third Grade Descriptive Statistics
N
Mean
SD
Minimum
Level 2
DK Attendanceb
194
0.31
Maleb
194
0.50
Age at K Entrya
194
0
1
b
FRPL
194
0.06
Special Educationb
194
0.03
b
Attended Preschool
194
0.88
a
Continuous variables converted to z scores
b
Dichotomous variables where mean indicates proportion of participants

Table 23
Fourth Grade Descriptive Statistics
N
Mean
SD
Minimum
Level 2
DK Attendanceb
131
0.31
b
Male
131
0.49
Age at K Entrya
131
0
1
b
FRPL
131
0.06
Special Educationb
131
0.03
b
Attended Preschool
131
0.88
a
Continuous variables converted to z scores
b
Dichotomous variables where mean indicates proportion of participants

148

Maximum

Maximum

Maximum

Table 24
Fifth Grade Descriptive Statistics
N
Mean
SD
Minimum
Level 2 predictors
DK Attendanceb
154
0.37
b
Male
154
0.45
Age at K Entrya
154
0
1
b
FRPL
154
0.04
Special Educationb
154
0.04
b
Attended Preschool
154
0.81
a
Continuous variables converted to z scores
b
Dichotomous variables where mean indicates proportion of participants

149

Maximum

BIBLIOGRAPHY

150

BIBLIOGRAPHY

Adams, M. J. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA:
MIT Press.
Aikens, N., Kopack, A. K., Tarullo, L., & West, J. (2013). Getting ready for kindergarten:
Children’s progress during Head Start. FACES 2009 Report. OPRE Report 2013-21a.
Washington, DC: Office of Planning, Research, and Evaluation, Administration for
Children and Families, U.S. Department of Health and Human Services. Retrieved from
http://www.acf.hhs.gov/sites/default/files/opre/faces_2009_child_outcomes_brief_final.p
df
Allen, C., Chen, Q., Willson, V. & Hughes, J. (2009). Quality of research design moderates
effects of grade retention on achievement: A meta-analytic, multilevel analysis.
Educational Evaluation and Policy Analysis, 31, 480-499.
doi:10.3102/0162373709352239
Alloway, T. P., Gathercole, S. E., & Pickering, S. J. (2006). Verbal and visiospatial short-term
and working memory in children: Are they separable? Child Development, 77, 16981716.
Anthony, J. L., & Lonigan, C. J. (2004). The nature of phonological awareness: Converging
evidence from four studies of preschool and early grade school children. Journal of
Educational Psychology, 96, 43-55. doi: 10.1037/0022-0663.96.1.43
Anthony, J. L. & Francis, D. J. (2005). Development of phonological awareness. Current
Directions in Psychological Science, 14, 255-259. doi: 10.1111/j.09637214.2005.00376.x
Aram, D. & Levin, I. (2001). Mother-child joint writing in low SES: Sociocultural factors,
maternal mediation, and emergent literacy. Cognitive Development, 16, 831-852.
Ardoin, S. P., Christ, T. J., Morena, L. S., Cormier, D. C., & Klingbeil, D. A. (2013). A
systematic review and summarization of the recommendations and research surrounding
curriculum based measurement of oral reading fluency (CBM-R) decision rules. Journal
of School Psychology, 51.
Ardoin, S. P., Witt, J. C., Suldo, S. M., Connell, J. E., Koenig, J. L., Resetar, J. L., … &
Williams, K. L. (2004). Examining the incremental benefits of administering a maze and
three versus one curriculum-based measurement reading probes when conducting
universal screening. School Psychology Review, 33, 218-233.
Arnold, D. H., Kupersmidt, J. B., Voegler-Lee, M. E., & Nastassja, M. A. (2012). The
151

association between preschool children's social functioning and their academic skills.
Early Childhood Research Quarterly, 27, 376-386. doi:10.1016/j.ecresq.2011.12.009
Badian, N. A. (2001). Phonological and orthographic processing: Their roles in reading
prediction. Annals of Dyslexia, 51, 179-202.
Baker, S. K., Smolkowski, K., Katz, R., Fien, H., Seeley, J. R., Kame’enui, E. J., Beck, C. T.
(2008). Reading fluency as a predictor of reading proficiency in low-performing, highpoverty schools. School Psychology Review, 37, 18-37.
Baraldi, A. N., & Enders, C. K. (2010). An introduction to modern missing data analyses.
Journal of School Psychology, 48, 5 – 37. Doi: 10.1016/j.jsp.2009.10.001
Barnett, W. S. (1996). Lives in the balance: Benefit-cost analysis of the Perry Preschool
Program through age 27. Monographs of the High//Scope Educational Research
Foundation. Ypsilanti, MI: High/Scope Press.
Barnett, W. S. (2008). Preschool education and its lasting effects: Research and policy
implications. Boulder and Tempe: Education and Public Interest Center & Education
Policy Research Unit.
Bedard, K., & Dhuey, E. (2006). The persistence of early maturity: International evidence of
long-run age effects. Quarterly Journal of Economics, 121, 1437-1472.
doi: 10.1162/qjec.121.4.1437
Belsky, J., Fearon, R. M., & Bell, B. (2007). Parenting, attention, and externalizing problems:
Testing mediation longitudinally, repeatedly and reciprocally. Journal of Child
Psychology and Psychiatry, 48, 1233-1242. doi:10.1111/j.1469-7610.2007.01807.x
Bettinger, E. P. (2005). The effect of charter schools on charter students and public schools.
Economics of Education Review, 24, 133-147. doi: 10.1016/j.econedurev.2004.04.009
Bierman, K. L., Torres, M. M., Domitrovich, C. E., Welsh, J. A., & Gest, S. D. (2009).
Behavioral and cognitive readiness for school: Cross-domain associations for children
attending Head Start. Social Development, 18, 305-323. doi: 10.1111/j.14679507.2008.00490.x
Bisanz, J., Morrison, F. J., & Dunn, M. (1995). Effects of age and schooling on the acquisition of
elementary quantitative skills. Developmental Psychology, 31, 221-236.
doi:10.1037/0012-1649.31.2.221
Blair, C. & Razza, R. P. (2007). Relating effortful control, executive function, and false belief
understanding to emerging math and literacy ability in kindergarten. Child Development,
78, 647 – 663.
Blair, R. & Savage, R. (2006). Name writing but not environmental print recognition is related to
letter-sound knowledge and phonological awareness in pre-readers. Reading and Writing,
152

