Part C Tracked

ECLS Part C v30 tracked.pdf

Early Childhood Longitudinal Study, Kindergarten Class of 2023-24 (ECLS-K:2024) August 2024 Materials Revision Request

Part C Tracked

OMB: 1850-0750

Document [pdf]
Download: pdf | pdf
Early Childhood Longitudinal Study,
Kindergarten Class of 2023-24
(ECLS-K:2024)
Kindergarten and First-Grade National Data Collection
and Transfer School Recruitment
OMB# 1850-0750 v.30

Supporting Statement
Part C
National Center for Education Statistics
U.S. Department of Education

October 2022
revised April 2023
revised October 2023
revised April 2024

TABLE OF CONTENTS

Section

Page

C.1

Introduction ................................................................................................................. 1

C.2

ECLS-K:2024 Parent Surveys .................................................................................... 3
C.2.1 Research Questions ..................................................................................... 4
C.2.2 Kindergarten Parent Surveys: Construct Coverage ..................................... 5
C.2.2.1
C.2.2.2

Constructs for the Parent Surveys ........................................ 5
Constructs for the Abbreviated Parent Survey................... 23

C.2.3 Spring First-Grade Parent Survey: Construct Coverage ........................... 24
C.3

Teacher Surveys ........................................................................................................ 29
C.3.1 Kindergarten and First-Grade Teacher Surveys: Research
Questions .................................................................................................. 30
C.3.2 Kindergarten Teacher Surveys: Construct Coverage ................................ 30
C.3.3 Spring First-Grade Teacher Surveys: Construct Coverage ....................... 41

C.4

Special Education Teacher Surveys .......................................................................... 45
C.4.1 Kindergarten Special Education Teacher Surveys .................................... 46
C.4.1.1 Kindergarten Special Education Teacher
Surveys: Research Questions ................................................ 46
C.4.1.2 Kindergarten Special Education Teacher
Surveys: Construct Coverage ................................................ 46
C.4.2 Spring First-Grade Special Education Teacher Surveys ........................... 49
C.4.2.1 Spring First-Grade Special Education Teacher
Surveys: Research Questions ................................................ 49
C.4.2.2 Spring First-Grade Special Education Teacher
Surveys: Construct Coverage ................................................ 50

C.5

School Administrator Surveys .................................................................................. 51
C.5.1 Kindergarten and First-Grade School Administrator Survey:
Research Questions ................................................................................... 51
C.5.1.1 Spring Kindergarten School Administrator Survey .............. 52
C.5.1.2 Spring Kindergarten School Administrator
Survey: Construct Coverage ................................................. 52
C.5.2 Spring First-Grade School Administrator Survey ..................................... 58
C.5.2.1 Spring First-Grade School Administrator Survey:
Construct Coverage ............................................................... 58
References ........................................................................................................ 61

iii

Part C – The ECLS-K:2024 Kindergarten and First-Grade National
Instrument Details
C.1

Introduction

The design of the ECLS-K:2024 and its survey instruments is guided by a conceptual framework of
children’s development and learning that emphasizes the interaction among the various environments that
children experience and the resources within those environments to which children have access. For this
reason, the study collects information on a wide array of topics, including the characteristics of the child,
the child’s family, the community, nonparental care and education arrangements, and the child’s school
and classroom environments. The ECLS-K:2024 incorporates multiple respondents so that information
about each of the environments children experience can be collected from those most likely to provide
accurate and reliable data. The respondent surveys included in the study and the general topics covered in
each include:
•

Parent Survey—to be completed by parents/guardians of children in the study. Across the two
waves of collection in kindergarten and one wave of collection in first grade, the parent instruments
include questions about family structure, the languages spoken in the home, parent education,
parent employment, the home environment, the parent’s health and well-being, family practices,
food security and consumption, discipline, parent involvement in school, school practices, early
care and education, and the child’s behavior regulation. Parents provide assessments of children’s
social skills that are comparable to those in the teacher survey and also report on their children’s
level of physical activity, health, and disabilities.

•

General Classroom Teacher Survey—to be completed by classroom teachers of children in the
study..1 There are two teacher surveys. The first, the teacher-level survey, includes questions about
the classroom and student body characteristics, class schedules, class materials, instructional
practices, and curriculum. It also includes items on the teacher’s background, teaching experience,
and attitudes about teaching and the school climate. The second survey is a child-level survey that
has questions specifically about each study child and includes the teacher’s ratings of the child’s
academic and cognitive abilities, behaviors, and social skills, as well as information about program
placements and special services that each child may receive.

•

Special Education Teacher Survey—to be completed by the special education teacher or service
provider for children in the study who have an Individualized Education Program (IEP). There are
two surveys for the special education teacher. The first survey, the teacher-level survey, includes
questions about the teacher’s background, training, and school assignment. The second survey, the
child-level survey, has questions about the study child who has an IEP, including items about child
characteristics and services the child receives.

•

School Administrator Survey—to be completed by the principal or director of each school attended
by a child in the study. This instrument includes a broad range of questions about the school setting;
policies, programs, and practices at the school level and in kindergarten and first grade; and
questions about the principal and about the teaching staff.

The design and implementation of these instruments was tested in the fall 2022 K-1 field test. The
resulting data were reviewed for missingness, bias, and other issues. Fall and spring kindergarten items
1

The ECLS-K:2024 includes a census of primary kindergarten teachers in all sampled schools in the base year. Therefore, all kindergarten teachers
at participating schools were included in the study regardless of whether they had a study child in their classroom. Kindergarten teachers who did
not teach any sampled children were asked to complete the teacher-level survey, but not the child-level survey.

C-1

were revised or deleted as needed for the launch of the national study in the fall of 2023 and the spring
kindergarten round in spring 2024. The spring first-grade items were also revised or deleted as needed for
the spring of 2025. The data from the final instruments used in the national study can be used, in
conjunction with the data obtained in the ECLS-K:2024 direct assessments, to answer a wide variety of
research questions about how home, school, and neighborhood factors relate to children’s cognitive,
social, emotional, and physical development.

The following instruments are included in the current OMB package:
•

B-3a Spring First Grade Parent Web Survey

•

C-5a Spring First Grade Teacher Teacher-Level Web Survey

•

C-8a Spring First Grade Special Education Teacher Teacher-Level Web Survey

•

D-5a Spring First Grade Teacher Child-Level Web Survey

•

D-8a Spring First Grade Special Education Teacher Child-Level Web Survey

•

E-3a Spring First Grade School Administrator Web Survey

In an upcoming revision request (revision request 4), the following will also be included:
•

B-3b Spring First Grade Parent Web Survey, Spanish

•

B-3c Spring First Grade Parent Paper Survey, Abbreviated

•

C-5b Spring First Grade Teacher Teacher-Level Paper Survey

•

C-8b Spring First Grade Special Education Teacher Teacher-Level Paper Survey

•

D-5b Spring First Grade Teacher Child-Level Paper Survey

•

D-8b Spring First Grade Special Education Teacher Child-Level Paper Survey

•

E-3b Spring First Grade School Administrator Paper Survey

•

The instruments included in the current OMB package reflect all of the changes expected for the
spring kindergarten surveys. The fall kindergarten instruments were approved in a July 2023
revision request. Final spring first-grade items/instruments that have been revised in response to
fall 2022 field test analyses and, when appropriate, fall 2023 national data collection experiences
will be submitted in future revision request memos with 30-day comment periods. For the current
OMB package, focus was placed on refining the spring kindergarten web and paper surveys
based on final analyses of the K-1 field test data. Web surveys for spring kindergarten and spring
first grade were drafts included in the October 2022 submission in order to show the expected
research domains and the basic structure of the instruments. The spring kindergarten and spring
first-grade web instruments were not fully updated in the October 2022 submission. The spring
kindergarten survey has been revised, but the spring first grade survey has not changed since that
submission. Revisions including those to update spring first grade to use the most recent version

C-2

of items are forthcoming in a future version request.2 Additionally, spring first-grade paper
surveys will be developed when their respective web survey is final.
The following sections include research questions that may be addressed with the data from each
instrument and lists of the constructs and accompanying discussion of some of the important constructs
covered by each instrument. Specifically, Part C provides information about the general contents of the
ECLS-K:2024 K-1 national parent surveys, the school administrator surveys, and the regular classroom
and special education teacher surveys. The survey instruments can be viewed in Attachments B (parent
web surveys), C (primary and special education teacher-level web and paper surveys), D (primary and
special education child-level teacher web and paper surveys), and E (school administrator web and paper
surveys. ), G (the full catalog of items along with information about the role each item plays in addressing
the research questions and theoretical constructs described below) and H (a list of all spring kindergarten
items from the field test that were removed, added, and changed, along with a rationale for the changes).
The full draft surveys are being presented and items are also listed in Attachments G andFor spring first
grade, the information from attachment G and H were combined into a single Attachment H.
In the October 2023 revision request, all spring kindergarten instruments have been updated to be their
final versions. Specifically, the following attachments have been updated: Attachment B-2 (spring
kindergarten parent web survey), Attachment C-3 (spring kindergarten teacher-level teacher web survey),
Attachment C-4 (spring kindergarten teacher-level teacher paper survey), Attachment C-6 (spring
kindergarten teacher-level special education teacher web survey), Attachment C-7 (spring kindergarten
teacher-level special education teacher paper survey), Attachment D-3 (spring kindergarten child-level
teacher web survey), Attachment D-4 (spring kindergarten child-level teacher paper survey), Attachment
D-6 (spring kindergarten child-level special education teacher web survey), Attachment D-7 (spring
kindergarten child-level special education teacher paper survey), Attachment E-1 (spring kindergarten
school administrator web survey), and Attachment E-2 (spring kindergarten school administrator paper
survey). Attachments C through E for the first-grade surveys were renumbered to accommodate new
paper survey attachments for the spring kindergarten paper surveys. In addition, tabs for the spring
kindergarten instruments have been updated in Attachment G but no changes to the spring first-grade
instrument tabs have been made. Attachment H is a new attachment provided to show item-level changes
since the field test. Attachment B-2b (spring kindergarten abbreviated parent paper survey) is a new
attachment provided to show an abbreviated paper parent survey that may be administered.

C.2

ECLS-K:2024 Parent Surveys

The ECLS-K:2024 plans to survey parents in all rounds of ECLS-K:2024 data collection. Parents will be
asked to complete surveys in the following rounds of data collection: fall kindergarten, spring
kindergarten, spring first grade, spring third grade, and spring fifth grade. This document will only
discuss the fall kindergarten, spring kindergarten, and spring first-grade data collections.
The children in the study will be from a broad range of family and community backgrounds and enter
kindergarten with widely differing abilities and levels of preparation for school. Understanding these
variations and examining the ways in which home and school environments interact as children progress
through school is a key goal of the ECLS-K:2024. Surveying parents is central to obtaining the
information necessary to measure these constructs over time.
The role of the parent in these surveys is twofold. First, because of the young age of the children, parents
will provide indirect assessments of their children to enhance the direct assessments. Second, parents will
provide information on the home environment, including parenting practices and the family’s
2

Future revision requests may also include abbreviated surveys for respondents who do not complete full-length surveys during the initial weeks
of data collection.

C-3

involvement with the school. In addition, the parents will be primary informants on their neighborhood
and will be asked questions to supplement available census data.3 The ECLS-K:2024 defines the parent to
be surveyed as the child’s primary caretaker at the time of the survey. Information will also be collected
about other parental figures in the household.

C.2.1

Research Questions

Research questions related to the ECLS-K:2024 kindergarten and spring first-grade parent survey items
are shown below.
P-RQ1. Policy Issues
•

What is the early care and education (ECE) landscape for children during kindergarten and the year
prior to kindergarten entry? How does it differ by child background characteristics such as SES,
region, and other demographics?

•

What special education and related services are being made available to children through the
Individuals with Disabilities Act (IDEA)?

•

What are the characteristics of parents who take advantage of the opportunity to choose schools?
When choosing a school what do parents consider?

P-RQ2. School Readiness
•

What skills and experiences do children have upon entry into kindergarten entry and how do these
relate to development through elementary school?

•

What actions do parents take to prepare their children for school and to ease their adjustment to
school? How do these actions relate to later experiences as children progress though elementary
school?

•

How do schools respond to children with different backgrounds and experiences? How do schools
help ease the transition into kindergarten and later grades? How do schools respond to children
who exhibit problem behaviors or who are struggling in school?

P-RQ3. Early School Experience and Academic Performance
•

What protective factors and/or difficulties do children experience during their kindergarten year?

•

How varied are children’s experiences in the year prior to kindergarten? In what ways does this
variation relate to success at school entry?

•

How are parents involved in their children’s education during the elementary school years and how
does this involvement relate to child development over this period?

•

How do parents and schools respond to problems children might experience in school and how are
these responses related to child development?

•

How do schools and teachers involve parents in their children’s education, or how do parents
involve themselves in the schooling process?

P-RQ4. Transitions to Kindergarten and Beyond

3

In the national study, variables will be created that provide zip and census tract codes for homes and schools. These variables can be used to
addlink to census data to the ECLS-K:2024 cases.

C-4

•

What kinds of transition patterns exist for children as they make the move from preschool (or no
school) to kindergarten and later elementary school grades?

•

How much movement occurs across and within sectors (e.g., private school to public school) during
and between kindergarten and later elementary school? How do those children and families who
change sectors compare to those who remain in the same sector?

•

How is changing schools between grades related to children’s cognitive and socioemotional
development during the elementary school years?

P-RQ5. Cognitive and Socioemotional Growth
•

How does socioemotional development differ by student and family characteristics? How is
socioemotional development related to children’s difficulties and successes in school?

•

What are the cognitive growth trajectories for students over time? How do these cognitive growth
trajectories vary between students over time?

•

How do cognitive and socioemotional growth covary?

•

What are the patterns of grade retention for elementary school children?

•

What are the patterns of intervention for elementary school children experiencing difficulties in
school?

•

What factors are related to students’ placement in particular educational programs (e.g., special
education or gifted and talented programs)?

C.2.2

Kindergarten Parent Surveys: Construct Coverage

In the kindergarten year, there are two parent surveys – one in the fall and one in the spring. For the
purposes of this section, the fall and spring kindergarten surveys are discussed together, even though
some items are asked in only one round of the study or asked in both rounds only if there are data missing
from the fall collection. The constructs for fall and spring kindergarten parent surveys are discussed
below.
To bolster information collected from parents, in the spring of kindergarten an abbreviated parent survey
maywill be fielded in the spring of kindergarten, toward the end of the spring kindergarten data collection
window. The abbreviated survey will be a paper survey, one page (front and back), and take parents an
estimated 5 minutes to complete. The constructs covered in the abbreviated survey are a subset of
constructs fielded in the full fall and spring kindergarten parent surveys. Further information on the
constructs is presented at the end of this section (C.2.2. 2).
C.2.2.1

Constructs for the Parent Surveys

Child Characteristics
The kindergarten parent surveys include questions about the following child characteristics:
•

Child’s gender (fall and spring kindergarten);

•

Child’s date of birth (fall and spring kindergarten);

•

Timing of kindergarten enrollment with respect to school guidelines (fall kindergarten);

•

Whether child is in first, second, or third year of kindergarten (fall kindergarten);

•

Enrollment in transitional kindergarten or pre-first grade (fall kindergarten); and

C-5

•

Child’s race/ethnicity (fall and spring kindergarten).

Parent’s Involvement with the Child’s Education
Parental involvement in education has proven to be a critical influence on school outcomes for children
(Stallings and Stipek 1986; Hoover-Dempsey and Sandler 1997; Gonzalez-DeHass, Willems, and Holbein
2005). However, parent involvement is not a single construct but rather refers to many diverse types of
home-school interaction. One type of parent involvement involves parents working with their child on
homework or educational activities at home or arranging for other persons inside or outside the household
to help with homework or tutor the child. Other ways that parents are involved with their children’s
education is in their interaction with teachers and through participation in organized school activities.
The research on parent involvement describes not just how parents are involved with schools but also how
schools work to involve parents. The reauthorization of the Elementary and Secondary Education Act
(ESEA) as the Every Student Succeeds Act (ESSA) in 2015 includes new federal grants for Statewide
Family Engagement Centers that focus on engaging parents and the community (Ujifusa and Tully 2016).
The ECLS-K:2024 will ask parents about school practices designed to increase involvement and
communication with parents and ask them to evaluate how well their child’s school does these practices.
Questions will also be asked about practices to provide an equal and culturally responsive environment
and barriers to involvement such as language barriers or inconvenient meeting times.
The following data about parent involvement will be collected from the parents:
•

Verification of the child’s current kindergarten grade and school (fall kindergarten);

•

Parent’s choice of school for child (fall kindergarten);

•

School attendance (for homeschooled children) (fall kindergarten);

•

School’s transition activities for kindergarten (fall kindergarten);

•

Child’s adjustment to kindergarten (fall kindergarten);

•

School-initiated contact with parents about behavior problems (spring kindergarten);

•

Parent attendance at parent-teacher conferences and meetings (spring kindergarten);

•

Parent participation in school activities (spring kindergarten);

•

School practices to communicate with parents and encourage involvement (spring kindergarten);

•

School practices to provide an equal and culturally responsive environment (spring kindergarten);

•

Whether school provides translated materials (spring kindergarten);

•

Barriers to involvement with the school (spring kindergarten);

•

How often parent or someone else checked that the child completed homework (spring
kindergarten); and

•

Child activities outside of school hours (spring kindergarten).

School Avoidance
Children’s engagement in school has been linked to their achievement (Connell, Spencer, and Aber 1994;
Skinner et al. 1990; Ladd and Dinella 2009; Nystrand and Gamoran 1991) and educational progress over
time (Alexander, Entwisle, and Dauber 1993). As noted by Ladd and Dinella (2009), there are several
different types of school engagement, including behavioral, cognitive, and emotional engagement. Ladd
and Dinella (2009, p. 2) note that there are multiple definitions of each type of engagement and state that

C-6

behavioral engagement “refers to participation in the learning environment;” emotional engagement refers
to “children’s sentiments toward school;” and cognitive engagement refers to “the level of processing or
intellectual effort that students devote to mastering learning tasks.” They note that emotional engagement
has been studied less frequently than cognitive engagement or behavioral engagement. In a longitudinal
study that followed children from school entry to the eighth grade, Ladd and Dinella (2009) examined
both emotional engagement (using parent and teacher measures of children’s school liking and avoidance)
and behavioral engagement (using a teacher measure of children’s cooperative and resistant participation
in the classroom) to determine their relation to children’s achievement. Findings showed that both types
of engagement were related to changes in children’s achievement over time.

Like the ECLS-K:2011, the ECLS-K:2024 parent survey will include school avoidance as a measure of
student emotional engagement. These questions will be asked beginning in kindergarten rather than the
fourth grade as was done in the ECLS-K:2011 because it was recommended at the Technical Review
Panel (TRP) meeting that the study have a baseline measure of school avoidance to relate to school
adjustment. Items are taken from the Parent Report of School Liking and Avoidance Questionnaire
(P-SLAQ; Ladd et al. 2000), a scale developed for children in kindergarten and used throughout the
elementary school years. It asks about the following:
•

The child’s school avoidance (spring kindergarten).

Parental Beliefs and Expectations
Parents’ beliefs and expectations about their children is another area of interest in the ECLS-K:2024.
Mothers’ educational expectations for their children have been shown to be positively related to
children’s academic interests as they proceed through school, and academic interests are, in turn, related
to school performance (Dotterer, McHale, and Crouter 2009). Parent beliefs about the skills necessary for
success in kindergarten are often related to children’s skills at kindergarten entry. Parents’ beliefs
regarding these school readiness skills can also be compared with teachers’ beliefs about school
readiness, which will be collected in the teacher survey. With the coronavirus pandemic, parents have
additional areas of concern regarding whether their child is falling behind in education and to what extent
they can provide supports for their child (Horowitz 2020, The Education Trust 2020).
Three constructs related to parental beliefs and expectations are included in the parent survey:
•

Parent’s educational expectations for how far the child will go in school (high school, college, etc.)
(fall kindergarten);

•

Parent’s beliefs about school readiness (fall kindergarten); and

•

Family concerns about the child’s education and services given the coronavirus pandemic (e.g.,
how confident parents are that their child learned the skills they expected them to learn, concern
over the child falling behind in school as a result of any disruptions caused by the coronavirus
pandemic, receipt of special education services) (fall kindergarten).

Family Structure
Family structure is associated with children’s outcomes and the economic circumstances in which they
are raised. Research has shown that children with married parents generally have better physical and
mental health than children of parents who live together but are not married (Cavanagh and Fomby 2019).
Findings have shown that health benefits to children living in families with married parents are the same
regardless of whether the parents are the same or different sexes (Reczek et al. 2016). Umberson and
Thomeer (2020) note that one reason for findings about married parents may be that families with married

C-7

couples experience less instability, stress, economic issues, and changes in family routines and
relationships than families with unmarried couples. As reviewed by Umberson and Thomeer (2020),
family instability and transitions have been found to be negatively related to children’s health and wellbeing.
Parental divorce has been negatively related to a variety of children’s academic, social, and psychological
outcomes (Child Trends 2015). In addition, children born to single rather than married parents are more
likely to experience changes in family living arrangements over time and their parents report negative
behavioral and cognitive issues (Child Trends 2016). They are also more likely to experience poverty. In
2017, 41 percent of families headed by a single mother were living in poverty, compared to 8 percent of
families with married parents (Child Trends Databank 2019). Cohabitation has also been found to be
related to children’s outcomes. Children born to parents who cohabitate are less likely to be in a stable
family through age 12 than children born to married parents and are also more likely to experience
poverty (Manning 2015).
The longitudinal nature of the ECLS-K:2024 makes it ideal for investigating the impact of change in
family composition prior to and during children’s elementary school years.
The ECLS-K:2024 will gather data on the following aspects of family structure:
•

Number of household members age 18 and older (fall and spring kindergarten);

•

Number of household members age 17 and younger (fall and spring kindergarten);

•

Parents or guardians in the household (fall and spring kindergarten);

•

Family relationship of key parent figures to the child (e.g., adopted) (fall and spring kindergarten);

•

Gender, age, and race/ethnicity of key parent figures (fall and spring kindergarten);

•

Number of household members who are siblings to the child (fall and spring kindergarten);

•

Number of household members who are grandparents to the child (fall and spring kindergarten);

•

Marital status of the primary caretakers (fall and spring kindergarten);

•

Whether the child has always lived with the respondent and if not, for how long they have lived
together (fall kindergarten); and

•

Family structure change and loss (e.g., remarriage, divorce, and death) (fall and spring
kindergarten).

Parent Characteristics
Basic parental demographic information will include:
•

Resident parent figures’ gender, age, and race/ethnicity and nonresident parents’ gender (fall and
spring kindergarten); and

•

Parent’s vital status (collected by asking about a biological/adoptive parent who does not live in
the household or collected when a parent/parental figure identified in a previous round is no longer
in the household) (fall and spring kindergarten).

Home Language
English language learners (ELLs) are an increasing group of students in the United States. From 2000 to
2017, the percentage of children ages 5 to 17 who spoke a language other than English at home increased
from about 18 percent to about 23 percent (Federal Interagency Forum on Child and Family Statistics

C-8

2019). English language learners come from a variety of backgrounds, have different levels of proficiency
in English, and speak many different languages. In the United States, among students ages 5 to 18 who
reported speaking English less than “very well,” Spanish was the most common first or home language
(71 percent) followed by Chinese (4 percent) (Ruiz-Soto, Hooker, and Batalova 2015).
Children entering kindergarten as English language learners may face particular academic challenges in
addition to those related to socioeconomic status, such as low parent education levels. Using ECLSK:2011 data, Ansari and Crosnoe (2018) examined the transition to kindergarten for ELL students and
found that 48 percent of Hispanic and 54 percent of Asian-American children in the fall of kindergarten
came from homes where English was not spoken. Results from reading and mathematics assessments
showed that English language learners entered kindergarten about a year behind their classmates who
only spoke English; however, these findings were largely duerelated to lower maternal education. English
language learners showed strengths in teacher ratings of behavior and social skills, including approaches
to learning.
Some studies have focused on how non-English speaking children canmay be helpedsupported by
preschool programs Some studies have focused on the various development trajectories in early
elementary grades related to home language and preschool enrollment.. As reviewed by Ansari and
Crosnoe (2018), high-quality preschool programs have been related to increased school readiness for all
children, but the effects have often decreased as school continues, perhaps because investments in
children’s education before school entry are not sustained once school starts. One study by Bachman et al.
(2018) used kindergarten to third-grade data from the ECLS-K:2011 and examined academic and
behavioral outcomes for Latino children with different early care and education experiences. Bachman et
al. (2018) found that in the fall of kindergarten, Latino children from English-speaking families had
higher reading and mathematics assessment scores than those from Spanish-speaking families who were
in public preschool, Head Start, or not in preschool. These effects decreased greatly by the third grade.
However, Latino children who attended private center-based early care and education arrangements
showed nonsignificant differences by language spoken at home in reading outcomes in the fall of
kindergarten. By third grade, though, Latino children from English-speaking households who attended
private center-based early care and education arrangements had higher reading scores than children from
Spanish-speaking homes. There were few differences in social or behavior ratings by language or
preschool type in the fall of kindergarten, but by the third grade there were more externalizing problems
among English-speaking Latino children who had attended Head Start for preschool. Thus, there were
short-term effects of language and preschool early care and education arrangements on academic
outcomes in the fall of kindergarten, but long-term differences were inconsistent for academic and
behavior outcomes by the third grade.
The parent survey will include questions about the primary languages spoken in the homes of the study
children, in addition to questions about the home languages of the study children. Researchers can
consider the language environment at home along with information from the school and teacher surveys
about the child’s instructional environment to better understand the interplay of factors related to ELL
children’s academic progress.
The parent surveys include questions about:
•

Languages spoken in the home (fall and spring kindergarten);

•

Primary language spoken (fall and spring kindergarten);

•

How often parents speak a language other than English to the child (fall kindergarten); and

•

How often the child speaks a language other than English to parents (fall kindergarten).

C-9

Home Environment, Activities, and Cognitive Stimulation
The environment parents create in the home and the activities in which they engage with their children
represent a direct linkage between parental characteristics and the child’s development. The mother’s
parenting practices are closely associated with the development of her child (Kadry, Ali, and Sorour,
2017; Maccoby and Martin 1983), and the practices of the biological father and other parent figures in the
household such as step-parents and grandmothers have also been shown to also play a role in children’s
development (e.g., Dunifon and Kowaleski-Jones 2007; Kadry, Ali, and Sorour, 2017).
Many parent-child activities, for example, with respect to literacy, have been linked to children’s
achievement in school. Even early home literacy activities with infants may affect children’s outcomes
prior to school entry. Using ECLS-B data, Sonnenschein and Sun (2017) found that parents’ knowledge
of children’s development and home literacy activities when children were 9 months old mediated the
relationship between race/ethnicity and reading scores during preschool. ECLS-K data with children
starting in kindergarten have shown that children’s literacy is positively correlated with the frequency
with which parents read to their children (Almond and Holt 2005; U.S. Department of Education 2000;
Sy and Schulenberg 2005) and also with nonliterary, social activities (e.g., teaching children about nature,
doing arts and crafts, parents and children eating breakfast together) (Almond and Holt 2005).
Other activities related to children’s reading achievement measured in the ECLS-K were the parent telling
stories to the child, going to the library, going to museums, and the number of books in the home
(Almond and Holt 2005). The amount of time children spend reading to themselves has also been related
to reading achievement (Mullis, Campbell, and Farstrup 1993; Stutz, Schaffner, and Schiefele 2016;
Tamis-LeMonda, et al. 2019). One study that compared the ECLS-K and the ECLS-K:2011 showed that
parent investments in children’s learning increased in the ECLS-K:2011 (Bassok et al. 2016). Bassok et
al. 2016 found that children in the ECLS-K:2011 compared to those in the ECLS-K had more books and
engaged in more literacy activities in the home. Children in the ECLS-K:2011 compared to those in the
ECLS-K also had greater access to computers and enrichment activities inside and outside the home. In
the ECLS-K:2024, the home environment will be measured by asking parents questions about home
activities that have been used in both the ECLS-K and the ECLS-K:2011 (e.g., reading, playing games or
doing puzzles with the child).
The opportunity to engage in mathematical activities within the home environment has also been linked to
children’s early mathematics achievement. Home environments that are of high quality and include
mathematical activities have been shown to positively relate to children’s early mathematical
development (Blevins-Knabe and Musun-Miller 1996; Blevins-Knabe, Whiteside-Mansell, and Selig
2007). Although numeracy-related activities tend to be less prevalent in home environments as compared
to literacy-related activities, home environments where such opportunities are offered have been found to
relate to early numeracy skills for young children (Anders et al. 2012; Jacobs et al. 2005; LeFevre et al.
2009). Using data from ECLS-K:2011, Padilla, Cabrera, and West (2017) found that low-income
Hispanic children experienced fewer opportunities for cognitively stimulating activities in the home and
were also behind their White peers in mathematics, both at the beginning of kindergarten and by the end
of third grade.
Given the current climate (i.e., the continuing coronavirus pandemic) Given the coronavirus pandemic
and the recent reliance on technology for and the recent reliance on technology for distance and hybrid
learning, engagement with technology is a valuable piece of information related to children’s home
experiences. Questions about technological access (primarily access to computers) were included in
ECLS-K. Because in later years computers became available in many different forms, including various
handheld devices such as cell phones and tablets, as well as the development of social media, questions
about technology use in the ECLS-K:2011 were modified to allows for other electronic devices and to

C-10

include parent monitoring of social media. Currently, students have access to cell phones, smartphones,
computers, tablets, and other electronic devices at increasingly younger ages. (Rideout and Robb 2020).
Due to the growing use of technology at younger ages and the continuing coronavirus pandemic, it is
more important than ever that families have internet access. As the pandemic has influenced technology
use and distance learning, the ECLS-K:2024 will be uniquely positioned to examine the impact of
distance learning on the use of technology in education moving forward. The ECLS-K:2024 will
continue to ask questions about access to and parental monitoring of use across more media
optionselectronic devices than in the ECLS-K:2011 in order to reflect growth in technology usehe The
ECLS-K:2024 will ask more questions about access to and parental monitoring of use across electronic
devices than in the EECLS-K:2011 in order to reflect growth in technology use.. It will also add The
ECLS-K:2024 includes questions about children’s own devices, family rules about device use, and
whether such devices are allowed in children’s bedrooms at night. The ECLS-K:2024 provides an
opportunity to investigate children’s early use of media electronic devices and technology and allows
researchers to examine how screen time affects not just learning and achievement but also social
relationships, emotional health, behavior, and physical health in the current and changing technological
landscape.
The amount of chaos in the home environment has also been related to children’s outcomes, and the
ECLS-K:2024 includes questions will be included in the parent surveys on this topic. A chaotic home
environment may be characterized by low levels of order, predictability, and family routines, along with
high levels of noise, crowding, and many persons coming and going (Johnson et al. 2008; Matheny et al.
1995). Household chaos has been associated with poor reading, vocabulary, and phonological awareness
(Johnson et al. 2008), low general academic achievement (Berger et al. 2019; Berry et al. 2016; GarrettPeters et al. 2016), lower low cognitive ability (Hart et al. 2007), and behavior problems (Coldwell, Pike,
and Dunn 2006).
By contrast, aspects of the home environment that suggest predictability, safety, and family routines such
as eating meals together, children being in a neighborhood where it is safe to play outside and having a
regular sleep schedule have been linked to positive outcomes for children. In the ECLS-K, children whose
families ate fewer meals together and whose parents perceived the neighborhood as less safe to play
outside were more likely to be overweight in elementary school (Gable, Chang, and Krull 2007; Galaviz,
Zytnick, Kegler, and Cunningham 2016). In addition, findings from the ECLS-K also showed a link
between parents setting regular bedtimes and children’s kindergarten reading scores. Items assessing such
aspects of home environments will be included in the ECLS-K:2024.
The ECLS-K:2024 parent survey will also ask about the hours of sleep children generally get on average
weeknight. Sleep has been related to many different children’s outcomes including achievement (Eide and
Showalter 2012) and depression (Smaldone, Honig, and Byrne 2007).
Additionally, family experiences have been affected by the coronavirus pandemic. Research suggests a
variation in family’s coping resources during the pandemic, time spent as a family, and access to
resources outside the household (Weeland, Keijsers, and Byrne 2021).
The following information collected in the ECLS-K:2024 parent survey will address research questions
concerning how the home environment influences children’s cognitive and social development:
•

Home learning activities (fall kindergarten);

•

Literacy materials in the home (fall kindergarten);

•

Parents’ frequency of reading books with the child (fall kindergarten);

•

Reading or looking at picture books by the child (fall and spring kindergarten);

C-11

•

Math activities (spring kindergarten);

•

Amount of chaosChaos in the home (spring kindergarten);

•

Media engagement and usage (spring kindergarten);

•

Availability and use of a home computer/digital device (spring kindergarten);

•

Amount of time the child plays video games and watches shows (spring kindergarten);

•

Children’s organized activities (sports, music, art, etc.) (spring kindergarten);

•

Frequency with which the family eats meals together (spring kindergarten);

•

Hours of child sleep and whether child has regular bedtime (spring kindergarten);

•

Outside play (spring kindergarten);

•

Parent perceptions of neighborhood resources and problems (spring kindergarten);

•

Outings and activities with child (spring kindergarten);

•

Child activities outside of school hours (e.g., outings to zoos, concerts, museums, libraries,
bookstores, etc.) (spring kindergarten);

•

Child’s participation in religious activities or instruction (spring kindergarten);

•

Child’s volunteer work or community service (spring kindergarten);

•

Talking to child about ethnic or racial heritage (spring kindergarten);

•

Talking to child about family religious beliefs or traditions (spring kindergarten); and

•

Family experiences during the coronavirus pandemic (e.g., restricted in-person interactions with
others, virtual interactions with others, participation in learning pods and extracurricular activities
during 2020) (fall kindergarten).

Neighborhood
The neighborhoods in which children are raised have been related to their academic outcomes and
experiences. One way that neighborhoods contribute to children’s outcomes is through resources, such as
having a public library. As reviewed by Philbin et al. (2019), public libraries have programs to help with
children’s reading and social skills (e.g., story hours and play groups) and provide access to the internet,
health information, and employment information. Other studies show that resources such as having a
neighborhood park are related to children’s outcomes. Reuben et al. (2020) used data from the 2016
National Survey of Children’s Health (NSCH) and found that not having a neighborhood park was related
to children having less physical activity, more screen time, less sleep, being overweight or obese, and
having more ADHD symptoms. Poverty was also associated with not having a neighborhood park.
Children in the ECLS-K:2011 in high poverty neighborhoods started kindergarten about a year behind
academically compared to those living in the lower poverty neighborhoods (Wolf, Magnuson, and
Kimbro 2017). Comparing neighborhood and family poverty for children in the ECLS-K:2011 to that of
the ECLS-K, Wolf, Magnuson, and Kimbro (2017) also found that a greater proportion of children in the
ECLS-K:2011 than in the ECLS-K lived in moderate to high poverty neighborhoods. Gabarino and
Kostelny (1993) found that the rate of reported child abuse in the poorest areas is four times higher than
the rate in more affluent areas. Aikens and Barbarin (2008) found that negative neighborhood conditions,
including low ratings of neighborhood safety, were related to lower growth in literacy and reading ability
from kindergarten through the third grade. Children in poor neighborhoods, especially public housing

C-12

developments, are also more likely than their peers to witness or be victims of violent crime. Parental
adaptations to the immediacy of violence in the poorest urban areas include staying close to their children,
as well as restricting children’s movement in the neighborhood.
The ECLS-K:2024 parent survey focuses on these aspects of children’s neighborhoods:
•

Neighborhood resources (spring kindergarten); and

•

Neighborhood safety (spring kindergarten).