19, 991-1016.
Bornstein, M. H., Hahn, C., & Haynes, O. M. (2010). Social competence, externalizing
and internalizing behavioral adjustment from early childhood through early
adolescence: Developmental cascades. Development and Psychopathology, 22,
717 – 735.
Bornstein, M. H., Haynes, O. M., O’Reilly, A. W., & Painter, K. (1996). Solitary and
collaborative pretense play in early childhood: Sources of individual variation in the
development or representational competence. Child Development, 67, 2910 – 2929.
Bowey, J. A., Storey, T., & Ferguson, A. N. (2004). The association between continuous naming
speed and word reading skill in fourth to sixth grade children. Australian Journal of
Psychology, 56, 155-163.
Bowles, R. P., Pentimonti, J. M., Gerde, H. K., & Montroy, J. J. (2014). Item response analysis
of uppercase and lowercase letter name knowledge. Journal of Psychoeducational
Assessment, 32, 146 – 156. doi:10.1177/07342829134490266.
Brennan, L. M., Shaw, D. S., Dishion, T. J., & Wilson, M. (2012). Longitudinal predictors of
school-age academic achievement: Unique contributors of toddler-age aggression,
oppositionality, inattention, and hyperactivity. Journal of Abnormal Child Psychology,
40, 1289-1300.
Bronfrenbrenner, U. (2005). Making human beings human: Bioecological perspectives on human
development. Thousand Oaks, CA: Sage Publications.
Bryant, D., Clifford, R., Early, D., Pianta, R., However, C., Barbarin, O., & Burchinal, M.
(2002). Diversity and directions in state Pre-K programs. Chapel Hill: The University of
North Carolina, FPG Child Development Institute, NCEDL.
Buhs, E. S., Ladd, G. W. (2001). Peer rejection as an antecedent of young children’s school
adjustment: An examination of mediating processes. Developmental Psychology, 37, 550560.
Buhs, E. S., Ladd, G. W., & Herald, S. L. (2006). Peer exclusion and victimization: Processes
that mediate the relation between peer group rejection and children’s classroom
engagement. Journal of Educational Psychology, 98, 1-13.
Bumgarner, E. & Lin, M. (2014). Hispanic immigrant children’s early language acquisition:
The role of socioeconomic status and early childcare arrangement. Early Education and
Development, 25, 515-529.
Burchinal, M., Vandergrift, N., Pianta, R., & Mashburn, A. (2010). Threshold analysis of
association between child care quality and child outcomes for low-income children in
153

pre-kindergarten programs. Early Childhood Research Quarterly, 25, 166-176.
Burger, K. (2010). How does early childhood care and education affect cognitive development?
An international review of the effects of early interventions for children from different
social backgrounds. Early Childhood Research Quarterly, 25, 140 – 165.
Burke, M. D. & Hagan-Burke, S. (2007). Concurrent criterion-related validity of early literacy
indicators for middle of first grade. Assessment for Effective Intervention, 32, 66-77.
doi: 10.1177/15345084070320020401.
Cabell, S. Q., Justice, L. M., Piasta, S. B., Curenton, S. M., Wiggins, A., Turnbull, K. P., &
Petscher, Y. (2011). The impact of teacher responsivity education on preschoolers’
language and literacy skills. American Journal of Speech-Language Pathology, 20, 315.
California Department of Education. (2013). Transitional Kindergarten Frequently Asked
Questions. Retrieved from http://www.cde.ca.gov/ci/gs/em/kinderfaq.asp#E3
Camilli, G., Vargas, S., Ryan, S., & Barnett, W. (2010). Meta-analysis of the effects of early
education interventions on cognitive and social development. Teachers College Record,
112, 579-620.
Campbell, F. A. & Ramey, C. T. (1994). Effects of early intervention on intellectual and
academic achievement: A follow-up study of children from low-income families. Child
Development, 65, 684-698.
Catts, H. W., Fey, M. E., Tomblin, J. B., & Zhang, X. (2002). A longitudinal investigation of
reading outcomes in children with language impairment. Journal of Speech, Language,
and Hearing Research, 45, 1142-1157.
Catts, H. W., Petscher, Y., Schatschneider, C., Bridges, M. S., & Mendoza, K. (2009). Floor
effects associated with universal screening and their impact on the early identification of
reading disabilities. Journal of Learning Disabilities, 42, 163-176.
Cascio, E. (2008, August). How and why does age at kindergarten entry matter? Federal Reserve
Bank of San Francisco Economic Letter. Retrieved from
http://www.frbsf.org/publications/economics/letter/2008/el200808-24.pdf
Cascio, E., & Shanzenbach, D. W. (2007, December). First in the class? Age and education
production function (Working Paper No. 13663). National Bureau of Economic
Research. Retrieved from http://www.nber.org/papers/w13663
Center for Educational Performance and Information. (2013). Free and reduced lunch counts.
Retrieved from http://www.michigan.gov/cepi/0,1607,7-113-21423_30451_36965--,00.html.
Chall, J.S. (1967). Learning to read: The great debate; An inquiry into the world and ideology of
old and new methods of teaching children to read, 1910-1965. New York, NY: McGraw154

Hill.
Christ, T. J., Zopluoglu, C., Monaghen, B., Pike-Balow, A., & Van Norman, E. R. (2013).
Curriculum-based measurement of oral reading: Multi-study evaluation of schedule,
duration, and dataset quality on progress monitoring outcomes. Journal of School
Psychology, 51.
Clay, M. M. (2000). Concepts about print: What children have learned about the way we print
language? Portsmouth, NH: Reed Publishing.
Clifford, R. M., Barbarin, O., Florence, C., Early, D., Bryant, D., Howes, C….Pianta, R. (2005).
What is pre-kindergarten? Characteristics of public pre-kindergarten programs.
Developmental Science, 9, 126-143.
Coldren, J. T. (2013). Cognitive control predicts academic achievement in kindergarten children.
Mind, Brain, and Education, 7, 40 – 48.
Collaborative for Social, Emotional, and Academic Learning (CASEL). (2013). www.casel.org
Cook, R. E., Klein, M. D., Tessier, A., & Daley, S. E. (2011). Adapting early childhood
curricula for children in inclusive settings (8th ed.). Boston, MA: Pearson.
Datar, A. (2006). Does delaying kindergarten entrance give children a head start? Economics of
Education Review, 25, 43-62. doi:10.1016/j.econedurev.2004.10.004
Deming, D., & Dynarski, S. (2008). The lengthening of childhood. Journal of Economic
Perspectives, 22, 71-92. doi:10.1257/jep.22.3.71
Denham, S. (2010). Social-emotional competence as support for school readiness: What is it and
how do we assess it? Early Education and Development, 17, 57-89.
doi:10.1207/s15566935eed1701_4
Diamond, K. E., Gerde, H. K., & Powell, D. R. (2008). Development in early literacy skills
during the pre-kindergarten year in Head Start: Relations between growth in children’s
writing and understanding of letters. Early Childhood Research Quarterly, 23, 467-478.
Deno, S. L., Mirkin, P., & Chiang, B. (1982). Identifying valid measures of reading. Exceptional
Children, 49, 36-45.
Dhuey, E., & Lipscomb, S. (2010). Disabled or young? Relative age and special education
diagnoses in schools. Economics of Education Review, 29, 857-872.
doi:10.1016/j.econedurev.2010.03.006
Dice, J. L., & Schwanenflugel, P. (2012). A structural model of the effects of preschool attention
on kindergarten literacy. Reading and Writing, 25, 2205-2222.