Child’s Social Skills, Problem Behaviors, and Approaches Toward Learning
Social skills have been found to be significant predictors of academic achievement (Clark, Gresham, and
Elliot 1985). Problem behaviors, such as aggression or withdrawal, are consistently correlated with
negative outcomes for children, including rejection by their peers (for a review of this research see
Meisels, Atkins-Burnett, and Nicholson 1995). Based on work by Meisels and his colleagues, the ECLSK:2024 includes items adapted from the Social Skills Rating System (SSRS) (Gresham and Elliot 1990)
and the Social Skills Improvement System (SSIS) (Gresham and Elliot 2008).
The ECLS-K:2024 also includes measures of approaches toward learning. Aspects of learning styles
include intellectual openness and curiosity, task persistence and attentiveness, reflection and
interpretation, and imagination and creativity. The social skills and approaches to learning behavior
ratings from parents are a useful complement to similar measures which will be provided by the teachers.
Having two sources of information about the social skills of the children allows researchers to view
children’s development in this area in both the home and school environments.
The ECLS-K:2024 parent surveys will include items measuring the child’s:
•

Approaches toward learning (spring kindergarten);

•

Self-control (spring kindergarten);

•

Social interaction (spring kindergarten);

•

Externalizing
problem
kindergarten); and

•

Internalizing problem behaviors: Sad/Lonely sad/lonely (spring kindergarten).

behaviors:

Impulsive/Overactiveimpulsive/overactive

(spring

Children’s Executive Function
Executive functions are interdependent processes that work together to accomplish purposeful, goaldirected activities and include working memory, attention, inhibitory control, and other self-regulatory
processes. Executive processes work to regulate and orchestrate cognition, emotion, and behavior to enable
a student to learn in the classroom. For example, executive control involves the ability to allocate attention,
to hold information in working memory, and to withhold an inappropriate response (Casey et al. 2000). Not
only are these cognitive and behavioral processes predictive of reading and mathematics achievement (Blair
and Razza 2007), but there is also emerging research that indicates that some of these cognitive processes
are trainable (Rueda et al. 2005; Klingberg et al. 2005) and can be improved upon in regular public school
classrooms without costly interventions (Diamond et al. 2007).
The ECLS-K:2024 parent survey includes items on attention, which has been found to relate to children’s
academic outcomes (Blair and Raver 2015; McClelland et al. 2015). Two aspects of attention measured in
the ECLS-K:2024 are attention focusing (the ability to sustain attention) and attention span persistence
(the ability to control behavior and emotions to complete challenging tasks) (Zhou et al. 2007). Both are
considered aspects of effortful control, a temperament construct that overlaps with executive function and
has been associated with a range of positive outcomes in children including academic achievement in

C-13

kindergarten and first grade and lower levels of externalizing problems in children ages 5 to 10
(Hernandez et al. 2017, Zhou et al. 2007). Attention span persistence may be a more complex ability than
attention focusing; McClelland et al. (2013) found that attention span persistence at age 4 significantly
predicted math and reading achievement at age 21 as well as the odds of college completion by age 25.
Additionally, using a direct assessment of self-regulation (including attention flexibility and working
memory), such skills have been found predictive of emergent literacy, vocabulary, and mathematics skills
for young children (McClelland 2007; Ponitz et al. 2009).
Items in the parent surveys will measure children’s:
•

Attention focusing (spring kindergarten); and

•

Attention span persistence (spring kindergarten).

Critical Family Processes
Primary caregivers must provide for children’s basic material needs, nurturance, and protection. Parents
are less able to perform as effective caregivers during times of family dysfunction. A variety of family
circumstances pose threats to the healthy functioning and development of children, for example, family
illness and disability and high levels of interparental conflict (Shonkoff 1992; Peterson and Zill 1986).
Conflict between parents negatively influences the psychological adjustment of school-age children,
whether parents live together or not (Grych and Fincham 1990). Furthermore, daughters of mothers who
display negative conflict strategies with fathers exhibited both social and physical aggression with peers
compared to daughters whose mothers did not have marital conflict (Underwood et al. 2008). Social and
material supports for parenting, both on a regular basis and in case of an emergency, may improve
parenting styles and enhance parents’ ability to foster their child’s development. Family routines and the
regularity of family life play an important role in the healthy development of school-age children.
To understand family processes, it is also important to understand negative experiences in the family
members’ lives. Adverse experiences in childhood have been related to problems with health and
substance abuse in adulthood (Center for Disease Control and Prevention 2020). New to the ECLSK:2024 will be a measure of children’s adverse experiences from the 2018 National Survey of Children’s
Health. Questions in the ECLS-K:2024 will ask about family economic hardship, divorce, death,
neighborhood violence, and being treated unfairly.
The following constructs will address research questions having to do with how family processes
influence children’s development:
•

The presence of parents, other parent-like figures, and grandparents to support the child and parent
(spring kindergarten); and

•

Adverse child experiences (spring kindergarten).

Early Care and Education (ECE) Arrangements
Children’s early care and education (ECE) experiences have been linked to positive short- and long-term
outcomes for children (Campbell et al. 2012; Deming 2009; Yoshikawa et al. 2013). For example, in their
review, Yoshikawa et al. (2013) concluded that preschool programs are related to short-term impacts on
children’s academic school readiness and that gains are larger for children who attended higher quality
programs. Additionally, the review conducted by Yoshikawa et al. (2013) concluded that existing benefitcost studies also find positive results with respect to investment returns for early childhood programs
when benefits are monetized.
School-aged children’s after-school needs vary. A national study of children in kindergarten through
twelfth grade conducted in January through March 2020 by the Afterschool Alliance (just before the

C-14

coronavirus pandemic reshaped schooling in the U.S.) suggests that for every child in an afterschool
program, there are three waiting to get in (Afterschool Alliance 2020). The study noted differences by
characteristics of children and families, for example, higher income families are more likely than lowincome families to be involved in afterschool programs. Collecting current information on enrollment in
afterschool programs provides much needed current national information.
Research has indicated that ECE received during the school years can have implications for children’s
functioning in the elementary school grades. As reviewed by Durlak et al. (2010), although there are some
inconsistent findings, many studies have shown that after-school care programs can have positive effects
on children’s achievement, behavior, physical health, and social competence. Studies of the effects of
informal adult care with a relative have shown no apparent risks (Sarampote, Bassett, and Winsler 2004)
and some protective effects for children of lower socioeconomic status who experience early care and
education with a sitter or relative compared with children of lower socioeconomic status who did not have
this type of care (Pettit et al. 1997). Pettit et al. (1997) also found protective effects for children of lower
socioeconomic status who had ECE in a day care center compared to children of lower socioeconomic
status who did not have this type of care. It was also found that girls who had small amounts of ECE with
a nonrelative neighbor had better behavior and achievement ratings than those without any nonrelative
neighbor early care and education or those with high amounts of nonrelative neighbor early care and
education. Additionally, the coronavirus pandemic affected children’s access to and experiences in early
education and care, with research suggesting greater challenges for children from low-income families
(Adams and Todd 2020, Weiland, Keijsers, and Byrne 2021).
Throughout the study, the ECLS-K:2024 will collect information on the number, consistency, and variety
of formal before- and after-school care arrangements that the children currently experience. During the
first year of the study, information will also be collected about children’s ECE during the year before
kindergarten. In sum, the study will include items on the following topics:
•

Participation in ECE, by type of arrangement (e.g., relative; non-relative; and center-based) (fall
and spring kindergarten);

•

Number of ECE arrangements, by type of arrangement (e.g., relative; nonrelative; and centerbased) (fall kindergarten);

•

Head Start attendance (fall and spring kindergarten);

•

Attendance of state sponsored preschool (fall kindergarten);

•

Characteristics of the ECE provider (i.e., the language the provider speaks most when caring for
the child) (fall kindergarten);

•

Time the child spent/spends in ECE arrangements (fall kindergarten); and

•

ECE arrangements during the coronavirus pandemic (e.g., continuity or disruptions in care
arrangements; remote learning experiences; balancing parent work with child care disruptions;
availability of a person inside or outside household to help with remote learning) (fall kindergarten).

Kindergarten Selection and Choice
The parent survey includes items asking how parents learned about their child’s kindergarten program as
well as the most important factors they considered in selecting a kindergarten. Previous literature focused
on how parents make decisions about the school their child will attend show mixed results on what the
most important factors are. While some evidence suggested academic quality as a determining factor
(e.g., Witte 2001), others find searching for peer composition rises above academic quality in selection

C-15

(e.g., Schneider and Buckley 2002). Other previous work has also identified demographic differences in
the type of selection information to which parents respond (Hart and Figlio 2015).
The ECLS-K:2024 parent survey will provide information on the following:
•

How respondent learned of the selected kindergarten (fall kindergarten);

•

Reasons for choosing child’s kindergarten (fall kindergarten);

•

Charge or tuition for school (fall kindergarten); and

•

Use of a voucher from the government to pay for school (fall kindergarten).

Involvement of Nonresident Parent
Asking questions about nonresidential parents is of great interest to researchers of family involvement.
Nearly four out of ten children are born outside of marriage in the United States (Ventura 2009).
Although one study found that 40 percent of nonmarital births are to mothers who are living with
partners, the majority of children born outside of marriage do not live with their fathers (Chandra et al.
2005). The high incidence of divorce and separation in this country leads to more children living apart
from one of their parents.
Although many fathers who do not live with their children tend to play a smaller role with their children
than do resident fathers and may lose contact with them over time, a significant proportion of nonresident
fathers do remain involved. Moreover, their involvement is important to children’s lives (Amato and
Gilbreth 1998; Nord, Brimhall, and West 1998; Jackson, Jeong-Kyun, and Franke 2009). Although the
majority of nonresident parents are fathers, an increasing number of children have nonresident mothers.
For both policy reasons and to understand children’s development, it is important to learn more about
both fathers and mothers who live apart from their children.
The following data about nonresident parents will be collected:
•

Whether child has biological or adoptive parents who are not currently living in the household (fall
and spring kindergarten); and

•

Time since last contact (either in person or by telephone, email, text, etc.) with biological/adoptive
parents no longer living in household (fall and spring kindergarten).

Child’s Health and Well-Being
This section includes items to identify children with different kinds of disabilities and to determine
whether children with disabilities are receiving services. The presence of disabilities is a significant risk
factor for children’s outcomes and is related to children’s development and education in school. These
items will also provide the data to analyze the accessibility of special education and other programs and
plans for children with disabilities. Other indices of children’s well-being include rate of growth, physical
fitness/activity, and health care utilization (Fattore and Mason, 2018; Newacheck and Hallfon 1988).
The importance of children’s health for school success is well established. Chronic conditions and
disabilities, such as hearing impairmentloss and physical handicapsdisabilities, not only “flag” youngsters
for administrative attention, they also shape the way that parents, peers, and school personnel relate to the
child (Alexander and Entwisle 1988). Even seemingly relatively mild conditions, such as earaches, may
affect children’s performance in school if left untreated.
Impairments in hearingHearing loss can contribute to deficits in speech and language acquisition, poor
academic performance, and social and emotional difficulties (Cunningham et al. 2003). The American
Academy of Audiology notes that 12 to 13 percent of children who are 6 to 19 years old have hearing loss

C-16

related to noise (e.g., noise that may come from listening to music through ear buds, loud toys, stereos,
sporting events, movie theaters, bands, etc.) and recommends that children be screened for hearing loss
yearly if they are involved in activities that expose them to loud noise (Hearing Loss Association of
America, 2018; National Hearing Conservation Association 2004). They also recommend that hearing
loss be ruled out whenever a child is being considered for special education services (American Academy
of Audiology 2011). It is important to note that capturing impairments in hearing may be even more
important in the ECLS-K:2024 because of the increased noise contamination in classrooms related to
additional technology and the variability in teacher approaches to helping all students hear in the
classroom (Da Cruz et al. 2016).
Impairments in vision can also lead to learning and socioemotional difficulties. About one in four schoolage children have vision problems including amblyopia (lazy eye), strabismus (crossed eye), and myopia
(nearsightedness). Studies find that there are racial and ethnic differences in the prevalence and incidence
of refractive disorders. A study of 2,523 children in Birmingham, Alabama found that 33.6 percent of
Asian children and 36.9 percent of Hispanic children had astigmatism (Collaborative Longitudinal
Evaluation of Ethnicity and Refractive Error Study Group 2003).
Other important indices of children’s well-being include rate of growth, physical fitness/activity, health
care utilization, and the consequences of the irregular medical care received by some poor school-aged
children (Fattore and Mason 2018; Newacheck and Hallfon 1988). A number of health risks, such as poor
nutrition, low birth weight, and accidental injuries, have detrimental effects on children’s school
performance. For example, children born at very low birth weight are twice as likely to repeat a grade in
school and three and a half times more likely to require special education services as children born at
normal birth weight (McCormick, Gortmaker, and Sobol 1990; Newman 1990).
While originally the study intended to collect information on children's height and weight from parents,
NCES later decided to directly measure height and weight of children in the study's subsample in all
spring rounds. A health risk for children is being overweight. The prevalence of overweight U.S. children
since 1980 has increased sharply (Federal Interagency Forum on Child and Family Statistics 2007). In
fact, using a nationally representative sample, Skinner, Ravanbakht, Skelton, Perrin, and Armstrong
(2018) found that 32.8 percent of 6- to 8-year-old children and 35.6 percent of 9- to 11-year-old children
were identifiedclassified as overweight based on CDC guidelines. Research based on prior
administrations of ECLS program kindergarten cohort studies (i.e., the ECLS-K and ECLS-K:2011)
confirms the increase in the prevalence of obesity. From the 1998–99ECLS-K study, when children
entered kindergarten in the school year 1998–99 approximately 12 percent were classified as obese by
their body mass index (BMI). Twelve years later, from the 2010–11ECLS-K:2011 study, the percentage
of children starting school classified as obese was approximately 15 percent (Cunningham, Hardy, Jones,
Ng, and Kramer 2022). Health risk factors associated with being overweight or obese are high blood
pressure, asthma, diabetes, stroke, and heart disease. One ECLS-K study (Judge and Jahns 2007) found
that while overweight third- graders did not have more academic problems than normal-weight third
graders, overweight girls in the third grade had less self-control and more problem behaviors such as
arguing and fighting (called “externalizing” behaviors) and sadness or loneliness (called “internalizing”
behaviors) than normal-weight girls.
However, immediate consequences of being overweight are often psychosocial (Federal Interagency
Forum on Child and Family Statistics 2007). An elevated body mass index (BMI) can have a significant
impact on test scores and school success. Girls who became overweight between kindergarten and the end
of grade 3 were significantly more likely to demonstrate a reduction in test scores, teacher ratings of
social-behavioral outcomes, and approaches to learning at the end of the third grade (Datar and Sturm
2006). Particularly in girls, appearance and weight gain are linked with perceptions of self-worth (Harter
1999). The importance of continuing to study the relationships between weight and academic

C-17

performance within the ECLS-K:2024 is seen in the mixed findings for this relationship shown in a
systematic review, indicating more work in this area needs to be done (Santana, Hill, Azevedo,
Gunnarsdottir, and Prado 2017).
The ECLS-K:2024 will collect the following data addressing children’s current and retrospective health
status:
•

Birth weight (fall and spring kindergarten);

•

Whether child was born at term, preterm, or post-term (fall and spring kindergarten);

•

Breastfeeding history (fall kindergarten);

•

Whether child was part of a multiple birth (fall and spring kindergarten);

•

Complications at birth (fall kindergarten);

•

Health care utilization during the pandemic;

•

History of receiving early intervention (fall kindergarten);

•

Current receipt of services through an IFSP, IEP, or 504 plan (fall kindergarten);

•

Ear infection history (fall and spring kindergarten);

•

Treatments used for ear infections (fall and spring kindergarten);

•

Communication problems (spring kindergarten);

•

Vision and hearing problems (spring kindergarten);

•

Glasses, hearing aids, cochlear implants (spring kindergarten);

•

Diagnoses of disabilities and health conditions (spring kindergarten);

•

Prescription medications (spring kindergarten);

•

General health status (fall and spring kindergarten);

•

Routine health and dental care (spring kindergarten);

•

Health insurance coverage (spring kindergarten);

•

Exercise/physical activities (spring kindergarten); and

•

Services for disabilities (spring kindergarten).

Parent’s Psychological Well-Being and Health
Current maternalMaternal depression is related to mothers’ reports of children’s internalizing problems
and children’s own report of depressive symptoms (Tompson et al. 2010). Parents who are depressed or
highly stressed are less likely to provide emotional support to their children and more likely to employ
harsh disciplinary practices (Puckering 1989; Moore et al. 1995). Maternal emotional distress is
associated with a lower frequency of positive behavior (e.g., reduced maternal nurturance) toward
children which can lead to children’s feelings of depression and anxiety (McLoyd and Wilson 1991).
These parenting styles are consistently associated with poorer child outcomes. Findings from the spring of
kindergarten round of the ECLS-K showed that 6.4 percent of children had mothers who indicated they
had symptoms of depression, with more mothers in lower income families reporting symptoms than those
in higher income families (Moore et al. 2006).

C-18

In addition, there are other life stressors experienced by parents (e.g., economic concerns, work stress,
discrimination, health, relationships, and concerns due to the coronavirus pandemic) that may affect
children. A report from the American Psychological Association (2017) showed an increase in the
number of Americans who reported at least one symptom of stress in the past month. About a third of
adults reported feeling tired, irritable, or angry, and nervous or anxious as symptoms of stress (American
Psychological Association 2017). Parents with more stress may show less positive and more negative
emotions with their children (Deater-Deckard, Li, and Bell 2016) and children may recognize that parents
are stressed (American Psychological Association 2010). An earlier report from the American
Psychological Association (2010) found that almost half of children reported feeling sad when their
parent was stressed or worried, and a third recognized that their parents were stressed when they yelled.
Children also recognized signs of stress in their parents such as being too busy to spend time with them
and arguing with family members (American Psychological Association 2010). Discrimination is also
notable factor contributing to family stress (Shonkoff, Slopen, and Williams 2020; Iruka et al. 2022). Due
to the continuing coronavirus pandemic, adults may be particularly stressed because of employment,
economic, and health concerns. According to the Household Pulse Survey by the U.S. Census Bureau,
almost a third of adults (29.7 percent) reported feeling nervous or anxious, about a fifth of adults (22.8
percent) reported not being able to stop worrying, and about a fifth (18.6 percent) reported feeling down
more than half the days in the previous week or almost every day (Callen 2020).
The parent survey will include questions about parent’s psychological and physical health including:
•

Depression and subjective well-being (spring kindergarten);

•

Respondent’s general health status (spring kindergarten);

•

Family health limitations (spring kindergarten);

•

Discrimination (spring kindergarten);

•

Overall life stress (spring kindergarten); and

•

Increase in stress due to the coronavirus pandemic (fall kindergarten).