155

Dizikes, C. (2011, March 31). Parents bothered by age maximum in Chicago schools. Chicago
Tribune. Retrieved from http://www.chicagotribune.com/news/education/ct=metkindergarten-cutoff-20110331,0,5314311.story
Domaleski, C. S. & Oshima, T. C. (2006). Academic performance gap between summer-birthday
and fall-birthday children in grades K-8. Journal of Educational Research, 4, 212-217.
doi:10.3200/JOER.99.4.212-217
Domitrovich, C. E., Morgan, N. R., Moore, J. E., Rhoades, B. L., Shah, H. K., Jacobson, L., &
Greenberg, M. T. (2013). One versus two years: Does length of exposure to an
enhanced preschool program impact the academic functioning of disadvantaged children
in kindergarten? Early Childhood Research Quarterly, 28, 704-713.
Drouin, M., & Harmon, J. (2009). Name writing and letter knowledge in preschoolers:
Incongruities in skills and the usefulness of name writing as a developmental indicator.
Early Childhood Research Quarterly, 24, 263-270.
Drouin, M., Horner, S. L., Sondergeld, T. A. (2012). Alphabet knowledge in preschool: A Rasch
model analysis. Early Childhood Research Quarterly, 27, 543-554.
doi:10.1016/j.ecresq.2011.12.008
Duckworth, A. L. & Seligman, M. E. (2006). Self-discipline gives girls the edge: Gender in selfdiscipline, grades, and achievement test scores. Journal of Educational Psychology, 98,
198 – 208. doi: 10.1037/0022-0663.98.1.198
Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A., Klebanov, P.,…Japel, C.
(2006). School readiness and later achievement. Developmental Psychopathology, 43,
1428-1466.
Early, D. M., Iruka, I. U., Ritchie, S., Barbarin, O. A., Winn, D. C., Crawford, G. M…Pianta, R.
C. (2010). How do pre-kindergarteners spend their time? Gender, ethnicity, and income
as predictors of experiences in pre-kindergarten classrooms. Early Childhood Research
Ehri, L. C. (1995). Phases of development in learning to read by sight. Journal of Research in
Reading, 18, 116-125.
Elder, T. & Lobotsky, D. (2009). Kindergarten entrance age and children's achievement: Impacts
of state policies, family background, and peers. Journal of Human Resources, 44, 641683.
Field, A. (2009). Discovering Statistics using SPSS. Thousand Oaks, CA: Sage Publications.
Foy, J. G. & Mann, V. A. (2013). Executive functioning and early reading skills. Reading and
Writing, 26, 453-472.
Francis, D. J., Shaywitz, S. E., Stuebing, K. K., Shaywitz, B. A., & Fletcher, J. M. (1996).
Developmental lag versus deficit models of reading disability: A longitudinal, individual
156

growth curves analysis. Journal of Educational Psychology, 88, 3 - 17.
Frede, E., Jung, K., Barnett, W. S., & Figueras, A. (2009). The APPLES blossom: Abbott
preschool program longitudinal effects study (APPLES). Report to the New Jersey
Department of Education. New Bruswick, NJ: National Institute for Early Education
Research.
Froyen, L. C., Skibbe, L. E., Bowles, R. P., Blow, A. J., & Gerde, H. K. (2013). Marital
satisfaction, family emotional expressiveness, home learning environments, and
children’s emergent literacy. Journal of Marriage and Family, 75, 42-55.
doi:10.1111/j.1741-3737.2012.01035.x
Fuchs, L. S., Fuchs, D., Maxwell, L. (1988). The validity of informal reading comprehension
measures. Remedial and Special Education, 9, 20 – 28.
Galinsky, E. (2006). The economic benefits of high-quality early childhood programs: What
makes the difference? Prepared for the Committee for Economic Development.
www.CED.org
Garces, E., Thomas, D., & Currie, J. (2000). Longer term effects of Head Start (Working Paper
Series 00 – 20). RAND Corporation.
Georgiou, G. K., Parilla, R., & Kirby, J. (2006). Rapid naming speed components and early
reading acquisition. Scientific Studies of Reading, 10, 199 – 220.
Gerde, H. K., Skibbe, L. E., Bowles, R. P., & Martoccio, T. L. (2012). Child and home
predictors of children’s name writing. Child Development Research, 2012, 1-12.
doi:10.1155/2012/748532
Gessell, A. (1929) Maturation and infant behavior pattern. Psychological Review, 36, 307-319.
Good, R. H., Kaminski, R. A., Shinn, M., Bratten, J., Shinn, M., Laimon, L. . . & Flindt, N.
(2004). Technical adequacy and decision making utility of DIBELS (Technical Report
No. 7). Eugene, OR: University of Oregon.
Good, R. H. & Kaminski, R. A. (2011). DIBELS next assessment manual. Eugene, OR: Dynamic
Measurement Group.
Goodman, A. & Sianesi, B. (2005). Early education and children’s outcomes: How long do the
impacts last? London: Institute for Fiscal Studies, University of London.
Goodman, Y. M. (1986). Children coming to know literacy. In W.H. Teale & E. Sulzby (Eds.)
Emergent literacy: Writing and Reading (pp.1-14). Norwood, NJ: Ablex.
Gormley, W., Gayer, T., Phillips, D., & Dawson, B. (2005). The effects of universal pre-K on
cognitive development. Developmental Psychopathology, 41, 872-884.
157