Peer Victimization
About 6 percent of children in the third grade in the ECLS-K:2011 were reported to have done one of the
actions measured as peer victimization in the study (teased, made fun of, or called other students names;
told lies or untrue stories about other children; frequently pushed, shoved, slapped, hit, or kicked other
students; or frequently excluded other students from play on purpose) (Federal Interagency Forum on
Child and Family Statistics 2017). In the ECLS-K:2011, parents were asked about their child’s peer
victimization starting in the third grade. In the ECLS-K:2024, these questions will be asked of parents of
children in kindergarten to explore how early these behaviors begin.
Other research shows that children with disabilities were two times as likely to be either a victim or
victimize others as children without disabilities (Rose and Espelage 2012). Findings from the ECLS-K
showed that eighth graders with disabilities who were victimized at school watched more television than
those without disabilities (Kremer and Kremer 2019). The study also found that test scores in reading
were negatively related to television watching. In the ECLS-K:2024, data on children’s disabilities,
engagement with media/watching shows, and assessment scores could be used together to understand
associations with peer victimization.

C-19

The ECLS-K:2024 will not collect data from parents about peer victimization in spring kindergarten, but
may the study is collecting these data in the first grade.
Food Sufficiency and Food Consumption
Adequate nutrition is critical for children’s growth and development. According to Coleman-Jensen et al.
(2019), 86.1 percent of families with children were food secure with reliable and consistent access to food
in 2018. The remainder of the families with children (13.9 percent) experienced food insecurity at some
point in the past year. Children in families with low income levels or who are below the poverty level,
children of adolescent mothers, and children whose parents are receiving welfare may be at risk of
undernourishment. Families’ economic status is significantly associated with food insecurity and food
insecurity is associated with children’s health and behavior difficulties (Dunifon and Kowaleski-Jones
2003; Kimbro and Denney 2015). For example, using ECLS-K:2011 data, Kimbro and Denney (2015)
found that transitions in and out of food insecurity were related to children’s health, self-control, social
skills, and externalizing behaviors. The food sufficiency and food consumption items in the ECLSK:2024 are from a well-established measure used by the USDA that was also used in the ECLS-K:2011 to
describe the level of food security or insecurity in the household.
The ECLS-K:2024 will include items about adult and child food security that ask about:
•

Ability to purchase food sufficient for family needs (spring kindergarten); and

•

Frequency that adults and children in the household do not have sufficient food (spring
kindergarten).

Parent Education and Human Capital
Parents’ education—especially mothers’ education—has a strong relationship with children’s cognitive
abilities at the beginning of kindergarten (U.S. Department of Education 2000; Lee and Burkam 2002)
and as children progress through school (Rathbun and West 2004). In the ECLS-K:2011 compared to the
ECLS-K, 35 percent of mothers of children in kindergarten had a bachelor’s degree or higher compared to
24 percent of mothers in the ECLS-K (Engel et al. 2016). Studies have shown that maternal education is a
strong predictor of the amount of time mothers spend playing with children, teaching them, and taking
them on outings (Hill and Stafford 1980) as well as the time spent engaging in high quality home literacy
experiences (Roberts, Jurgens, and Burchinal 2005; Storch and Whitehurst 2001). Maternal education
may also be related to the effect of the mother’s and father’s contributions to preschool children’s
learning prior to school entry. Foster et al. (2016) found that both mothers and fathers make contributions
to preschool children’s home learning environments that are related to assessments of children’s early
academic skills. Mothers’ contributions to children’s home learning environment were a significant
predictor of children’s academic skills when mothers have a bachelor’s degree or higher, whereas fathers’
contributions are most related to academic skills for children whose mothers have less than a bachelor’s
degree (Foster et al. 2016). Lower parent education has also been related to children’s externalizing
problems and maternal depression (Moore et al. 2006). Children whose parents do not have a high school
degree are also more likely to have a lower birthweight, have health problems, and be less prepared for
entering school than children whose parents have a high school degree or higher (Annie E. Casey
Foundation 2019).
Educational attainment data will be collected for up to twofour parent figures in the household. The
following data will be collected:
•

Diplomas or degrees parent has obtained (fall and spring kindergarten); and

•

Parents’ current school attendance (spring kindergarten).

C-20

Parent Employment
Parental employment status affects the amount of material resources available to the child (Jackson,
Bentler, and Franke 2006). Research from the Household Pulse Survey by the U.S. Census Bureau
indicates that adults in households with children were more likely to have experienced loss of
employment income than adults in households without children since the coronavirus pandemic started.
Fifty-five percent of households with children had an adult lose income from employment (Monte 2020).
Secure employment (defined as one or both parents being employed full time) is related to the economic
well-being of families; access to health insurance; and children’s health, academic, and socioemotional
development (Federal Interagency Forum on Child and Family Statistics 2019). Meta-analyses of several
studies document that socioeconomic status (parent occupation and education) is positively associated
with the quality of stimulation that parents provide their children (Gottfried 1984). The type of
employment a parent has may also be related to children’s outcomes. In an analysis of ECLS-K data,
Bowden et al. (2018) found that students in third through eighth grades with parents in a STEM (science,
technology, engineering, and math) field performed better on math assessments than children whose
parents were not in a STEM field. Fathers having an occupation in a STEM field was related to the
mathematics assessment scores of both male and female children, while mothers having an occupation in
a STEM field was only related to mathematics scores of female children but not male children.
One type of employment that is being examined in the ECLS-K:2024 is a family’s employment in the
military. Children in military families often experience frequent changes in schools as their parent(s)
receive new stations for their duties and long periods of absence by one or both parents as they are
deployed. Therefore, this is an important factor to consider when investigating children’s academic and
developmental outcomes.
Parent employment data will be collected for up to two parent figures in the household. The following
data will be collected:
•

Parents’ current employment (spring kindergarten);

•

Occupation (spring kindergarten);

•

Looking for work (spring kindergarten);

•

Employment and education changes as a result of the coronavirus pandemic (spring kindergarten);

•

Active duty military service (spring kindergarten); and

•

Family hardship (spring kindergarten).

Welfare and Other Public TransfersAssistance
Engel et al. (2016) found that 26 percent of children in the ECLS-K:2011 received food stamps while 6
percent received Temporary Assistance to Needy Families (TANF). Receipt of welfare benefits,
particularly if receipt is long term, reflects a high level of economic deprivation and generally low human
capital on the part of the mother (Zill et al. 1991; Bane and Ellwood 1983). McLoyd and Wilson (1991)
found that poor single mothers were substantially more likely to be depressed and to provide a
nonstimulating environment to their children ages 10 to 17. Subsequently, children of welfare-receiving
families demonstrate poorer outcomes across a variety of domains, compared to more advantaged
children (Saitadze 2021; Moore et al. 1993). However, for poor children, the receipt of associated benefits
such as Food Stamps, Women, Infants, and Children (WIC), and participation in the Federal school lunch
program should have positive implications for their physical health whereas gaps in coverage for these
programs can have negative effects on children. Using ECLS-K:2011 data, Arteaga, Heflin, and Parsons
(2019) found that the length of the gap between when children were no longer eligible to receive WIC at

C-21

60 months old and when they become eligible for participation in the Federal school lunch program at
kindergarten entry was related to negative effects on children’s reading assessment scores. Although,
although these effects faded for children in full-day kindergarten by the spring of the school year, they
illustrate the importance of nutritional assistance programs for children.
Children whose parents are not employed may be particularly disadvantaged in terms of the welfare
programs available. Shaeffer and Edin (2018) reported that the number of children in households who
received food stamps, or the Supplemental Nutrition Assistance Program (SNAP) and no other source of
income was four times higher in 2015 (1.3 million) compared to 1995 (289,000). As summarized by
Shaeffer and Edin (2018), for parents who are employed, aid to families is available in the form of tax
credits and greater eligibility for SNAP, but for parents who are not employed welfare assistance has
decreased and moved away from cash to in-kind benefits. With little or no cash assistance, some parents
who are unemployed have no additional income.
Since March 2020, there have been government efforts to help families affected by the coronavirus
pandemic. On March 18, 2020, the Families First Coronavirus Response Act (H.R. 6201) was enacted to
provide unemployment benefits and free- and reduced-price school meals for eligible children whose
schools were closed due to the coronavirus (Moss et al. 2020). On March 27, 2020, the Coronavirus Aid,
Relief, and Economic Security Act (CARES Act) (H.R. 748) was signed into law to support small
businesses and provide payments to eligible persons (U.S. Department of the Treasury 2020). States are
using funds from these acts to support families. For example, many states are providing money to families
to buy children’s food through the Pandemic Electronic Benefits Transfer (P-EBT) program when schools
are closed for 5 or more consecutive days (U.S. Department of Agriculture 2020). In 2021, the American
Rescue Plan Act of 2021 (H.R. 1319) was enacted, providing economic impact payments, child tax
credits, state and local fiscal recovery fund, capital projects fund, homeowner assistance fund, emergency
rental assistance, state small business credit initiative, employee retention credit and paid leave credit
programs, and unemployment compensation (U.S. Department of Treasury 2021). The bill provides
continued funding for nutritional programs, including the Supplemental Nutrition Assistance program
(SNAP, formerly known as food stamps) (U.S. Department of Agriculture 2021).
In the ECLS-K:2024, parents will be asked to provide information on the following:
•

Receipt of benefits from the Special Supplemental Food Program for Women, Infants, and
Children, or WIC (spring kindergarten);

•

Receipt of TANF since child’s birth and in last 12 months (spring kindergarten);

•

Receipt of Food Stamps, also called SNAP (the Supplemental Nutrition Assistance Program), or
food benefits on EBT (Electronic Benefit Transfer) during past 12 months (spring kindergarten);
and

•

Participation in Federal School Lunch or Breakfast Program (spring kindergarten).

Parent Family Income and Assets
Family income affects the family’s material standard of living, neighborhood and housing quality,
opportunities for stimulating recreation and cultural experiences, and the stress and psychological wellbeing of the parents. In the past 20 years, there has been increasing income inequality between the
wealthy and the poor and these gaps have been widening since the Great Recession (Engel et al. 2016).
Engel et al. (2016) compared children entering kindergarten in 1998 in the ECLS-K and in 2010 in the
ECLS-K:2011 and found that children from low-income families were more disadvantaged in 2010 than
in 1998 in multiple areas of well-being including an increase in receipt of food stamps and lower maternal
unemploymentemployment. In addition, findings from this study showed that the percent of

C-22

kindergartners whose families had incomes below the Federal poverty level increased from 22 percent in
1998 to 24 percent in 2010.
Children’s academic and behavior outcomes have been related to household income. Children from more
economically advantaged households tend to be more successful in the primary grades compared to their
less advantaged peers (Alexander and Entwisle 1988). Any behavior and learning problems the child
exhibits in the early grades are more likely to persist for children from economically disadvantaged
families than for children in families with more financial resources (Ackerman, Brown, and Izard 2003).
Reardon and Portilla (2016) compared data from the ECLS-K and the ECLS-K:2011 and found that while
school readiness gaps narrowed between low- and high-income kindergartners, the income gap was over
one standard deviation for children’s reading and math skills and about a half a standard deviation for
children’s behavior. One area of concern is the impact of income volatility on children’s development and
adjustment to school. Duncan (1991) has found that many households with children under 5 experience
extreme ups and downs in the amount of money available to the family, especially as a result of divorce
or remarriage. Income is not a stable background characteristic but rather a dynamic force that will be
measured longitudinally in the parent surveys in the ECLS-K:2024.
Parents will be asked to provide information on the following:
•

Total family income and assets for the year (spring kindergarten); and

•

Tuition paid for the child’s education (fall kindergarten).

Child Mobility, Closing, and Tracking Questions
In order to locate parents for future parent surveys, questions will be asked about whether parents plan to
move in the next year as well as questions to collect parent contact information. This information will
either be collected in the survey or on the MyECLS website.
The parent surveys will include questions about the following:
•

Plans to move (fall kindergarten);

•

Location and name of child’s next school (fall kindergarten); and

•

Contact persons to locate the parent (fall and spring kindergarten).

C.2.2.2

Constructs for the Abbreviated Parent Survey

The abbreviated survey collects important explanatorykey information about the child’s household often
used by researchers in exploring the variation in children’s development, knowledge, and skills. In addition
to select demographic characteristics, the abbreviated parent survey also includes important questions about
the child’s transition to kindergarten, the home educational environment, and family experiences with the
coronavirus pandemic.
Construct justifications are presented above in section C.2.2.1. The abbreviated survey includes questions
about the following:
•
•
•

School Choice
o How the respondent learned about the school where the child attends kindergarten
Parent Involvement with the Child’s Education
o Transition to kindergarten activities
Parent Beliefs and Expectations

C-23

o Family concerns about the child’s education given the coronavirus pandemic (i.e., how
•
•
•
•
•
•

C.2.3

confident parents are that their child learned the skills they expected them to learn)
Family structure
o Household size
Home language
o Primary language spoken in the home
Home Environment, Activities, and Cognitive Stimulation
o Home learning activities (i.e., how frequently a family member engages in different
learning activities with the child)
Early Care and Education Arrangements
o Participation in early care and education the year before kindergarten
Parent Education and Human Capital
o Highest level of education
Parent Family Income and Assets
o Household income

Spring First-Grade Parent Survey: Construct Coverage

Most constructs listed below for the first-grade parent survey are the same as those in the kindergarten
parent survey (e.g., child’s health and well-being) although some topics within constructs vary (e.g.,
parents are asked about the child’s birth weight in kindergarten, but are asked about whether the child has
asthma in the first-grade round). Literature reviews for constructs that are the same as those in
kindergarten are not duplicated in this section.
Child Characteristics (if missing from previous rounds)
•

Child’s gender;

•

Child’s date of birth; and

•

Child’s race/ethnicity.

Parent’s Involvement with the Child’s Education
•

Parent’s choice of school for the child;

•

School attendance (for homeschooled children);

•

School-initiated contact with parents about behavior problems;

•

Child had in- or out-of-school suspensions or expulsions;

•

Parent report of the child’s grades;

•

How many times the child has been late for school;

•

Parent attendance at parent-teacher conferences and meetings;

•

Parent participation in school activities;

•

School practices to communicate with parents and encourage involvement;

•

School practices to provide an equal and culturally responsive environment;

•

Whether school provides translated materials;

•

Whether school methods of communication are in the respondent’s native language;

C-24

•

Parent satisfaction with the school;

•

Barriers to involvement with the school;

•

Parent satisfaction with the school;

•

How many times the child has been late for school;

•

Perception of the amount of homework;

•

How often parent or someone else helps the child with homework; and

•

How often parent or someone else checked that the child completed homework.

School Avoidance
•

The child’s school avoidance.

Family Structure
•

Number of household members age 18 and older;

•

Number of household members age 17 and younger;

•

Parents or guardians in the household;

•

Family relationship of key parent figures to the child (e.g., biological, adopted);

•

Gender, age, and race/ethnicity of key parent figures;

•

Number of household members who are siblings to the child;

•

Number of household members who are grandparents to the child;

•

Marital status of the primary caretakers; and

•

Family structure change and loss (e.g., remarriage, divorce, and death).

Parent Characteristics
•

Biological parent’s gender, age, and race/ethnicity; and

•

Parent’s vital status (collected by asking about contact with a biological/adoptive parent who does
not live in the household or collected when a parent/parental figure identified in a previous round
is no longer in the household).

Home Environment, Activities, and Cognitive Stimulation
•

Literacy materials in the home;

•

Frequency of reading activities with the child;

•

Reading by the child;

•

Math activities;

•

Availability and use of a home computer/digital device;

•

How often the child uses a home computer/digital device for educational purposes;

•

Amount of time the child plays video games;

•

Tutoring;

C-25

•

Children’s organized activities (sports, music, art, etc.);

•

Frequency with which the family eats meals together; and

•

Hours of child sleep and whether child has regular bedtime;.

•

Outside play and perception of how safe it is for children to play outside; and

•

Library use.

Neighborhood
•

Neighborhood safety.

Child’s Social Skills, Problem Behaviors, and Approaches Toward Learning
•

Approaches toward learning;

•

Self-control;

•

Social interaction;

•

Externalizing problem behaviors: Impulsive/Overactive;

•

Internalizing problem behaviors: Sad/Lonely;

•

Affective empathy; and

•

Emotional socialization.

Children’s Executive Function
•

Attention focusing; and

•

Inhibitory control.

Critical Family Processes
•

Social support; and.

•

Marital satisfaction.

Early Care and Education (ECE) Arrangements
•

Participation in ECE, by type of arrangement (e.g., relative, nonrelative, and center-based);

•

Number of ECE arrangements, by type of arrangement (e.g., relative, nonrelative, and centerbased);; and

•

Time the child spends in ECE arrangements; and.

•

Cost of ECE.

Parental Discipline, Warmth, and Emotional Supportiveness
•

Parenting stress;

•

Parent-child communication; and

•

Inconsistent discipline.

Involvement of Nonresident Parent
•

Whether child has biological or adoptive parents who are not currently living in the household;

C-26

•

Biological and adoptive parents’ vital status;

•

Time since last contact (either in person or by telephone, email, text, etc.) with biological/adoptive
parents no longer living in household; and

•

Frequency of contact in the last four weeks that was not in person (e.g., by telephone, email, text,
etc.) with biological/adoptive parents no longer living in the household.

Child’s Health and Well-Being
•

Routine health and dental;

•

Asthma;

•

Health insurance coverage;

•

Activity level;

•

History of receiving early intervention;

•

Current receipt of services through an IFSP, IEP, or 504 plan;

•

Ear infection history;

•

Ear infections since kindergarten;

•

Treatments used for ear infections;

•

Asthma;

•

Child’s independence and ability to take care of him/herself;

•

Behavioral and attention problems;

•

Learning problems;

•

Coordination problems;

•

Diagnosis from a professional;

•

Activity level;

•

Emotional or psychological difficulties;

•

Communication problems;

•

Vision and hearing problems;

•

Glasses, hearing aids, cochlear implants;

•

Diagnoses of disabilities and health conditions;

•

Prescription medications;

•

General health status;

•

Routine healthTherapy services; and dental care;

•

Health insurance coverage;

•

Exercise/physical activities;

•

Services for disabilities; and

C-27

•

Parent report of child’s height and weight.

•

Participation in and satisfaction with special education program.

Peer Victimization
•

Problems with other children

Parent’s Psychological Well-Being and Health
•

Respondent’s general health status; and

•

Overall life stress;.

•

Increase in stress due to the coronavirus pandemic; and

•

Discrimination.