doi:10.1037/0012-1649.41.6.872
Graham, J. W. (2009). Missing data analysis: Making it work in the real world. Annual Review of
Psychology, 549-576.
Graue, E. (2010). The answer is readiness - now what is the question? Early Education and
Development, 17, 43-56. doi:10.1207/s15566935eed1701_3
Guerra, N. G., Graham, S., & Tolan, P. H. (2011). A meta-analysis of school-based universal
interventions. Child Development, 82, 405-432. doi: 10.1111/j.1467-8624.2010.01564.x
Hammill, D. D., Mather, N., Allen, E. A., & Roberts, R. (2002). Using semantics, grammar,
phonology, and rapid naming tasks to predict word identification. Journal of Learning
Disabilities, 35, 121-136. doi:10.1177/002221940203500204
Hamre, B. K. & Pianta, R. C. (2001). Early teacher-child relationships and the trajectory of
children’s school outcomes through eighth grade. Child Development, 72, 625-638.
Hair, E., Halle, T., Terry-Humen, E., Lavelle, B., & Calkins, J. (2006). Children's school
readiness in the ECLS-K: Predictions to academic, health, and social outcomes in first
grade. Early Childhood Research Quarterly, 4, 431-454.
Hatfield, B., Lower, J. K., Cassidy, D. J., Faldowski, R. A. (2014). Inequities in access to quality
early childcare and education: Associations with funding and community context. Early
Childhood Research Quarterly, http://dx.doi.org/10.1016/j.ecresq.2014.01.001
Hawaii State Department of Education. (2013). Junior Kindergarten/Kindergarten. Retrieved
from http://doe.k12.hi.us/kindergarten/index.htm
Hart, T. M., Berninger, V. W., & Abbott, R. D. (1997). Comparison of teaching single or
multiple orthographic-phonological connections for word recognition and spelling:
Implications for instructional consultation. School Psychology Review, 26, 279-297.
Head Start. (2013). Final fiscal year 2013 funding level. Retrieved from
http://eclkc.ohs.acf.hhs.gov/hslc/standards/PIs/2013/resour_pri_003_042613.html
Hecht, S. A., Burgess, S. R., Torgeson, J. K., Wagner, R. K., & Rashotte, C. A. (2000).
Explaining social class differences in growth of reading skills from beginning
kindergarten through fourth grade: The role of phonological awareness, rate of access,
and print knowledge. Reading and Writing: An Interdisciplinary Journal, 12, 99-127.
Heckman, J. J. (2000). Policies to foster human capital. Research in Economics, 54, 3 – 56.
Heckman, J. J., Stixrud, J., & Uruza, S. (2006). The effects of cognitive and noncognitive
abilities on labor market outcomes and social behavior. Journal of Labor Economics, 24,
411-482.
158

Hernandez, D. J., Denton, N. A., & Macartney, S. E. (2007). Demographic Trends and the
Transition Years. In Pianta, R. C., Cox, M. J., & Snow, K. L.
(Eds.), School readiness & the transition to kindergarten in the era of accountability (217
– 282). Baltimore, MD: Brookes Publishing Company.
Hogden, E. (2007). Early childhood education and young adult competencies at age 16. New
Zealand: Ministry of Education and New Zealand Council for Educational Research.
Holmes, C. T. (1989). Grade-level retention effects: A meta-analysis of research studies. In L. A.
Shepard & M. L. Smith (Eds.), Flunking grades: Research and policies on retention
(pp.16-33). London: The Falmer Press.
Holmes, C. T. & Matthews, K. M. (1984). Effect size estimation in meta-analysis. Journal of
Experimental Education, 52,106-109.
Honig, B., Diamond, L., & Gurlohn, L. (Eds.) (2008). Teaching reading sourcebook, second
edition. Berkeley, CA: Consortium on Reading Excellence, Inc.
Hong, G. & Raudenbush, S. (2006). Evaluation kindergarten retention policy. Journal of the
American Statistical Association, 101, 901-910. doi:10.1198/016214506000000447
Hong, G. & Yu, B. (2007). Early-grade retention and children’s reading and math learning in
elementary years. Educational Evaluation and Policy Analysis, 29, 239-261.
doi:10.3102/0162373707309073
Hothersall, D. (2004). History of Psychology (4th ed.). Columbus, OH: McGraw-Hill Companies.
Howes, C., Burchinal, M., Pianta, R., Bryant, D., Early, D., Clifford, R., & Barbarin, O. (2008).
Ready to learn? Children's pre-academic achievement in Pre-K programs. Early
Childhood Research Quarterly, 23, 27-50.
Huang, F. & Invernizzi, M. (2013). Birthday effects in preschool attendance. Early Childhood
Research Quarterly, 28, 11-23. doi:10.1016/j.ecresq.2012.03.002
Huey-Ling, L., Lawrence, F. R., & Gorrell, J. (2003). Kindergarten teachers' views of children's
readiness for school. Early Childhood Research Quarterly, 18, 225237. doi:10.1016/S0885-2006(03)00028-0
Im, M. H., Hughes, J. N., Kwok, O., Puckett, S., Cerda, C. A. (2013). Effect of retention in
elementary grades on transition to middle school. Journal of School Psychology, 51, 349365. doi:10.1016/j.jsp.2013.01.004
Jackson, L. A., Von Eye, A., Biocca, F. A., Barbatsis, G., Zhao, Y., & Fitzgerald, H. E. (2006).
Does home internet use influence the academic performance of low-income children?
Developmental Psychology, 42, 429.
159

Jimerson, S., Anderson, G., & Whipple, A. (2002). Winning the battle and losing the war:
Examining the relation between grade retention and dropping out of school. Psychology
in Schools, 39, 441-457. doi:10.1002/pits.10046
Jimerson, S., Pletcher, S., Graydon, K., Schnurr, B., Nickerson, A., & Kundert, D.
(2006). Beyond grade retention and social promotion: Promoting the social
and academic competence of students. Psychology in the Schools, 23, 85-97.
doi:10.1002/pits.20132
Justice, L., Bowles, R., & Skibbe, L. (2006). Preschool attainment of print-concept knowledge:
A study of typical and at-risk 3 to 5 year old children using item response theory.
Language, Speech, and Hearing Services in Schools, 37, 224-235.
Justice, L. M., Pence, K., Bowles, R. B., & Wiggins, A. (2006). An investigation of four
hypotheses concerning the order by which 4-year-old children learn the alphabet letters.
Early Childhood Research Quarterly, 21, 374-389.
Kaminski, R., Cummings, K. D., Powell-Smith, K. A., & Good, R. H. (2008). Best practices in
using dynamic indicators of basic early literacy skills for formative assessment and
evaluation. In A. Thomas & P. Harrison (Eds.), Best Practices in School Psychology (4th
ed.) (1181-1204). Bethesda, MD: National Association of School Psychologists.
Kaminski, R. A., & Cummings, K. D. (2007). Assessment for learning: Using general outcomes
measures. Retrieved from ciconline.org/threshold.
Karweit, N. L. & Wasik, B. A. (1992). A review of the effects of extra-year kindergarten
programs and transitional first grades.
Katzir, T., Youngsuk, K., Wolf, M., O'Brien, B., Kennedy, B., Lovett, M., & Morris, R. (2006).
Reading fluency: The whole is more than the sum of its parts. The Annals of Dyslexia, 56,
51-82.
Kilburn, R. M. & Karoly, L. A. (2008). The economics of early childhood policy: What the
dismal science has to say about investing in children. RAND CORPORATION
http:www.rand.org/pubs/occasional_papers/OP227
Kirby, J. R., Parilla, R. K., Pfeiffer, S. L. (2003). Naming speed and phonological awareness as
predictors of reading development. Journal of Educational Psychology, 95, 453-464.
Kirk, S. A. (1958). Early Education of the Mentally Retarded. Urbana: University of Illinois
Press.
Kisker, E. E., Paulsell, D., Love, J. M., & Raikes, H. (2002). Pathways to quality and full
implementation in Early Head Start programs (No. 3424). Mathematica Policy Research.

160

Klein, L. G., & J. Knitzer. (2006). Effective preschool curricula and teaching strategies.
Pathways to Early School Success, Issue Brief No.2. New York: Columbia University,
National Center for Children Living in Poverty.
Kutner, M., Greenberg, E., Jin, Y., & Paulsen, C. (2006). The Health Literacy of America's
Adults: Results from the 2003 National Assessment of Adult Literacy (NCES 2006-483).
U.S. Department of Education. Washington, DC: National Center for Education
Statistics.
La Paro, K. M. & Pianta, R. C. (2000). Predicting children’s competence in the early school
years: A meta-analytic review. Review of Educational Research, 70, 443-484.
Lee, V. E., & Burkam, D. T. (2002). Inequality at the starting gate: Social background
differences in achievement as children begin school. New York: Economics Policy
Institute.
Lengua, L. J. (2002). The contribution of emotionality and self-regulation to the understanding
of children’s responses to multiple risk. Child Development, 73, 144-161.
Levin, I., Both-De Vries, A., Aram, D., & Bus, A. (2006). Writing starts with own name writing:
From scribbling to conventional spelling in Israeli and Dutch children. Applied
Psycholinguistics, 26, 462-477. doi:10.1017.S0142716405050253
Levy, B. A., Gong, Z., Hessles, S., Evans, M. A., & Jared, D. (2006). Understanding print: Early
reading development and the contributions of home literacy experiences. Journal of
Experimental Child Psychology, 93, 63-93. doi:10.1016/j.jecp.2005.07.003
Lin, H. L, Lawrence, F. R., & Gorrell, J. (2003). Kindergarten teachers’ views of children’s
readiness for school. Early Childhood Research Quarterly, 18, 225-237.
doi:10.1016/S0885-2006(03)00028-0
Lincove, J., & Painter, G. (2006). Does the age that children start kindergarten matter? Evidence
of long-term educational and social outcomes. Educational Evaluation and Policy
Analysis, 28, 153-179. doi:10.3102/01623737028002153
Lindsey, E. W. (2002). Preschool children’s friendships and peer acceptance: Links to social
competence. Child Study Journal, 32, 145-156.
LoCasale-Crouch, J., Konold, T., Pianta, R., Howes, C., Burchinal, M., Bryant, D,…Barbarin, O.
(2007). Observed classroom quality profiles in state-funded Pre-K programs and
associations with teacher, program, and classroom characteristics. Early Childhood
Research Quarterly, 22, 3-17.
Lonigan, C. J., Burgess, A. R., & Anthony, J. L. (2000). Development of emergent literacy and
early reading skills in preschool children: Evidence from a latent variable longitudinal
study. Developmental Psychology, 36, 596-613.
161

Lovelace, S., & Stewart, S. R. (2007). Increasing print awareness in preschoolers using nonevocative print referencing. Language, Speech, and Hearing Services in Schools, 38, 16.
Magnuson, K., Ruhm, C., & Waldfogel, J. (2007). Does prekindergarten improve school
preparation and performance? Economics of Education Review, 26, 33-51.
doi:10.1016/j.econedurev.2005.09.008
Matthews, J. S., Ponitz, C. C., & Morrison, F. J. (2009). Early gender differences in selfregulation and academic achievement. Journal of Educational Psychology, 3, 689-704.
doi: 10.1037/a0014240
Martin, R. P., Foels, P., Clanton, G., & Moon, K. (2004). Season of birth is related to child
retention rates, achievement, and rate of diagnosis of specific LD. Journal of Learning
Disabilities, 37(4), 307-317.
Matson, S. C. & Haglund, K. A. (2000). Relationship between scholastic and health behaviors
and reading level in adolescent females. Clinical Pediatrics, 39, 275-280.
McCormick, C. E., & Mason, J. M. (1986). Intervention procedures for increasing preschool
children’s interest in and knowledge about reading. In W. H. Teal & E. Sulzby (Eds.),
Emergent literacy: Writing and reading (pp.90-115). Norwood, NJ: Ablex.
McNaughton, S. (1995). Patterns of emergent literacy: Processes of development and transition.
New York: Oxford University Press.
McWayne, C. M., Cheung, K., Wright, L. E., Green, L. E., Hahs-Vaughn, D. L. (2012). Patterns
of school readiness among head start children: Meaningful within-group variability
during the transition to kindergarten. Journal of Educational Psychology, 104, 862-878.
Meisels, S. J. (1992). Doing harm by doing good: Iatrogenic effects of early childhood
enrollment and promotion policies. Early Childhood Research Quarterly, 7, 155-174.
Merrell, K., Ervin, R., & Gimpel-Peacock, G. G. (2012). School Psychology for the 21st Century:
Foundations and Practices. New York: Guilford Press.
Michigan Department of Education. (2013a). How do I know if my child is ready for
kindergarten?: Parent guide #2. Retrieved from http://www.michigan.gov/mde/0,4615,7140-6530_6809-152726--00.html.
Michigan Department of Education. (2013b). Is my child required to attend kindergarten?:
Parent guide #1. Retrieved from http://www.michigan.gov/mde/0,4615,7-1406530_6809-152726--,00.html
Michigan Department of Education. (2013c). Will my child benefit from an extra year of
kindergarten?: Parent guide #24. Retrieved from
162