Food Sufficiency and Food Consumption
•

Ability to purchase food sufficient for family needs;

•

Frequency that adults and children in the household do not have sufficient food, and

•

Obtaining free groceries or meals because of money problems related to the coronavirus pandemic.

Historical Household Information and Involvement of Nonresident Parent
•

Whether child has biological or adoptive parents who are not currently living in the household;

•

Biological and adoptive parents’ vital status;

•

Time since last contact (either in person or by telephone, email, text, etc.) with biological/adoptive
parents no longer living in household; and

•

Frequency of contact in the last four weeks that was not in person (e.g., by telephone, email, text,
etc.) with biological/adoptive parents no longer living in the household.

Parent Education and Human Capital
•

Diplomas or degrees parent has obtained; and

•

Parents’ current school attendance.

Parent Employment
•

Parents’ current employment;

•

Looking for work;

•

Availability for work;

•

Occupation and industry; and

•

Active duty military service.

Welfare and Other Public TransfersAssistance
•

Participation in the Federal School Lunch or Breakfast Program.

ParentFamily Income and Assets
•

Total family income for the year;

C-28

•

Use of a government voucher to attend school; and

•

Whether the family has had to leave their home because they could not afford it.

Child Mobility, Closing, and Tracking Questions
•

Number of places lived;

•

Length of time at current residence;

•

Whether and why the family moved;

•

Contact persons to locate the parent;

•

Email address;

•

Telephone number; and

•

Permission to text.

C.3

Teacher Surveys

The ECLS-K:2024 plans to survey teachers in all rounds of ECLS-K:2024 data collection. Teachers will
be asked to complete surveys in the following rounds of data collection: fall kindergarten, spring
kindergarten, spring first grade, spring third grade, and spring fifth grade. This document will only
discuss the fall kindergarten, spring kindergarten, and spring first-grade data collections.
In the study’s initial rounds, the ECLS-K:2024 will collect information from the teachers of the sampled
children in fall kindergarten, spring kindergarten, and spring first grade. The survey will collect
information about the teacher’s classroom, teaching methods, views on teaching, professional training,
and professional background. The primary purpose of these data is to help describe the child’s classroom
experiences which may relate to children’s social and academic development. The ECLS-K:2024 will
also conduct a census of all kindergarten teachers in the sampled ECLS-K:2024 schools to produce
nationally representative teacher-level estimates. In the nationally representative sample of teachers,
teachers will be asked to complete the same teacher-level surveys as those completed by teachers of
sampled children.
In addition, teachers will be asked to provide information on the study students who are in their classes,
completing one survey for each ECLS-K:2024 child. The ECLS-K:2024 assessment battery provides an
objective assessment of academic outcomes for the nationally representative sample of children. Teachers
can provide another perspective, albeit a less objective perspective, on children’s abilities and behavior
because they spend a great deal of time with the children under far more routine conditions.
Because the ECLS-K:2024 collects a very broad range of variables and collects that information
longitudinally, it is well-suited to study simultaneously the relationships of several variables and thus
assess the relative importance of particular schooling variables compared to other schooling and family
background variables on important outcomes.
The ECLS-K:2024 classroom component will ask teachers to provide information on classroom and
student characteristics, instructional practices, and their teaching qualifications and background. As noted
above, in the kindergarten year there will be a nationally representative sample of teachers.

C-29

C.3.1

Kindergarten and First-Grade Teacher Surveys: Research Questions

Research questions related to the ECLS-K:2024 fall and spring kindergarten and spring first-grade teacher
surveys items are shown below.
T-RQ1. How do instructional practices, content coverage, and classroom resources, and methods of
providing feedback differ across classrooms or schools? What are the consequences of those
differences for children’s academic and social development?
T-RQ2. How does diversity in the classroom regarding age, race/ethnicity, gender, disabilities, and
number of kindergarten repeaters relate to other classroom characteristics? How do these classlevel characteristics interact with children’s own characteristics in the development of academic
and social skills?
T-RQ3. How do teachers and schools handle the diversity of children’s skills? How are children
who receive specialized programs or services (e.g., English language learners, gifted and talented
students, students with IEPs) taught? How might instructional differences for these students relate
to academic and social outcomes?
T-RQ4. Do teachers’ characteristics including sociodemographic characteristics, views on school
“readiness,” sense of efficacy, job satisfaction, perceptions of school climate, their educational
background, certifications, including participation in alternate certification programs, or teaching
experience influence children’s outcomes, on average or in interaction with children’s
sociodemographic backgrounds?
T-RQ5. Do supports provided to teachers through mentorship and professional learning
opportunities on evidence-based practices influence teachers’ decision to remain in teaching?
T-RQ6. Do teachers’ practices to involve parents result in higher levels of parent involvement?
T-RQ7. How do teacher’s relationships with individual students differ? What are the consequences
of those differences for children’s academic and social development?
T-RQ8. What academic and socioemotional skills and behaviors (including activity level) do
teachers report children having as they enter and go through school? Do these vary by family social
background characteristics? How do these skills and behaviors change over time? How do
cognitive and socioemotional skills covary?
T-RQ9. To what extent do teachers and other school staff use assessments to monitor students’
progress on specific skills and identify those in need of interventions? What kinds of interventions
are provided for struggling students and how much staff support and parent communication are
there for these efforts?

C.3.2

Kindergarten Teacher Surveys: Construct Coverage

The fall and spring kindergarten teacher surveys in the ECLS-K:2024 are similar to the surveys used for
the ECLS-K:2011. Details are shown below.
Classroom and Student Characteristics
The first set of constructs included in the ECLS-K:2024 kindergarten teacher surveys concerns the
organizational features of the class. Whether the class is self-contained (one teacher teaching multiple
subjects to the same class of students all or most of the day) or is configured differently (e.g., team
teaching, departmentalized instruction, etc.) influences scheduling and curriculum coverage. Full-day
kindergarten has become more prevalent over time, with enrollment growing from 11 percent of
kindergartners in 1969 to 63 percent in 2002 (Ackerman, Barnett, and Robin 2005; Kauerz 2005) and 77
percent in 2018 (U.S. Department of Education 2020). Prior research tends to confirm that at the end of

C-30

the school year, children who attend full-day kindergarten programs make more progress in their early
reading skills than children who attend part-day programs (Cooper, Batts Allen, Pattall, and Dent 2010;
Fusaro 1997; Thompson and Sonnenschein 2016; Walston and West 2004). The total number of children
enrolled in a class is a widely used index of instructional quality at all levels of education. Class size is
usually considered important because of the constraints it places on teacher-child interactions. The time
available for individuation and small-group supervision is reduced as class size increases, and this is
widely believed to result in lower student achievement levels. Class size studies are quite prevelant but
findings on outcomes related to various class sizes are not consistent. While education researchers and
economists debate the benefits of broadscale class size reduction efforts relative to the high costs of
implementation, most seem to agree on the benefits of targeted class size reduction policies for select
subpopulations of students (Hanushek 2002; Krueger 2002; Rice 2002).
Additionaly, the demographic characteristics and ability-levels of the children in the class as a whole will
be collected to support analyses that consider how a child’s learning trajectory might be related to the
characteristics of their classmates, which may or may not be similar to their own.
The effort to educate all children in regular education programs presents challenges to teachers at all
levels of education. Special populations include those with physical and cognitive disabilities, as well as
ELL and gifted and talented children. The ECLS-K:2024 is well-positioned to collect information on how
these children are served and the consequences of treatment differences.
In light of the growing number of ELL children in the country (up to 10.1 percent or 5 million students in
the 2017-18 school year; Hussar et al. 2020), the ECLS-K:2024 has included many items for the teacher
about the instructional programs for ELL children beyond what was used in the ECLS-K. In a related
inquiry, using data from ECLS-K:2011, Sullivan, Houri, and Sadeh (2016) found that 27 percent of
kindergartners in the 2011 sample were from immigrant families. Additionally, another study using
ECLS-K:2011 data found that teachers reported higher perceived executive function skills in bilingual
children in comparison to monolingual children (Castillo, Khislavsky, Altman, and Gilger 2020).
The range of specific disabilities included under the special education label makes it particularly
important to find out how schools and teachers accommodate children with disabilities. As more schools
move toward inclusion of children with disabilities in regular classrooms, data evaluating the extent and
efficacy of these efforts need to be collected and evaluated. In fact, data indicate that the percent of
special education students spending at least 80 percent of their time in general classes has increased to 64
percent in 2018 compared to 47 percent in 2000 (U.S. Department of Education 2020). The ECLS-K:2024
also asks teachers about the numbers of children who are frequently tardy or absent and to rate the overall
behavior of their class.
In addition, these characteristics may be of specific interest as there may be variation related to the
coronavirus pandemic in 2020 and 2021. For example, research suggests there was a kindergarten
enrollment drop of off in fall 2020 (Bassok and Shapiro 2021, Council of Chief State School Officers 2021).
The downward enrollment may lead to an uptick in enrollment in fall 2021 or fall 2022 as families seek to
begin kindergarten education for their child. This may mean that children entering kindergarten in fall 2022,
fall 2023, and onward have different characteristics from prior cohorts of kindergartners. For example,
enrollment trends for children entering kindergarten might skew older than prior cohorts or a higher
percentage may have no prior formal early education experience (Hollingsworth and Attanasio 2021,
Council of Chief State School Officers 2021). In addition, the ECLS-K:2024 will collect information on
absenteeism, which may be especially relevant post pandemic.
Teachers will provide information about classroom and student characteristics including:
•

Class time (full/half day, hours per day, days per week);

C-31

•

Program type (regular kindergarten, 2-year kindergarten, transitional program, etc.);

•

Grade levels of classes the teacher teaches;

•

Class demographics: class size, age distribution, race-ethnicity distribution, gender distribution,
number repeating grade, percent experiencing homelessness or housing insecurity;

•

Number of students who enter or leave during the school year;

•

Students’ reading and mathematics skills upon kindergarten entry;

•

Number of language minority (LM) children and English-language learners (ELL) in the
classroom;

•

Number of children in the classroom receiving special services or in special programs (e.g., special
education services, a gifted and talented program, remedial services);

•

Number of students with IEPs or 504 plans;

•

Languages used in the classroom;

•

Instructional approach for English language learners;

•

Number of children above or below grade level in reading and mathematics;

•

Numbers of children with disabilities by disability type (e.g., autism, speech or language
impairments, emotional disturbance, intellectual disability, developmental delay, vision
impairment, hearing impairment); and

•

Number of children tardy or absent on an average day.

Instructional Activities and Curricular Focus
Several studies suggest demonstrate the importance of instructional approaches, for example teacherguided play, to promoting academic learning that large amountsrelationships between the amount of free
play and unstructured time are negatively related to children’s and cognitive and language development
(Danniels and Pyle 2018; Zosh et al. 2017; McCartney 1984; Ruopp et al. 1979).). In addition, Aa large
number of studies have emphasized the importance of “time on task” for student achievement
(Greenwood 1991; Greenwood, Arreaga-Mayer, and Carta 1994; Wang, Haertel, and Walberg 1990).
Children achieve more (as measured by achievement tests) in classrooms where a higher proportion of
time is spent in academic instruction and where they are engaged in their work with few interruptions or
few periods of unoccupied time (Crocker and Brooker 1986; Greenwood 1991; Powell 1992; Teddlie,
Kirby, and Stringfield 1989). In fact, over time, kindergarten has been found to have increased in its
academic focus. For example, using ECLS data from both the 1998 and 2011 kindergarten cohorts,
Bassok, Latham, and Rorem (2016) found that in comparison to the 1998 cohort, kindergarten teachers in
the 2011 cohort reported higher academic expectations for children, spent more time teaching literacy and
math content, and spent more time in teacher-directed instruction. Teachers also reported spending
substantially less time in their classrooms in other activities such as art, music, and child-selected
activities.
However, engaging in child-directed, imaginative play develops many social, emotional, and cognitive
competencies necessary for children’s school success including perseverance, patience, and the ability to
image the future (Singer and Singer 2006; Bergen and Fromberg 2009). Child development experts have
noted with concern that elementary school children have less time to engage in free play as some schools
reduce recess time in favor of more instructional time and that this trend may have unintended negative
academic consequences (e.g., Pellegrini and Bohn 2005; Bergen and Fromberg 2009) and physical

C-32

consequences (Datar and Strum 2004). Using ECLS-K data, Datar and Sturm found that only 16 percent
of schools had P.E. every day in kindergarten. Kindergartners spent almost an hour a week in P.E. class
(57 minutes), while first-graders on average spent 8.2 minutes more. The study showed that P.E.
programs helped girls who were overweight, or at risk for overweight, avoid becoming obese.
The research on scheduling and program organization suggests that programs that are carefully planned
and structured and offer a balance between adult-directed and child-initiated activities may provide the
highest quality environments for children (Hayes, Palmer, and Zaslow 1990). The Class Organization and
Resources section of the teacher survey includes items about time for free-play and recess which, in
conjunction with items about time for various subject matters and classroom activities, can provide data
which may be useful to investigate this issue for today’s kindergartners.
Teachers can use a variety of grouping arrangements, such as teacher directed whole-class, small-group,
and individualized instruction, as well as child-selected activities to provide instruction in kindergarten
classrooms. Whole-class activities emphasize uniformity over diversity of instruction (Lou et al. 1996).
During whole-class instruction, teachers provide each of their students with the same learning experience
by teaching the full group the same curriculum objective using the same instructional method.
In contrast, small-group instruction emphasizes diversity over uniformity of instruction. Small-group
arrangements can be created in a variety of ways, including self-selection, random assignment, or teacher
assignment based on students’ skill and achievement levels. Heterogeneous small group arrangements
may foster learning when higher performing students develop their explanatory skills by providing peer
tutoring for the lower-performing students in their group (Lou et al. 1996). On the other hand, when
students in small groups have a wide range of skills and abilities, group members may rely on the highestperforming student(s) to do most of the work, a strategy that results in less group interaction and less
academic engagement for some members of the group.
In contrast to heterogeneous grouping, teachers may use within-class ability or achievement grouping to
place students into smaller groups stratified by achievement, skill, or ability levels (Entwisle 1995;
Karweit 1988; Lou et al. 1996; McCoach, O’Connell, and Levitt 2006; Slavin 1987). Compared with
whole-class instruction, achievement grouping allows teachers to reduce heterogeneity and target
instruction to match students’ current level of knowledge and skills. Children’s reading achievement
group placement can determine the amount and type of instruction children receive, it can influence the
group process through the amount of disruptions and interruptions, and it can affect teachers’ and parents’
views of children (Entwisle 1995; Slavin 1987). Opponents of achievement grouping express concerns
that teachers may develop lower expectations for children in low achievement groups, that children in low
achievement groups will fall further behind their higher-achieving classmates and never catch up
academically, and that children’s self-esteem will be adversely impacted (McCoach, O’Connell, and
Levitt 2006).
In addition to whole-class and small-group instruction, teachers may provide individualized instruction to
children or may allow them time to select their own classroom activities. During teacher-directed
individual activities, teachers can work one-on-one with children to present new material or provide
remedial assistance (Morrow, Strickland, and Woo 1999). Alternatively, teachers can provide children
with time to self-select classroom activities, such as learning or play centers. Developmental, wholelanguage based classrooms tend to encourage child-selected activities based on the premise that they
empower children to direct their own learning and choose activities in which they are interested (Xue and
Meisels 2004)

C-33

The following constructs are used in the ECLS-K:2024 instruments to characterize teachers’ curricular
focus and how they organize their classes for instruction:
•

Class activities outside of the regular class (library, lunch, and recess);

•

Use of class time by subject area;

•

Instructional time spent handling disruptive behavior;

•

Culturally responsive teaching practices (e.g., display pictures reflecting all students’ background,
written communication to families in their native language, use of alternative formats of
communication, screening materials for negative racial and ethnic stereotypes);

•

Class organization (teacher-directed and child-selected activities);

•

Use of achievement grouping, number of groups, and mobility between groups;

•

Transition activities into kindergarten;

•

Additional reading services;

•

Use of languages other than English in the classroom (e.g., instruction in reading/literature,
instruction in math, instructional support, directing student behavior, and conversation); and

•

Instructional activities with ELL children (assess/monitor language acquisition, assess literacy
skills, intensive skills work in small groups, and peer assisted settings); and ).

•

Use of homework.

Content Coverage for Language Arts, Mathematics, Science, and Social Studies Instruction
Early childhood experts recommend that children learn the following: the alphabetic principle, lettersound correspondence, phonemic segmentation of sounds in words, vocabulary, concepts of words,
rhyming patterns, decoding skills, writing skills, and relationships between oral and written language
(NAEYC 1998; Morrow, Strickland, and Woo 1999; Neuman 2002; Snow, Burns, and Griffin 1998).
Children also should learn the structural elements and organization of print (e.g., words, punctuation) and
become familiar with the forms and formats of books and other print resources. In addition, reading
experts recommend that teachers provide instruction in text comprehension that includes skills of retelling
stories, responding to questions about story content, and identifying elements of story structure (Morrow,
Strickland, and Woo 1999).
Researchers find positive relationships between children’s exposure to reading curriculum and their
reading achievement. A summary of research on effective reading instruction indicated that instruction on
phonemic awareness, word study, and decoding skills in kindergarten was positively associated with
children’s reading development (Neuman 2002). Snow and colleagues’ 1998 synthesis of research on
reading instructional practices stated that children who received instructional training in letter knowledge
and phonological awareness (i.e., knowledge that words are composed of smaller speech elements)
learned to read more quickly than those without such training. A study using ECLS-K data showed that
children’s gains in reading achievement over the kindergarten year were positively related to the
frequency that teachers provided instruction on letter-sound skills (e.g., alphabet and letter recognition,
rhyming words, letter-sound matching) and reading and writing skills (e.g., vocabulary, composing and
writing sentences, reading multi-syllable words, composing stories with a beginning, middle, and end,
and using capitalization and punctuation) (Guarino et al. 2006). On the other hand, the frequency of
instruction in comprehension strategies (e.g., identifying main parts of stories, making predictions based

C-34

on text, understanding common prepositions) was not significantly related to reading gains in
kindergarten.
The ECLS-K:2024 content coverage questions combine content that is included on the ECLS-K:2024
child assessment batteries with other skills that elementary school teachers cite as central to the
elementary school curriculum. The ECLS-K:2024 teacher survey measures what is taught, how often it is
taught, and how it is taught (i.e., using what materials and activities).
The following constructs measure students’ opportunities to learn in various academic subjects.
•

Time spent on specific activities and skills in reading/language arts and in mathematics; and

•

Topics taught in social studies and science.