http://www.michigan.gov/mde/0,46809-152726--,00.ht
Michigan Department of Education. (2013d). Common core state academic standards.
Retrieved from http://mi.gov/med/0,4615,7-140-28753_64839_64848---,00.html
Michigan Department of Education. (2013e). Michigan Educational Assessment Program.
Retrieved from http://www.michigan.gov/mde/0,4615,7-140-22709_31168---,00.html
Michigan Department of Education. (2011). Michigan Educational Assessment Program
Technical Report (2010 – 2011). Retrieved from
http://www.michigan.gov/documents/mde/MEAP_20102011_Technical_Report_394693_7.pdf
Michigan State Board of Education. (2005). Early Childhood Standards of Quality for
Prekindergarten. Retrieved from http://www.michigan.gov/mde/0,1607,7-1406530_6809-103343--,00.html.
Miller, C. J., Miller, S. R., Bloom, J. S., Jones, L., Lindstrom, W., Craggs, J…Hynd, G. W.
(2006). Testing the double-deficit hypothesis in an adult sample. Annals of Dyslexia, 56,
83-102. doi:10.1007/s11881-006-0004-4
Muter, V., Hulme, C., Snowling, M. J., & Stevenson, J. (2004). Phonemes, rimes, vocabulary,
and grammatical skills as foundations of reading development: Evidence from a
longitudinal study. Developmental Psychology, 40, 665-681.
National Association of the Education of Young Children. (2009). Developmentally appropriate
practice in early childhood programs serving children from birth through age 8.
National Early Literacy Panel. (2002). Developing early literacy: Report of the early literacy
panel. Washington, DC: National Institute for Literacy. Retrieved from
http://lincs.ed.gov/earlychildhood/NELP/NELPreport.html
National Institute of Child Health and Human Development (NICHD). (2000). The NICHD study
of early child care and youth development: Findings for children up to age 4 ½ years.
Retrieved from http://www.nichd.nih.gov.
National Institute for Literacy (2009). Early Beginnings: Early Literacy Knowledge and
Instruction. Retrieved from
http://lincs.ed.gov/publications/pdf/NELPEarlyBeginnings09.pdf
National Reading Panel (US), National Institute of Child Health & Human Development (US).
(2000). Report of the national reading panel: Teaching children to read: An evidencebased assessment of the scientific research literature on reading and its implications for
reading instruction: Reports of the subgroups. National Institute of Child Health and
Human Development, National Institutes of Health.

163

Neidell, M. & Waldfogel, J. (2010). Cognitive and noncognitive peer effects in early education.
The Review of Economics and Statistics, 92, 562 – 576.
Neuenschwander, M. P., Vida, M., Garrett, J. L., Eccles, J. S. (2007). Parents’ expectations and
students’ achievement in two western nations. International Journal of Behavioral
Development, 31, 594-602.
Nevada Pre-Kindergarten Standards. (2010). Building a foundation for school readiness and
success in Pre K-12 and Beyond. Retrieved from http://www.nevadaregistry.org/officeof-early-care-and-education/pre-k-standards.html
New Mexico's Early Learning Outcomes. (2006). New Mexico Pre-K: Invest a Little, Get a Lot.
Retrieved from
http://www.ped.state.nm.us/earlyChildhood/dl08/preK/NM%20PreK%202006%20Early
%20Learning%20Outcomes-Full%20Version.pdf
Neuman, S. B. & Dickinson, D. K. (2011). Handbook of early literacy research. The Guilford
Press: New York, New York.
National Institute of Child Health and Development Early Child Care Research Network
(NICHD ECCRN). (2000). The relation of child care to cognitive and language
development. Child Development, 71, 958-978.
National Institute of Child Health and Development Early Childcare Research Network
(NICHD ECCRN). (2003). Does quality of child care affect child outcomes at age 4-½?
Developmental Psychology, 39, 451-469.
Nithart, C., Demont, E., Metz-Lutz, M. N., Majerus, S., Poncelet, M. & Leybaert, J. (2011).
Early contribution of phonological awareness and later influence of phonological
memory throughout reading acquisition. Journal of Research in Reading, 34, 346-363.
doi:10.1111/j.1467-9817.2009.01427.x.
Nunnally, J. C. (1978). Psychometric Theory (2nd ed.). New York: McGraw-Hill.
O’Connor, E. & McCartney, K. (2007). Examining teacher-child relationships and achievement
as part of an ecological model of development. American Educational Research Journal,
44, 340-369.
O’Donnell, K. (2008). Parents’ reports of the school readiness of young children from the
National Household Education Surveys Program of 2007 (NCES 2008-051). National
Center for Education Statistics, Institute of Education Sciences, U.S. Department of
Education. Washington, D.C.
Oklahoma State Department of Education. (2013). Early Childhood and Family Education.
Retrieved from http://ok.gov/sde/early-childhood-and-family-education#4%20yr

164

Office of Head Start. (2010). The Head Start child development early learning framework:
Promoting positive outcomes in early childhood programs serving children 3 – 5 years
old. Retrieved from http://eclkc.ohs.acf.hhs.gov/hslc/ttasystem/teaching/eecd/Assessment/Child%20Outcomes/HS_Revised_Child_Outcomes_Fr
amework%28rev-Sept2011%29.pdf
Office of Juvenile Justice and Delinquency Prevention. (2006). Juvenile offenders and victims:
2006 National report. Retrieved from http://www.ojjdp.gov/ojstatbb/nr2006/.
Palermo, F., Hanish, L. D., Martin, C. L., Fabes, R. A., & Reiser, M. (2007). Preschoolers’
academic readiness: What role does the teacher-child relationship play? Early Childhood
Research Quarterly, 22, 407-422.
Paris, S. G. (2005). Reinterpreting the development of reading skills. Reading Research
Quarterly, 40, 184-202. doi:10.1598/RRQ.40.2.3
Payton, J., Weissberg, R. P., Durlak, J. A., Dymnicki, A. B., Taylor, R. D., Schellinger, K. B., &
Pachan, M. (2008). The positive impact of social-emotional learning for kindergarten
to eighth-grade students: Findings from three scientific reviews. Collaborative for
Academic, Social, and Emotional Learning (CASEL). Retrieved from
http://casel.org/publications/positive-impact-of-social-and-emotional-learning-forkindergarten-to-eighth-grade-students-findings-from-three-scientific-reviews/
Peisner-Feinberg, E. S. & Schaaf, J. M. (2007). Evaluation of the North Carolina More at Four
Pre-kindergarten Program: Children’s Outcomes and Program Quality in the Fifth Year.
Chapel Hill, NC: FPG Child Development Institute.
Peugh, J. L. (2012). A practical guide to multilevel modeling. Journal of School Psychology, 48,
85-112. doi:10.1016/j/jsp.2009.09.002
Phillips, D. A., Gormley, W. T., & Lowenstein, A. E. (2009). Inside the pre-kindergarten door:
Classroom climate and instructional time allocation in Tulsa’s pre-K programs. Early
Childhood Research Quarterly, 24, 213-228.
Pianta, R. C. & Harbors, K. L. (1996). Observing mother and child behavior in a problemSolving situation at school entry: Relations with academic achievement. Journal of
School Psychology, 34, 307-322.
Pianta, R. & Kraft-Sayre, M. (2003). Successful transition to kindergarten: Your guide to
connecting children, families, and schools. Baltimore, MD: Paul Brookes Publishing
Company.
Pianta, R. C. (Ed.), Cox, M. J. (Ed.), & Snow, K. L. (2007). School readiness and the transition
to kindergarten in the era of accountability. Baltimore, MD: Paul H Brookes Publishing.
Pianta, R. C. & Stuhlman, M. W. (2004). Teacher-child relationships and children’s success in
The first years of school. School Psychology Review, 33, 444-458.
165

Promising Practices Network. (2012). Child-Parent Centers. Retrieved from
http://www.promisingpractices.net/program.asp?programid=98
Puranik, C., & Lonigan, C. (2012). Name-writing proficiency, not length of name is associated
with preschool children's emergent literacy skills. Early Childhood, 27, 284-294.
doi:10.1016/j.ecresq.2011.09.003
Puranik, C. S., Lonigan, C. J., & Kim, Y. S. (2011). Contributions of emergent literacy skills to
name writing, letter writing, and spelling in preschool children. Early Childhood
Research Quarterly, 26, 465-474.
Quirk, M., Nylund-Gibson, K., & Furlong, M. (2013). Exploring patterns of Latino/a children’s
school readiness at kindergarten entry and their relations with grade 2 achievement. Early
Childhood Research Quarterly, 28, 437-449.
Raforth, M., Buchenauer, E. L., Crissman, K. K., & Halko, J. L. (2004). School readiness:
Preparing children for kindergarten and beyond. National Association of School
Psychologist’s Position Statement. Retrieved from:
http://www.nasponline.org/resources/handouts/schoolreadiness.pdf
Raudenbush, S. W., Byrk, A. S., & Congdon, R. (2004). HLM 6 for Windows. [Computer
software]. Skokie, IL: Scientific Software International, Inc.
Raver, C. C. (2004). Emotional self-regulation in sociocultural and socioeconomic contexts.
Child Development, 75, 346-353.
Razza, R. A., Martin, A., & Brooks-Gunn, J. (2012). Journal of Applied Developmental
Psychology.
doi:http://org.proxy2.cl.msu.edu.proxy1.cl.msu.edu/10.1016/j.appdev.2012.07.005
Reschly, A. L. & Christenson, S. L. (2013). Grade retention: Historical perspectives and new
research. Journal of School Psychology, 51, 319-322. doi:10.1016.j.jsp.2013.05.002
Reynolds, A. J. (2000). The state of early intervention. In Success in Early Intervention: The
Chicago Child-Parent Centers (1 – 21). Lincoln, NE: University of Nebraska.
Reynolds, A. J. & Temple, J. A. (2008). Cost-effective early childhood development programs
from preschool to third grade. Annual Review of Clinical Psychology, 4, 109-139.
doi:10.1146/annurev.clinpsy.3.022806.091411
Rimm-Kaufman, S. E., Pianta, R., & Cox, M. (2000). Teachers' judgments of problems in the
transition to kindergarten. Early Childhood Research Quarterly, 15, 147-166.
Risely, T. R., Hart, B., & Bloom, L. (1995). Meaningful differences in the everyday experiences
of young American children. Brookes Publishing: Baltimore, MD.
166

Robertson, E. (2011). The effects of quarter of birth on academic outcomes at the elementary
school level. Economics of Education Review, 30, 300-311. doi:10.1016/j.econedurev.
2010.10.005
Rose, E. (2011). Prekindergarten in Oklahoma. In E. Zigler, W.S. Gilliam, W.S. Barnett (Eds.),
The Pre-K Debates: Current Controversies & Issues (188-190). Pacific Grove, CA:
Brookes Publishing.
Rumberger, R. W. & Palardy, G. J. (2005). Does segregation still matter? The impact of student
composition on academic achievement in high school. Teachers College Record, 107,
1999 – 2045.
Schafer, J. L & Graham, J. W. (2002). Missing data: Our view of the state of the art.
Psychological Methods, 7, 147-177.
Schatschneider, C., Wagner, R. K., & Crawford, E. C. (2008). The importance of measuring
growth in response to intervention models: Testing a core assumption. Learning and
Individual Differences, 18, 308-315.
Schechter, C. & Bye, B. (2007) Preliminary evidence for the impact of mixed-income preschools
on low-income children’s language growth. Early Childhood Research Quarterly, 22,
137-146.
Schickedanz, J. A. & Collins, M. F. (2013). So much more than the ABCs: The Early Phases of
Reading and Writing. Washington, D.C.: National Association for the Education of
Young Children.
Schweinhart, L. J. (2003). Benefits, costs, and explanations of the High Scope Perry Preschool
Program. Paper presented at the Meeting of the Society for Research in Child
Development. Tampa, Florida. Retrieved from
https://www.highscope.org/file/Research/PerryProject/Perry-SRCD_2003.pdf
Shinn, M. (Ed.). (1989). Curriculum-based measurement: Assessing special children. New York:
Guilford Press.
Shonkoff, J. P. & Phillips, D. A. (Eds.) (2000). From Neurons to Neighborhoods. Washington,
D.C.: National Academy Press.
Skibbe, L. E., Connor, C. M., Morris, F. J., & Jewkes, A. M. (2011). Schooling effects on
preschoolers’ self-regulation, early literacy, and language growth. Early Childhood
Research Quarterly, 26, 42-49. doi:10.1016/j.ecresq.2010.05.001
Skibbe, L. E., Phillips, B. M., Day, S. L., Brophy-Herb, H. E., & Connor, C. M. (2012).
Children's early literacy growth in relation to classmates' self-regulation. Journal of
Educational Psychology, 104, 541-553. doi:10.1016/j.ecresq.2010.05.001
167