Resources/Materials
Team teaching, where two teachers work together with a single class, and use of instructional aides allow
for greater individuation of instruction and personal attention. Characteristics of the aides (especially level
of fluency in English and educational background) are relevant for how well they can perform educational
tasks. The number of adults and the number of children have been combined in studies focusing on the
consequences of teacher-to-student ratios for classroom management and student outcomes.
In schools that are obliged to enroll more children than they were constructed to accommodate, class size
may cause serious problems. Similarly, classes are likely to vary in terms of the availability of
instructional materials and supplies. Because standards of adequacy for many resources depend on many
conditions, to the ECLS-K:2024 will ask the teachers about the degree to which they believe various
resources are adequately provided to their classes.
The following items are used to characterize a classroom in terms of the availability of adults in the
classroom and the adequacy and availability of physical space and materials:
•

Classroom aides (paid aides and volunteers); and

•

Availability, use, and adequacy of instructional materials.

Student Evaluation
The incentives for children to learn and behave properly in class consist of both formal and informal
arrangements. For children at the earliest ages, the incentives are mainly receipt of praise from adults and
recognition from peers, while sanctions consist primarily of disapproval. Formal arrangements include
grades, progress reports to parents, portfolios, and report cards. For these mechanisms, the most important
variables are the criteria for grading, the frequency of feedback, and whether constructive advice on how
to improve is included. Martínez, Stecher, and Borko (2009) used ECLS-K data and found third- and
fifth-grade teachers’ ratings of students’ mathematics achievement correlated strongly with the direct
assessments, however this relationship varied by certain classroom assessment practices which suggested
that teachers evaluate student performance relative to other students in the school.
One measureThe ECLS-K:2024 only includes the use of one child evaluation is included in the ECLSK:2024measure:
•
•

Use of standardized tests

Standardized Tests

C-35

Parent Involvement
Research has increasingly emphasized the importance of parental involvement in explaining differences
in student educational outcomes (Schneider and Coleman 1993; Hoover-Dempsey and Sandler 1997;
Gonzalez-DeHass, Willems, and Holbein 2005; Ma, Shen, Krenn, Hu, and Yuan, 2016). This is also true
for the growing population of Hispanic children in the United States. For example, a meta-analysis of 28
studies found a significant relationship between parental involvement and academic achievement for
kindergarten through fifth-grade students (Jeynes 2017). Constructs included in the ECLS-K:2024 in this
area include the following:
•

Communication with parents about children’s performance; and

•

Parent involvement in school activities (volunteering, attending meetings, other activities).

Collegial Relations and Opportunities for Professional Development
The importance of collegial relations among teachers and instructional leadership from the principal and
administration are two additional areas that have been studied in the literature with respect to mediated
student outcomes for decades (Edmonds 1979; Kilgore and Pendleton 1993; Bidwell and Bryk 1994;
Talbert and McLaughlin 1994; Wimberley 2011).
Many teachers receive in-service training designed to improve teaching techniques and content
knowledge. Although reliable information on the specific content of the programs would be difficult to
collect, the ECLS-K:2024 can find out about the kinds of in-service training in which teachers have
participated and the extent to which they consider that training useful.
In addition to needing time for professional development, teachers need time to plan and prepare their
daily lessons. Elementary teachers have traditionally had very limited planning time, a point of some
concern for some, as reform proposals call for additional work from teachers outside of their instructional
time. When that planning time is conducted collaboratively, it has been shown to relate positively to
student outcomes. For example, Goddard, Goddard, and Tschannen-Moran (2007) found that fourth
graders achieved higher scores in mathematics and reading when they attended schools categorized as
higher in teacher collaboration in a sample of more than 45 elementary schools.
In another example, Reeves, Pun, and Chung (2017) examined Trends in International Mathematics and
Science Study (TIMMS) data and found that teacher collaboration during lesson planning significantly
predicted student achievement. Additionally, when teachers spent time visiting other classrooms it
corresponded to higher job satisfaction ratings.
In addition to teacher time in quality training and planning experiences, school leadership has also been
found to relate to positive outcomes for teachers and students (Leithwood et al. 2004; Supovitz et al.
2010). For example, Waters, Marzano, and McNulty (2003) conducted a meta-analysis of 70 studies and
found that leadership characteristics such as knowledge of curriculum, instruction, and assessment all
significantly predicted student learning.
The following constructs measure collegial relations and opportunities for staff development:
•

Mentorship activities;

•

Frequency of meeting with other teachers and specialists; and

•

Professional learning activities on evidence-based practices.

C-36

Teachers’ Views on Teaching, School Climate, and Environment
Teachers’ satisfaction with the amount of autonomy afforded to them and the amount of support they feel
has a strong effect on their overall job commitment and interaction styles with children (Manlove 1993;
Rosenthal 1991; Webb and Lowther 1993). A teacher’s sense of professional efficacy is associated with
student outcomes. In the ECLS-K:2024, teachers’ autonomy, input into school policies, and sense of
efficacy will be measured. These can then be used to address questions having to do with how these relate
to teaching practices and ultimately to child outcomes, such as the following:
•

School climate;

•

Job satisfaction;

•

Teachers’ sense of efficacy; and

•

Views on transition into kindergarten activities and school “readiness.”

Teacher Background
Teacher demographics are mainly of interest in the context of fit with children’s backgrounds. Although
teacher race-ethnicity and gender have not been shown to make much difference to student achievement
generally, they may interact with student background variables to produce interesting results. Gershenson,
Holt, and Papageorge’s 2016 study on the relationship between student-teacher demographic mismatch
and teachers’ expectations for students found that student-teacher racial mismatch reduced teachers’
expectations for Black students.
Another teacher background variable of interest is teacher preparation and training. Although studies have
found substantial variation in teacher training at the preschool level, the differences tend to be smaller at
the elementary level. Moreover, the differences that are found on such conventional yardsticks as highest
degree earned and major field of study are at best weakly related to student cognitive outcomes (Hedges,
Laine, and Greenwald 1994). Nonetheless, these indicators continue to be used as bases for salary
differences and hiring decisions and items on these topics will be included in the ECLS-K:2024.
The teacher’s years of teaching experience is also a variable that is taken very seriously in schools but that
has only weak systematic relationships with student test scores (Hedges, Laine, and Greenwald 1994).
The following demographic, training, and experience variables will be collected as part of the ECLSK:2024:
•

Teacher’s gender, age, and race/ethnicity;

•

Teaching experience, by school and grade;

•

Teacher’s education, including degrees and credentials/licenses;

•

Type of teaching certification held;

•

Type of certification program completed;

•

National Board certification; and

•

Intention to remain in teaching.

Child-Specific: Enrollment Information
The teacher will provide child-specific information about important characteristics of the child’s:
•

Kindergarten program type;

C-37

•

Current grade level;

•

Child’s retention status;

•

Length of time child has been enrolled in the classroom;

•

Number of school absences;

•

Teacher’s subject-area teaching assignment for child; and

•

Kindergarten transition.

Child-Specific: Evaluation of Child’s Skills, Knowledge, and Behavior
Teachers’ reports of children’s academic skills augment the information obtained in the direct cognitive
assessments. Teachers provide ratings of the skills the child demonstrates in the classroom in
literacy/reading, mathematics, and science. These cover many constructs that are not directly assessed
including writing behaviors in kindergarten and science skills. These constructs were assessed using
teacher reports in the ECLS-K and ECLS-K:2011, although the content of some of the items was updated
to reflect current curricular focus. Teachers will also rate children’s early language skills (e.g., how well
they communicate ideas clearly, ask for information, initiate and maintain conversations, etc.). These
teacher ratings of how frequently children exhibit specific early language skills are new to the ECLSK:2024. These ratings are based on teacher observations of the child’s functional use of language in the
natural classroom setting and will supplement findings from the direct child assessments and expand
ratings in the area of early language skills.
Teachers will also rate children in their classroom on social skills and classroom behaviors, including
children’s ability to regulate their behavior in classroom contexts, problem behaviors (e.g., fighting,
arguing, anger, depression, low self-esteem, impulsiveness, etc.), and learning dispositions or “approaches
to learning” (e.g., curiosity, self-direction, and organization). The approaches to learning items and the
problem behavior items are Two important sets of socioemotional behaviors items that have been
incorporated into a wide variety of research done with the ECLS-K and ECLS-K:2011 data are the
approaches to learning items and the problem behavior items. For example, using data from the ECLS-K,
Ready et al. (2005) found that girls had an advantage in literacy/reading skills in kindergarten and their
more positive approaches to learning explained almost two-thirds of the advantage. Externalizing
behavior problems are more prevalent in boys, but this did little to explain the gender gap in reading
literacy development in kindergarten. Using data from the ECLS-K:2011, researchers have found
significant relationships between approaches to learning and several other measures (e.g., ability grouping
in kindergarten through third grade, Catsambis and Buttaro 2012; reading and mathematics achievement
in grades 3 and 5, (Bodovski and Youn 2011, Li-Grining et al. 2010; and bilingualism, Han 2010)). Lim
and Kim (2011) found that social behaviors measured in kindergarten were crucial to reading skill
development through fifth grade. Morgan et al. (2008) confirmed their hypothesis that behavior problems
and poor reading skills are risk factors for each other. That is, behavior problems in first grade predicted
poor reading skills in third grade, and poor reading skills in first grade predicted behavior problems in
third grade. Teacher ratings of social skills and classroom behaviors for the ECLS-K:2024 overlap with
what was collected in the ECLS-K and ECLS-K:2011, but with some new updated items. The ECLSK:2024 will also include a new measure of classroom behavioral self-regulation that assesses the
behavioral aspects of self-regulation that are important for success in classroom contexts. (e.g., takes the
time to do their best work). The classroom behavioral regulation items are new to the ECLS-K:2024.
The ECLS-K:2024 will also include teacher measures related to children’s executive function, as it did in
the ECLS-K:2011. As discussed above for the parent survey, research shows the importance of executive
function for learning and academic achievement (e.g., Blair and Razza 2007; Posner and Rothbart 2006).

C-38

The ECLS-K:2024 will include measures of attention focusing and inhibitory control in the kindergarten
teacher survey, as was done in the ECLS-K:2011.
As discussed in the parent survey section above, children’s feelings about school have been linked to their
achievement and educational progress over time. For example, Ladd, Buhs, and Seid (2000) found that
children’s feelings about school can influence school adjustment and participation and engagement in
school, which can impact achievement and educational progress over time. Thus, the child-level teacher
surveys will include a teacher-report measure of child school liking. These items were added to the
ECKS-K:2011 in the spring fourth-grade teacher questionnaire. Based on the recommendation of the
Technical Review Panel for the ECLS-K:2024, these items were added to the kindergarten and first-grade
child-level teacher surveys.
Teachers will be asked about children’s problem-solving skills using items that assess strategic planning
(McDermott 2018; McDermott et al. 2011). These items are new to the ECLS-K:2024. Planning and
problem-solving are interrelated skills that are both needed for scientific reasoning and critical thinking.
Planning is a complex “set of mental and behavioral operations that brings together cognitive, emotional,
and motivational resources in the service of reaching desired goals” (p. 3, Friedman and Scholnick 1997).
Current curriculum standards emphasize the importance of hands-on learning and the need to engage
children in critical thinking and problem solving in science learning. For example, the Next Generation
Science Standards4 indicate that students are expected to demonstrate grade-appropriate proficiency in
such things as asking questions, planning and carrying out investigations, designing solutions, and
communicating information. The National Science Teacher Position Statement for elementary science
education explains that high-quality science instruction moves students from curiosity to interest to
reasoning (Moulding, Bybee, and Paulson 2015), and that students need opportunities to observe
phenomena, engage in problem solving, and provide explanations of their thinking. The strategic planning
items ask teachers to rate students on such skills as understanding cause and effect, developing strategies
to solve problems, self-correcting errors when a plan does not work, and communicating information
about the problem-solving process.
Peer relationships are also an important predictor of children’s later social-psychological adjustment (e.g.,
Parker and Asher 1987). Different patterns of peer relationships can signal behavioral risk or competence.
A primary risk factor is whether a child is rejected by peers. Peer rejection is when the child is disliked or
excluded by one’s peer group. Peer rejection predicts maladaptive behaviors in childhood such as school
disengagement and underachievement (e.g., Buhs, Ladd, and Herald 2006), but it can also have
consequences later in adolescence and adulthood such as criminality, poor psychological health, and
underachievement (e.g., Parker and Asher 1987).
In contrast, children who exhibit prosocial behaviors with peers such as helping others, showing concern,
and being kind are more socially competent with peers. The ability to exhibit prosocial behaviors with
peers predicts the child’s ability to form and maintain positive relationships (see Coie and Kupersmidt
1983) and predicts later psychological health (e.g., Eisenberg, Faves, and Spinrad 2006).
Child-specific skills, knowledge, and behaviors covered in the child-level teacher surveys are the
following:
•

Language and literacy skills and knowledge;

•

Mathematical thinking skills and knowledge;

4

See www.nextgenscience.org for further information. The Next Generation Science Standards (NGSS) is a multi-state effort to create new science
education standards for grades K-12 that are grounded in the most current research on science and scientific learning, which was outlined in the
report Framework for K-12 Science Education that was released in 2011 from the National Academies of Science, a non-governmental organization
whose mission is to advise the nation on scientific and engineering issues. In 2013, the NGSS were released for states to consider for adoption.

C-39

•

Science skills and knowledge;

•

Child’s functional use of language in the classroom;

•

Social skills and approaches to learning;

•

Classroom behavioral regulation;

•

Attention focusing and inhibitory control;

•

Child behaviors relevant to school liking and avoidance;

•

Referral of child out of classroom for behavior;

•

Strategic planning;

•

Peer relationships;

•

Overall rating of academic skills in reading, writing, oral language, math, science, and social
studies;

•

Child’s instructional group placement in reading and math;

•

Child’s activity level (e.g., during structured and unstructured play); and

•

Child’s academic difficulties.

Child-Specific: Special Services and Programs
Although some children spend all of their time in separate special education classes or schools, many
children move in and out of a regular class daily, receiving services in pull-out classes and returning to
the classroom for the rest of the day. The ECLS-K:2024 data on special education placement and
practices will provide critical information about the range and effectiveness of various special services.
These constructs include:
•

Receipt of special services (e.g., pull-out or in-class grouping for regular or remedial services,
individual tutoring, ELL services, speech-language therapy, other special education programs,
programs for children with behavioral/emotional problems, gifted/talented instruction);

•

Child’s ELL status;

•

Child’s IEP/IFSP status;

•

Child’s Section 504 plan status; and

•

Testing accommodations and participation.

Child-Specific: Parent Involvement
Parental involvement in children’s education can have an important influence on school outcomes for
children (Stallings and Stipek 1986; Hoover-Dempsey and Sandler 1997; Gonzalez-DeHass, Willems,
and Holbein 2005). Teachers’ report of the study child’s parent’s participation at school and
communication with the teacher can supplement parents’ report of involvement in school to offer a
picture of parent involvement from both perspectives.
The ECLS-K:2024 items that collect information on school-family-community connections from the
teacher include those on the topic of:
•

Parents’ involvement in children’s schools and education; and

C-40

•

Parent-teacher communication.

Child-Specific: Teacher-Child Relationships
When the child-teacher relationship is warm and free from conflict, children are most apt to have
academic and social success in elementary school. This is especially true for children who might
otherwise be at risk of academic or social problems in school (Pianta and Stuhlman 2004; PeisnerFeinberg et al. 2001). Like the ECLS-K:2011, the ECLS-K:2024 will include a measure of the teacherchild relationship which will be used to help researchers further understand the role that this important
relationship plays in children’s adjustment to school and learning outcomes.
The teacher will answer questions about:
•

Level of closeness between child and teacher; and

•

Level of conflict between child and teacher.

C.3.3

Spring First-Grade Teacher Surveys: Construct Coverage

The spring first-grade teacher surveys in the ECLS-K:2024 are similar to the surveys used for the ECLSK:2011. Details are provided below. Literature review of constructs that are the same as those in
kindergarten are not duplicated in this section.
Classroom and Student Characteristics
Teachers will provide information about classroom and student characteristics including:
•

Class time (full/half day, hours per day, days per week);

•

Grade levels of classes the teacher teaches;

•

Class demographics: class size, age distribution, race-ethnicity distribution, gender distribution,
number repeating grade, percent experiencing homelessness or housing insecurity;

•

Number of students who enter or leave during the school year;

•

Number of language minority children and English language learners (ELL) in the classroom;

•

Number of children in the classroom receiving particular services or in special programs (e.g.,
special education services, a gifted and talented program, remedial services);

•

Number of students with IEPs or 504 plans;

•

Languages used in the classroom;

•

Instruction for English language learners;

•

Number of children above or below grade level in reading and mathematics;

•

Numbers of children with disabilities by disability type (e.g., autism, speech or language
impairments, emotional disturbance, intellectual disability, developmental delay, vision
impairment, hearing impairment);

•

Number of children tardy or absent on an average day; and

•

PTA/PTO contributions to the classroom (e.g., books, technology, art supplies, field trips).

C-41

Instructional Activities and Curricular Focus
The following constructs will be used in the ECLS-K:2024 to characterize teachers’ curricular focus and
how teachers organize their classes for instruction:
•

Class activities outside of the regular class (library, lunch, and recess);

•

Use of class time by subject area and time spent handling disruptive behavior;

•

Socioemotional competencies taught;

•

Behavior support practices;

•

Culturally responsive teaching practices (e.g., display pictures reflecting all students’ background,
written communication to families in their native language, use of alternative formats of
communication, screening materials for negative racial and ethnic stereotypes);

•

Class organization (teacher-directed and child-selected activities);

•

Use of achievement grouping, number of groups;

•

Additional reading services;

•

Use of languages other than English in the classroom (e.g., instruction in reading/literature,
instruction in math, instructional support, directing student behavior, and conversation);

•

Instructional activities with ELL children (assess/monitor language acquisition, assess literacy
skills, intensive skills work in small groups, and peer assisted settings); and

•

Use of homework.