Smith, S. L., Scott, K. A., Roberts, J., & Locke, J. L. (2008). Disabled readers' performance on
tasks of phonological processing, rapid naming, and letter knowledge before and after
kindergarten. Learning Disabilities Research & Practice, 23, 113-124.
doi:10.1111/j.1540-5826.2008.00269.x
Snow, K. (2010). Measuring school readiness: Conceptual and practical considerations. Early
Education and Development, 17, p. 7-41. doi:10.1207/s15566935eed1701_2
Snow, C. E., Burns, M. S., & Griffin, P. (1998). Preventing reading difficulties in young
children. Washington, DC: National Academy Press.
Stage, S. A. (2001). Program evaluation using hierarchical linear modeling with curriculumbased measurement reading probes. School Psychology Quarterly, 16, 91.
Stipek, D., & Byler, P. (2001). Academic achievement and social behaviors associated with age
of entry into kindergarten. Journal of Applied Developmental Psychology, 22, 175-189.
doi:10.1016/S0193-3973(01)00075-2
Storch, A. S., & Whitehurst, G. J. (2002). Oral language and code-related precursors to reading:
Evidence from a longitudinal structural model. Developmental Psychology, 38, 934-837.
Strommen, L. T. & Mates, B. F. (1997). What readers do: Young children’s ideas about the
nature of reading. The Reading Teacher, 51, 98 – 107.
Sylva, K., Melhuish, E., Sammons, P., Siraj-Blatchford, I., & Taggert, B. (2004). The final
report: Effective pre-school education. Technical paper 12. London: Institute of
Education, University of London.
Synder, Richard. (Producer). (2014, January 16) State of the State Address [Television
Broadcast]. Lansing, Michigan: WKAR Broadcasting Service.
Teal, W. H. & Sulzby, E. (1986). Emergent Literacy: Writing & Reading. Norwood, NJ: Ablex.
Tucker-Drob, E. (2012). Preschools reduce early academic-achievement gaps: A longitudinal
twin approach. Psychological Science, 23, 310 – 319.
United States Census Bureau. (2014). State and county quick facts. www.uscensus.gov.
United States Department of Education. (2013). Building the Legacy: IDEA 2004.
http://idea.ed.gov/explore/home
United States Department of Health and Human Services. (2010). Head Start impact study: Final
report. Washington, D.C: US Department of Health & Human Services., retrieved from
www.acf.hhs.gov/programs/opre/hs/impact_study
United States Department of Health and Human Services, Administration for Children and
168

Families, Office of Head Start (2010). The Head Start child development and early
learning framework: Promoting positive outcomes in early childhood programs serving
children 3 - 5 years old. Retrieved from http://eclkc.ohs.acf.hhs.gov/hslc/ttasystem/teaching/eecd/assessment/child%20outcomes/revised-child-outcomes.html.
University of Oregon, Center on Teaching and Learning (2012). 2012-2013 DIBELS Data
System Update Part I: DIBELS Next Composite Score (Technical Brief No. 1202).
Eugene, OR: University of Oregon.
University of Oregon DIBELS Data System. (2013). https://DIBELS.uoregon.edu/
Vallotton, C., & Ayoub, C. (2011). Use your words: The role of language in the development of
toddlers’ self-regulation. Early Childhood Research Quarterly, 26, 169-181.
doi:10.1016/j.ecresq.2010.09.002
van Kleeck, A. (1998). Preliteracy domains and stages: Laying the foundations for beginning
reading. Journal of Children’s Communication Development, 20, 33-51.
Vaughn, S., Wanzek, J., Woodruff, A. L., & Linan-Thompson, S. (2008). Prevention and early
identification of students with reading disabilities. In D. Haager, J. Klinger, & S. Vaughn
(Eds.), Evidence-based reading practices for response to intervention (pp. 11-28).
Baltimore, MD: Brookes.
Vitiello, V. E., Booren, L. M., Downer, J. T., Williford, A. P. (2012). Variation in children’s
classroom engagement throughout a day in preschool: Relations to classroom and child
factors. Early Childhood Research Quarterly, 27, 210-220.
doi:10.1016/j.ecresq.2011.08.005
Vygotsky, L. (1978). Mind in society: The development of higher psychological processes.
Cambridge, MA: Harvard University Press.
Waldfogel, J. (2012). The role of out of school factors in the literacy problem. The Future of
Children, 22, 39 – 54.
Waldfogel, J. & Washbrook, E. (2011). Early years policy. Child Development Research.
Retrieved from http://www.hindawi.com/journals/cdr/2011/343016/abs/.
doi:10.1155/2011/343016
Walker, O. L., Henderson, H. A. (2012). Temperament and social problem solving competence
in preschool: Influences on academic skills in early elementary school. Social
Development, 21, 761-779.
Wang, S. & Aamodt, S. (2011, September 24). Delay kindergarten at your child’s peril. The New
York Times. Retrieved from
http://www.nytimes.com/2011/09/25/opinion/sunday/dont-delay-your-kindergartnersstart.html.

169

Wang, M. C., Haertel, G. D., & Walberg, H. J. (1997). Learning influences. In H. J. Walberg &
G. D. Heartel (Eds.), Psychology and educational practice (pp. 199-211). Berkeley, CA:
McCatchan.
Wasik, B. H., & Hendrickson, J. S. (2004). Family literacy practices. In C. A. Stone, E. R.
Silliman, B. J. Ehren, & K. Apel (Eds.), Handbook of language and literacy:
Development and disorders (pp.154-174). New York: Guilford Press.
West, J., Denton, K., & Reaney, L. (2000). The kindergarten year: Findings from the Early
Childhood Longitudinal Study, kindergarten class of 1998-99. Washington, DC: US
Department of Education, National Center for Education Statistics.
Winter, S. M., & Kelley, M. F. (2008). Forty years of school readiness research: What have we
learned? Childhood Education, 84, 260-266. doi:10.1080/00094056.2008.10523022
Winter, M. & Klein, A. F. (1970). Extending the kindergarten day: Does it make a difference in
the achievement of educationally advantaged and disadvantaged pupils? Union City, NJ.
Bureau of Elementary and Secondary Education.
Wolf, M., Bally, H., & Morris, R. (1986). Automaticity, retrieval processes, and reading: A
longitudinal study in average and impaired readers. Child Development, 4, 988-1000.
Zigler, E., Gilliam, W. S., Barnett, W. S. (2011). The Pre-K Debates: Current Controversies &
Issues. Pacific Grove, CA: Brookes Publishing.
Zvoch, K., Reynolds, R. E., Parker, R. P. (2008). Full-day kindergarten and student literacy
growth: Does a lengthened school day make a difference? Early Childhood Research
Quarterly, 23, 94-107. doi:10.1016/j.ecresq.2007.08.001
Zvoch, K., & Stevens, J. (2013). Summer school effects in a randomized field trial. Early
Childhood Research Quarterly, 28, 24 – 32. doi: 10.1016/j.ecresq.2012.05.002

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