Content Coverage for Language Arts, Mathematics, Science, and Social Studies Instruction
The following constructs will be included in the ECLS-K:2024 to measure students’ opportunities to learn
in various academic subjects.
•

Time spent on specific skills and activities in reading/language arts and in mathematics; and

•

Topics taught in social studies and science.

Resources/Materials
Topics to assess the following will be used to characterize the ECLS-K:2024 students’ classroom
resources and materials:
•

Classroom aides (paid aides and volunteers); and

•

Availability, use, and adequacy of instructional materials.

Student Evaluation
The following are measures of child evaluation that will be included in the ECLS-K:2024:
•

Student factors assessed (e.g., individual achievement relative to class, individual achievement
relative to state or professional standards of student learning, individual achievement relative past
performance, effort, class participation, and class behavior);

•

Methods of assessing children’s progress; and

•

Use of standardized tests.

C-42

Parent Involvement
Constructs to be included in the ECLS-K:2024 in the area of parent involvement include the following:
•

Communication with parents about children’s performance; and

•

Parent involvement in school activities (volunteering, attending meetings, other activities).

Collegial Relations and Opportunities for Professional Development
Data will be collected on the following constructs to measure collegial relations and opportunities for
staff development:
•

Mentorship activities;

•

Frequency of meetings with other teachers and specialists; and

•

Professional learning activities on evidence-based practices.

Teachers’ Views on Teaching, School Climate, and Environment
The ECLS-K:2024 will include items assessing teachers’ views, which can be related to teaching
practices and ultimately to child outcomes, such as the following:
•

School climate;

•

Job satisfaction; and

•

Teachers’ sense of efficacy.

Teacher Background
The following demographic, training, and experience information will be collected as part of the
ECLS-K:2024:
•

Teacher’s gender, age, and race/ethnicity;

•

Teaching experience, by school and grade;

•

Teacher’s education, including degrees and credentials/licenses;

•

Type of teaching certification held;

•

Type of certification program completed;

•

Board certification; and

•

Intention to remain in teaching.

Child-Specific: Enrollment Information
The teacher will provide child-specific information about important characteristics of the child’s:
•

Current grade level;

•

Retention status;

•

Length of time enrolled in the classroom;

•

Number of school absences; and

•

Teacher’s subject-area teaching assignment for child.

C-43

Child-Specific: Evaluation of Child’s Skills, Knowledge, and Behavior
As in kindergarten, first-grade teachers’ reports of children’s skills, knowledge, and behavior will
augment the information collected using the direct cognitive assessments. The spring first-grade teacher
surveys will include constructs similar to the ECLS-K:2024 kindergarten teacher surveys and similar to
the ECLS-K:2011 first-grade teacher surveys. Teachers will be asked some of the same questions asked
of first-grade teachers in ECLS-K:2011, andalong with some new questions will also be added. Details
are provided below.
As in the kindergarten teacher surveys, first-grade teachers will provide ratings of the skills the child
demonstrates in the classroom in literacy/reading, mathematics, and science. Some items are identical to
what was collected in the ECLS-K:2011 in first grade, and some items are identical to items from the
kindergarten round of the ECLS-K:2024. Some of the skills rated in the academic rating scales for the
ECLS-K:2024 are new to reflect new curriculum standards.
The following sets of ratings will be in both the kindergarten and first-grade teacher surveys: functional
language skills, social skills, approaches to learning, classroom behavioral regulation, attentional
focusing, inhibitory control, the child’s school liking behaviors, strategic planning, and peer relationships.
See section C.4.2 for additional information on first-grade constructs that are also obtained in
kindergarten.
Information on peer victimization was collected from teachers and parents in the ECLS-K:2011 starting in
second grade. In the ECLS-K:2024, teachers in the first-grade data collection will be asked about peer
victimization, using items that were asked in the ECLS-K:2011. Peer victimization can be a problem for
school-aged children. A report of school safety and crime, which included student reports of bullying, a
construct closely related to peer victimization, found that about 28 percent of middle and high school
students reported being bullied once or twice at school in the 2010-11 school year (Robers, Kemp, and
Truman 2013). However, the study also found that a lower percentage of students reported being bullied
in 2011 than in 2007 (32 percent of students in the 2006-07 school year). Fewer studies have been done
with younger children, but those that have been published suggest that bullying is experienced by many
children and is related to negative child outcomes. Glew et al.’s (2005) study of third through fifth graders
found that 22 percent of children were classified as victims, bullies, or both. Victims, and children who
were both bullies and victims, had lower achievement scores and were more likely to feel like they did
not belong at school compared to bystanders who observed the bullying but who were not direct victims
of the bullying (Glew et al. 2005). Kochenderfer and Ladd (1996) found a relation between victimization
and school adjustment outcomes, with victimization related to children’s loneliness and desire to avoid
school. Given these findings and White House anti-bullying initiatives, it is important to collect
information about peer victimization in the ECLS-K:2024’s national sample of elementary school
children. Collecting teacher-report data in addition to parent-report data allows for the examination of
peer victimization in different contexts and reduces the effect of single-method bias in measuring this
construct.
Child-specific skills, knowledge, and behaviors covered in the child-level first-grade teacher survey are:
•

Language and literacy skills and knowledge;

•

Mathematical thinking skills and knowledge;

•

Science skills and knowledge;

•

Child’s functional use of language in the classroom;

•

Social skills and approaches to learning;

C-44

•

Classroom behavioral regulation;

•

Attention focusing and inhibitory control;

•

Child behaviors relevant to school liking and avoidance;

•

Referral of child out of classroom for behavior;

•

Strategic planning;

•

Peer relationships;

•

Overall rating of academic skills in reading, writing, oral language, math, science, and social
studies;

•

Child’s instructional group placement in reading and math;

•

Child’s activity level (e.g., during structured and unstructured play); and

•

Child’s academic difficulties.

Child-Specific: Special Services and Programs
These constructs include:
•

Receipt of special services (e.g., pull-out or in-class grouping for regular or remedial services,
individual tutoring, ELL services, speech or language therapy, other special education programs,
programs for children with behavioral/emotional problems, gifted/talented instruction);

•

Child’s ELL status;

•

Child’s IEP/IFSP status;

•

Child’s Section 504 plan status; and

•

Testing accommodations and participation.

Child-Specific: Parent Involvement
The ECLS-K:2024 items that collect information on school-family-community connections from the
teacher will include:
•

Parents’ involvement in children’s schools and education; and

•

Parent-teacher communication.

Child-Specific: Teacher-Child Relationships
The teacher-child relationship will be measured in the spring first-grade child-level teacher survey. The
teacher will answer questions about:
•

Level of closeness between child and teacher; and

•

Level of conflict between child and teacher.

C.4

Special Education Teacher Surveys

Like their general education counterparts, special education teachers and service providers will be asked
to complete surveys. The special education teacher teacher-level survey will gather data on the teacher or
service provider’s background training, experience, and roles. The teacher child-level survey collects
information on students’ disabilities, services, and goals; and the teacher-child relationship. The items are

C-45

parallel tocomplement those on the general classroom teacher’s teacher-level survey.5 In the child-level,
teachers or service providers are asked to complete one survey for each ECLS-K:2024 child who has an
IEP.

C.4.1

Kindergarten Special Education Teacher Surveys

C.4.1.1

Kindergarten Special Education Teacher Surveys: Research Questions

SE-RQ1. What are the types of service delivery models in place for special education? How do
program variations relate to differences in children’s academic or social development?
SE-RQ2. What is the prevalence of different types of disabilities among children in elementary
school? What types of services, instructional strategies, and assistive technologies are provided to
children with different types of disabilities?
SE-RQ3. Do children receive special education services before kindergarten? How do service
variations relate to differences in children’s school readiness, and academic and social
development?
SE-RQ4. What transition activities take place from prekindergarten to kindergarten? How do those
transition activities relate to differences in children’s academic or social development?
SE-RQ5. How is inclusion related to children’s progress through the early grades?
SE-RQ6. Do special education teachers’ or services providers’ characteristics including
sociodemographic characteristics, sense of efficacy, job satisfaction, perceptions of school climate,
their educational background, certifications including participation in alternate certification
programs, or teaching experience influence children’s outcomes, on average or in interaction with
children’s sociodemographic backgrounds?
SE-RQ7. How do special education teachers or service providers and schools handle the diversity
of children’s skills? How are children with disabilities taught? What instructional practices and
classroom resources are used?
SE-RQ8. Are special education teachers’ or service providers’ practices to involve parents
associated with student outcomes?
SE-RQ9. How do special education teachers’ or service providers’ relationships with individual
students differ? What are the consequences of those differences for children’s academic and social
development?
C.4.1.2

Kindergarten Special Education Teacher Surveys: Construct Coverage

Special Education Teacher or Service Provider’s Background
Information on special education teachers’ and service providers’ demographic backgrounds, education,
certification, and teaching experience are of interest to researchers because they provide contextual
information about the child’s learning environment. Other teacher or provider information, such as selfreports of their professional efficacy and their workload (e.g., number of students they serve, teaching
assignment and position), may influence their interactions with students and student outcomes.

In cases where the general education teacher is also the child’s service provider, the general education teacher will be the respondent to both
surveys. In this situation, items common to the general education and special education surveys will be skipped in the special education survey, to
lessen respondent burden.
5

C-46

The following demographic, training, and experience information will be collected from special education
service providers of ECLS-K:2024 children:
•

Teacher’s or service provider’s gender, age, and race/ethnicity;

•

Total years of experience as a teacher or service provider;

•

Total years as a special education teacher or service provider;

•

Total years teaching or providing services at the study school;

•

Teacher’s or service provider’s education, including degrees, credentials/licenses, and coursework;

•

Teacher’s or service provider’s position and assignment;

•

Locations in which the teacher or service provider delivers services, including virtual services;

•

Teacher’s or service provider’s job satisfaction/sense of efficacy;

•

Availability and use of instructional and information technology; and

•

Teacher’s or service provider’s caseload: number of students with IEPs with whom the teacher or
service provider works during a typical week and those students’ background characteristics.

Child-specific: Disabilities and Timing of Eligibility
Information will be collected on the disabilities of the students served. Numerous studies have suggested
that students from different demographic groups based on gender, socioeconomic status, and
race/ethnicity are over identified for special education in some disability categories, suggesting bias in
referral and assessment practices. However, other studies, including some using ECLS-K data, suggest
that students from racially and ethnically diverse backgrounds are underrepresented in special education
once researchers control for other factors, such as socioeconomic status (Cruz and Rodl 2018).
Disproportionality is an active area of policy-related research, which ECLS-K:2024 will inform directly.
In a related and widely discussed study using ECLS-K data, Morgan and his colleagues (2010) analyzed
the effectiveness of special education services by examining whether matched comparison groups of
children receiving and not receiving special education services displayed differences in reading or
mathematics skills, learning-related behaviors, or problem behaviors. Collectively, results indicated that
receipt of special education services had no statistically significant effects. A similar non significance was
also found with regard to adulthood outcomes including educational attainment, social adjustment,
economic self-sufficiency, and physical health, compared to individuals with the same likelihood of
receiving but not receiving services as children (Kanaya, Wai, and Miranda 2019). These studies point to
the importance of further research on children’s disabilities and receipt of special services and programs.
It is also important to understand when children were identified for special education, since prior research
suggests that preschool services improve educational outcomes for children with disabilities, including a
reduced likelihood of repeating kindergarten, enhanced likelihood of meeting minimum literacy
competencies enhanced cognitive skills, and enhanced behavioral outcomes (Lo Casale-Crouch et al.,
2008; Schulting, Malone, and Dodge 2005).
Such information is best collected from the child’s special education teacher or service provider because
he/she is most familiar with the child’s IEP and the types of services, accommodations, and assistive
technology used with the child.

C-47

The kindergarten child-level special education teacher survey asks the teacher or service provider to
provide the following student-level information:
•

Whether the child is receiving special education services through an IEP;6

•

Whether the child had an IEP or IFSP before kindergarten;

•

Whether the teacher or service provider reviewed the child’s records related to special education
services;

•

Transition activities between preschool and kindergarten; and

•

Child’s disabilities.

Child-specific: Services
The kindergarten child-level special education teacher survey also asks for information about the services
students receive, including:
•

Type and amount of special education services the child receives;

•

Child’s classroom placement;

•

Teaching methods and materials used with the child, including assistive technologies;

•

Communications with other teachers about the child; and

•

Communication with the child’s parents.

Child-specific: Goals and Achievement
The kindergarten child-level special education teacher survey will also ask the teacher or provider to
provide information about the child’s IEP goals and achievement, including:
•

Individual evaluations to develop IEP goals;

•

Extent to which the IEP goals have been met;

•

Extent to which the child is expected to meet general education goals and participate in grade-level
assessments; and

•

The child’s expected educational attainment.

Child-specific: Teacher- or Service Provider-Child Relationships
Like the ECLS-K:2011, the ECLS-K:2024 will include a measure of the teacher- or service provider-child
relationship which will be used to help researchers further understand the role that this important
relationship plays in children’s adjustment to school and learning outcomes.

6

This item is designed to ensure that the respondent is answering the correct survey.

C-48

The teacher or service provider will answer questions about:
•

Level of closeness between child and teacher or service provider; and

•

Level of conflict between child and teacher or service provider.

C.4.2

Spring First-Grade Special Education Teacher Surveys

Like their regular classroom teacher counterparts, teachers or service providers who provide special
education and related services to study participants will be asked to complete surveys in the spring firstgrade data collection. The items are parallel tocomplement those on the general education teacher
surveys7 and are similar to those from the kindergarten special education teacher surveys. The first
survey, the special education teacher teacher-level survey, gathers data on the teacher’s or service
provider’s background training, experience, and roles. The second, child-level survey collects information
on students’ disabilities, services, and goals; and teacher-child relationship. In the child-level survey,
teachers and service providers are asked to share information on the study participants with whom they
work, completing one form for each ECLS-K:2024 child who has an IEP.
C.4.2.1

Spring First-Grade Special Education Teacher Surveys: Research Questions

SE-RQ1. What are the types of service delivery models in place for special education? How do
program variations relate to differences in children’s academic or social development?
SE-RQ2. What is the prevalence of different types of disabilities among children in elementary
school? What types of services, instructional strategies, and assistive technologies are provided to
children with different types of disabilities?
SE-RQ73. How are children identified for receipt of special education services?
SE-RQ4. What transition activities take place from prekindergarten to first grade, and how do those
transition activities relate to differences in children’s academic or social development?
SE-RQ3RQ5. How is inclusion related to children’s progress through the early grades?
SE-RQ4RQ6. Do special education teachers’ or services providers’ characteristics including
sociodemographic characteristics, sense of efficacy, job satisfaction, perceptions of school climate,
their educational background, certifications including participation in alternate certification
programs, or teaching experience influence children’s outcomes, on average or in interaction with
children’s sociodemographic backgrounds?
SE-RQ5RQ7. How do special education teachers or service providers and schools handle the
diversity of children’s skills? How are children with disabilities taught? What instructional
practices and classroom resources are used?
SE-RQ6. Are special education teachers’ or service providers’ practices to involve parents
associated with student outcomes?
SE-RQ7. How are children identified for receipt of special education services? What transition
activities take place from prekindergarten to first grade, and how do those transition activities relate
to differences in children’s academic or social development?
SE-RQ8. Are special education teachers’ or service providers’ practices to involve parents
associated with student outcomes?

In cases where the general education teacher is also the child’s service provider, the general education teacher will be the respondent to both
surveys. In this situation, items common to the general education and special education surveys will be skipped in the special education survey, to
lessen respondent burden.
7

C-49

SE-RQ9. How do special education teachers’ or service providers’ relationships with individual
students differ? What are the consequences of those differences for children’s academic and social
development?
C.4.2.2

Spring First-Grade Special Education Teacher Surveys: Construct Coverage

Special Education Teacher or Service Provider Background
Information on teacher or service providers’ demographic backgrounds, education, certification, and
teaching experience are of interest to researchers because they provide contextual information about the
child’s learning environment. Other teacher or service provider information, such as reports of their
professional efficacy and their workload (e.g., number of students they teach/serve, teaching assignment
and position), may influence their interactions with students and student outcomes.
The following demographic, training, and experience variables will be collected from special education
teachers and service providers of ECLS-K:2024 children:
•

Teacher’s or service provider’s gender, age, and race/ethnicity;

•

Total years teaching experience as a teacher or service provider;

•

Total years as a special education teacher or service provider;

•

Total years teaching or providing services at the study school;

•

Teacher’s or service provider’s education, including degrees, credentials/licenses, and coursework;

•

Teacher’s or service provider’s position and assignment;

•

Locations in which the teacher or service provider delivers services, including virtual services;

•

Teacher’s or service provider’s job satisfaction/sense of efficacy;

•

Availability and use of instructional and information technology; and

•

Teacher’s or service provider’s caseload: number of students with IEPs with whom the provider
works during a typical week and those students’ background characteristics.

Child-specific: Disabilities and Timing of Eligibility
Like the spring kindergarten special education teacher survey, the spring first-grade special education
teacher survey will ask the teacher or service provider to provide the following student-level information:
•

Whether the child is receiving special education services through an IEP;

•

When the child began receiving special education services;

•

Teacher’s or service provider’s review of child’s records related to special education services;

•

Transition activities from year to year; and

•

Child’s disabilities.

Child-specific: Services
The spring first-grade special education teacher survey will also ask the teacher or provider to share
information about the services students receive, including:
•

Type and amount of special education services the child receives;

•

Child’s classroom placement;

C-50

•

Teaching methods and materials used with the child, including assistive technologies;

•

Practices and programs used to support outcomes for students with disabilities;

•

Communications with other teachers about the child; and

•

Communication with the child’s parents.

Child-specific: Goals and Achievement
The special education teacher survey also asks the teacher or provider to share information about the
child’s IEP goals and achievement, including:
•

Individual evaluations to develop IEP goals;

•

Extent to which the IEP goals have been met;

•

Extent to which the child is expected to meet general education goals and participate in grade-level
assessments; and

•

The child’s expected educational attainment.

Child-specific: Teacher- or Service Provider-Child Relationships
As described previously for the spring kindergarten special education teacher survey, the first-grade
special education teacher or service provider will answer questions about:
•

Level of closeness between child and teacher or service provider; and

•

Level of conflict between child and teacher or service provider.

C.5

School Administrator Surveys

The ECLS-K:2024 will collect data in spring kindergarten and spring first grade on school composition,
policies, and practices from elementary school principals in schools attended by ECLS-K:2024 sampled
children. The child is the central unit of analysis, and school component data will be used to illuminate
the school context of the ECLS-K:2024 children and investigate the influence of school and administrator
attributes on student outcomes. In the kindergarten year of the study, there will be a nationally
representative sample of schools.

C.5.1

Kindergarten and First-Grade School Administrator Survey: Research
Questions

SA-RQ1. What steps are schools taking to improve student performance, particularly for the groups
of students who are the focus of federal legislation (for example, English language learners and
students with disabilities)?
SA-RQ2. What services are being made available to cohort member children related to federal
requirements?
SA-RQ3: How do differences in schools’ basic demographic, enrollment, resources, polices, and
organizational characteristics relate to children’s academic and social development in the early
elementary school years?
SA-RQ4. What factors are related to students’ placement in particular educational programs (e.g.,
special education or gifted and talented programs)?
SA-RQ5. How does the length of the school year relate to children’s progress, especially cognitive
gains?

C-51

SA-RQ6. How are parents involved in their children’s education during the elementary school
years and how does this involvement relate to child development over this period?
SA-RQ7. What kinds of services or programs do schools provide to families, children, or
community members? How do these relate to children’s academic and socioemotional
development?
SA-RQ8. How do schools respond to the needs of parents with little or no English proficiency?
SA-RQ9. How do neighborhood or community differences relate to children’s cognitive and social
development?
SA-RQ10. What challenges associated with student behavior, attendance, teacher mobility, and
school safety do schools face, and how do these relate to other school characteristics and children’s
cognitive and social development?
SA-RQ11. What are the patterns of grade retention for elementary school children?
SA-RQ12. What are the patterns of intervention for elementary school children experiencing
difficulties in school?
SA-RQ13. How do differences in principals’ background characteristics relate to other school
characteristics and practices?
SA-RQ14: How does the use of online and blended learning relate to children’s progress,
especially in cognitive gains?
C.5.1.1

Spring Kindergarten School Administrator Survey

The instrument is very similar to the administrator surveys for the ECLS-K:2011, with the exception that
questions have been added to the “School Characteristics,” “School Policies and Practices,” and “School
Family Community Connections” sections to detect school-level effects of provisions of the 2015
reauthorization of the Elementary and Secondary Education Act, Every Student Succeeds. The items
included in the instrument are described in more detail below.
C.5.1.2

Spring Kindergarten School Administrator Survey: Construct Coverage

The ECLS-K:2024 will collect data in spring kindergarten on school characteristics, facilities and
resources, community characteristics and school safety issues, school policies and practices, and school
programs for special populations, principal characteristics, and staffing and teacher characteristics from
elementary school principals in schools attended by the ECLS-K:2024 sampled children. The child is the
central unit of analysis, and school component data will be used to illuminate the school context of
ECLS-K:2024 children and investigate the influence of school and administrator attributes on student
outcomes.
School Characteristics, Facilities, and Resources
Several characteristics of elementary schools influence children’s educational experiences and may be
related to their learning outcomes. For example, school size, average daily attendance, and the numbers of
students enrolling in or leaving the school during the school year may influence the stability in classroom
membership experienced by an individual student. The number of days the school is in session sets
bounds on the instructional time available to children and thus can influence learning outcomes. Grade
span dictates the number of school transitions children must make between levels of schooling and the
age range of their school peers. In a study using ECLS-K data, Burkam, Michaels, and Lee (2007) found
that kindergarten children in preprimary schools, where kindergarten was the highest grade, started the
year with a socioeconomic advantage but learned significantly less in mathematics and reading over the
school year than kindergarten children in more traditionally configured elementary schools. The authors

C-52

postulate potential reasons for these findings including curricular alignment with other grade levels and
student opportunities for interaction with older students. Additionally, Combs et al. (2011) found that
students in K-5 schools were found to achieve statistically significantly higher levels of reading and
mathematics achievement compared to students who attended separate intermediate schools.
The type of school attended has important implications for student experience and achievement. Most
public elementary schools are not selective, enrolling all children within predefined attendance zones.
Private schools, by contrast, typically have some kind of admission policy and therefore can be more
selective in their enrollment. Of nonpublic schools, parochial schools, especially Catholic schools, have
historically received the most research attention (e.g., Bryk, Lee, and Holland 1993). Catholic schools
tend to have low absenteeism rates and, for high school students, low dropout rates, and high academic
achievement, despite a high level of heterogeneity in the student body. In recent years, the rise of
nonreligious charter schools has brought greater variability to the nonpublic school landscape and
renewed attention to the potential effects of nonpublic options. For example, Cheng, Hitt, Kisida, and
Mills (2017) found that charter schools which include high academic expectations (referred to as No
Excuses charters) produce significantly higher math and literacy scores after a single year of attendance.
However, in findings from a meta-analysis Betts and Tang (2019) found mixed results for charter school
effects on student achievement depending on the grade level (elementary, middle, high) and outcome
(reading or math achievement). ECLS-K:2024 data will provide important opportunities to contribute to
the literature on effects of school type. Not only will analysts have information about sector, they will
also know whether schools include magnet programs, if they are charter schools, and if they are schools
of choice.
The composition of the student body has important consequences for the types of programs and services
that schools offer. The diversity of student populations with respect to social and economic background,
preparation for school, needs for special services, housing and homelessness, migrant family living, and
levels of proficiency in English has created a number of challenges for schools. The ECLS-K:2024 will
allow analysts to examine how schools have responded to student diversity.
In a study using kindergarten through third-grade data from the ECLS-K to examine family, school, and
neighborhood factors and the impact of socioeconomic status (SES) on children’s reading abilities,
Aikens and Barbarin (2008) found that family characteristics including home literacy and parental
involvement in school had the largest impact on reading ability at the beginning of kindergarten.
However, school and neighborhood conditions were more strongly related than family characteristics to
SES differences in rates of growth in reading over time. The authors state that a school’s poverty
concentration and number of children with reading deficits in the school are negatively related to
individuals’ reading outcomes. Rucinski (2019) used kindergarten through third-grade data from the
ECLS-K:2011 to examine the extent to which racial/ethnic diversity in children’s elementary classrooms
impacts their socioemotional, executive function, and academic development. The study found that
children’s exposure to racial/ethnic diversity in their early elementary classrooms varied greatly and that
increased diversity exposure was significantly related to cognitive flexibility. However, Rucinski (2019)
also found a negative relationship of classroom diversity to teacher-reported internalizing problem
behaviors and negative peer interactions. Like earlier ECLS kindergarten cohort studies, the ECLSK:2024 will be ideally suited for studies that look at academic growth related to school and classroom
characteristics.
The other variables in this set provide the “backdrop” for educational processes occurring within the
school. Total enrollment, school capacity, sources of funding, and adequacy of the physical building
define both the size of the population to be served and the resources to do so. Overcrowding can be a
serious problem, as can inadequate facilities and low levels of funding. Altogether, these variables define
important differences between schools.

C-53

Elementary schools tend to be smaller, more local, and have larger grade spans than either middle or high
schools. The smaller catchment area of elementary schools, combined with the longer grade span,
suggests a long-term cumulative influence of the local neighborhood on both children and their schools.
School-level characteristics are likely to parallel those for the local neighborhood (demographically, but
also, in terms of attitudes, values, and expectations), allowing a long-term, mutual reinforcement less
possible in the larger, more diverse middle and high schools.
The community characteristics items in the school survey focus on school and neighborhood safety.
Schools in crime-ridden areas may have to prioritize security within and around the school, preventing
outdoor play periods or field trips around the neighborhood. The neighborhood questions ask about the
neighborhood in which the school is located. The data collected in these surveys can be combined with
census data that characterize the neighborhood in other ways (by racial composition, crime, income,
employment, etc.). Newly created neighborhood questions about opiate abuse and tensions based on
racial, ethnic, or religious differences have been added to the ECLS-K:2024 kindergarten school
administrator survey.
This set of items broadly defines the characteristics and basic resources of the school. These factors help
describe the student population, the goals and purposes of instruction, time and resource constraints, and
opportunities and resources to meet educational objectives.
These data will allow comparisons of schools that vary by these school characteristics:
•

School type (public/private; affiliation; grades; magnet; etc.);

•

Length of school year;

•

Information on school week (days and length of each day);

•

School programs including full and half-day kindergarten programming, transitional kindergarten,
and pre-first grade;

•

Enrollment and attendance;

•

Student demographics: race/ethnicity, students from migrant families, those experiencing
homelessness, language minority students, catchment area, and students with disabilities;

•

School breakfast and lunch programs and the percentage of children eligible for free or reducedprice meals;

•

State assessment data (e.g., percent of students proficient and above in reading and math);

•

Receipt of Title I and Title III funding;

•

Services and programs/ Title I, including services for kindergartners;

•

Services and programs/ Title III, including services for kindergartners;

•

Adequacy of facilities and resources;

•

Availability and use (e.g., instructional, administrative, and student assessment) of electronic
devices including desktop computers, laptops, Chromebooks, tablets, or others;

•

School status relative to ESSA school performance categories (e.g., unclassified, comprehensive
improvement, and targeted support);

•

School problems (e.g., bullying, children bringing weapons to school, children bringing drugs to
school); and

C-54

•

Recent changes at the school (e.g., funding levels, enrollment, student mobility, staffing, class size,
percent of ELL students, percent of students eligible for free and reduced priced-lunch).

School Policies and Practices
Schools differ in regard to how children are placed into kindergarten programs. Some schools use
placement tests to help determine kindergarten “readiness.” Many schools and districts have policies
regarding age of entry to kindergarten but vary with regards to how flexible those policies are.
There are strong opinions on both sides of the issue of the efficacy of retention as a practice aimed at
remediating the academic or social difficulties of young children. Schools and school districts mirror this
uncertainty, some favoring the use of retention in certain circumstances, others having a “no retention”
policy. Using data from the ECLS-K, Burkam et al. (2007) found that most children who repeated
kindergarten did not appear to receive any cognitive benefits. The authors suggest that current retention
policies at kindergarten should be reconsidered. Hong and Yu (2007) found that any negative effect of
repeating kindergarten faded by the fifth grade. In a longitudinal study, Raffaele Mendez, Kim, Ferron,
and Woods (2015) found that compared to children who started kindergarten 1 year delayed, children
retained in kindergarten were more likely to be placed in special education throughout elementary grades
(1-5) and were also more likely to be rated lower in attention by teachers in both third and fifth grades.
The ECLS-K:2024 will collect data on retention policy and remediation and/or support practices at the
school level and gather information about the number of children retained in each class from the teachers
at each target grade level. These data can be used to address a number of issues about retention: the
effects of retention for individual children, the influence of the proportion of the class that has been
retained, and school policies regarding retention in kindergarten.
In addition, with the coronavirus pandemic beginning in 2020 and its continued ramifications for schools,
the spring kindergarten school administrator survey includes questions on the schools’ use of funding
from federal aid through the American Rescue Plan.
The policy topics covered in the school administrator survey include:
•

Measures taken to ensure school safety;

•

Emergency procedure drills (e.g., evacuation, lockdown, shelter in place);

•

Disruptions to instruction due to emergencies or implementation of emergency procedures;

•

School policy regarding technology use;

•

Limits on contributions of school parent teacher organizations;

•

Kindergarten readiness/placement testing;

•

Entry age for kindergarten;

•

Identification of students for gifted and talented program;

•

Programs to support positive student behavior (e.g., MTSS, SEL, PBIS);

•

Equitable school practices (e.g., suspensions and identification for gifted and talented programs);

•

Retention policies and practices; and

•

Use of funding from federal aid through the American Rescue Plan related to coronavirus-related
issues.

C-55

School-Family-Community Connections
Some schools have responded to community needs for daycare and before- and after-school programs by
offering these services in the school building. Schools may run these programs themselves or through the
Parent Teacher Association or may allow independent providers to operate on site. These services may be
essential for children of working parents; on-site programs allow for continuity between the school day
and their before- and after-school daycare arrangements.
Parent-school communication may have a number of potential benefits for children’s education. Parents
as a visible presence in the school can reinforce the notion that education is a valued community goal.
Parents can volunteer as classroom or school aides, freeing the teacher’s time for instruction. When
schools actively promote parent involvement and communication, parents may become more involved
and more aware of school and classroom activities and of their own child’s instructional program. Parents
can then communicate with students about their experiences in school and what they are learning in a
more informed manner and can support the child’s learning more effectively at home. Strong
relationships between schools and parents are associated with positive outcomes for children (HooverDempsey and Sandler 1997; Gonzalez-DeHass, Willems and Holbein 2005).
The ECLS-K:2024 items that collect information on school-family-community connections include:
•

Programs or services for children on the school site;

•

School-based programs or services for parents and families (e.g., parenting education adult literacy,
and family literacy programs for families whose first language is not English);

•

Neighborhood problems (racial tensions, gangs, crime, and opioid addiction);

•

School-safety measures and drills;

•

Disruption of school activities due to school safety threats;

•

Communication with parents and families (e.g., modes of communication, reports of student
performance, parent-teacher conferences); and

•

Parent involvement (e.g., volunteering, attending school events, and PTAParent-Teacher
Organizations/ Associations).

School Programs for Special Populations
Because the ECLS-K:2024 will provide longitudinal data on a nationally representative sample of
children, including children with special educational needs, information is needed on the special programs
in which children in the study participate. Because programs serving special populations can vary in
content and organization—differences that may, in turn, have consequences for both children’s
opportunities to learn and their progress in school—basic characteristics of these programs need to be
documented. Services to families of children in special programs should also be documented. The use of
special staff—e.g., social workers, parent liaisons—home visits, parenting education, and other efforts to
involve parents in support of their children’s success in school are among the topics included. Survey
questions included in the ECLS-K:2024 on these topics will provide data to address issues of how schools
can best serve children who receive specialized programs or services.
Data from the ECLS-K were used to examine the association between the school resources for English
language learners (ELL) students and their academic growth from kindergarten through fifth grade (Han
and Bridglall 2009). The authors found that ELL children narrowed the initial gap in math scores with
their English-speaking peers by fifth grade. This was especially true for ELL children in schools with
either a high- or low ELL student concentration. In contrast, using data from ECLS-K:2011, a study

C-56

found neither the adequacy of instructional materials nor student program type to be related to growth in
math over the kindergarten year (Wilkinson 2017). The ECLS-K:2024 will provide current data about
schools’ efforts to serve the growing population of ELL children in U.S. schools. The ECLS-K:2024
direct assessments are specially designed to directly assess ELL children’s early English reading abilities,
which was not possible in the ECLS-K but was possible with the ECLS-K:2011 data. This feature will
continue to allow for a more thorough understanding of how services for these children relate to their
reading growth beginning at kindergarten entry, regardless of their initial English proficiency.
Additionally, the study will continue to ask school administrators to report the proportion of ELL children
in the school’s kindergarten and the total number of ELL children in the school, as well as the number of
children receiving bilingual education or ELL/ESL services, and the types of services provided to
language minority (LM) families for the ECLS-K:2024 study, as was done in the ECLS-K:2011.
Because baseline data will be collected during the kindergarten year, a point when many children with
disabilities have not yet been identified by schools, the ECLS-K:2024 can help to shed light on how
children come to be classified as having a particular disability. Information on where children with
disabilities are served (i.e., in the classroom— “inclusion”—or in special pull-out classes) is also
important information to be gathered in the ECLS-K:2024. Enabling children to function effectively in a
regular classroom setting is a goal of many special education programs. Although some children spend all
of their time in separate special education classes or schools, many children move in and out of a regular
class daily, receiving services in pull-out classes and returning to the classroom for the rest of the day.
The ECLS-K:2024 data on special education placement and practices will provide critical information
about the range and effectiveness of options for special education delivery.
The ECLS-K:2024 data on special populations include:
•

Delivery of instruction to English language learners (ELL) (ESL, bilingual, and dual language) and
services for language minority (LM) families (translators made available during meetings, written
materials translated into native language);

•

Delivery of special education and related services to children with disabilities;

•

Programs for gifted and talented children; and

•

Services provided to students experiencing homelessness or housing insecurity.

Staffing and Teacher Characteristics
The ECLS-K:2024 school-level data on teacher characteristics will allow researchers to evaluate the
importance of the following elements of the teaching staff for children, aside from the characteristics of
their own teacher (which will be addressed on the teacher survey):
•

Total number of full- and part-time teachers, specialists, nurses, and paraprofessionals;

•

Teacher mobility;

•

The racial and ethnic composition of teaching staff;

•

Teacher compensation (base salary range, average starting salary, and monetary incentives); and

•

School climate.

Principal Characteristics
School principals have many roles and responsibilities: conveying and implementing state and district
requirements and initiatives, assuming the role of inspirational leader for the staff, coordinating reform
efforts, and managing the day-to-day operations of the school. Many principals also have additional

C-57

teaching or administrative duties. How principals exercise these duties may influence teachers’
motivation, enthusiasm, and commitment to education.
Although literature exists on how leadership skills create conditions conducive to effective schools, few
studies address the influence of variations in principals’ characteristics, qualifications, and time use on
student outcomes. The following ECLS-K:2024 variables might help explain why certain principals are
especially successful:
•

Principal’s gender, age, and race/ethnicity;

•

Principal’s years at the study school;

•

Principal’s years in the role of principal;

•

Principal’s formal education;

•

Principal’s time allocation; and

•

Principal’s familiarity with students.

C.5.2

Spring First-Grade School Administrator Survey

The spring first-grade school administrator instrument is very similar to the administrator survey for the
ECLS-K:2024 kindergarten data collection round, with the exception that questions from latter rounds of
the ECLS-K:2011 have been added to the Staffing and Teacher Characteristics and Principal
Characteristics sections, including questions about salary ranges for teachers, teacher incentives for
improving student performance, and languages other than English spoken by the school administrator to
communicate with students, families, and caregivers.. Similar to the ECLS-K:2011, there are several
constructs that are introduced in the first-grade school administrator surveys, including the number of
students newly evaluated for IEPs, and methods used to evaluate students for IEPs. The ECLS-K:2024
first-grade administrator paper survey will have two versions: one for schools without a completed
administrator survey in the kindergarten round and a more streamlined version for schools with a
completed kindergarten instrument. These items are combined in the web survey. The items included in
the instrument are described in more detail below.
C.5.2.1

Spring First-Grade School Administrator Survey: Construct Coverage

Literature review for constructs that are the same as those in kindergarten are not duplicated in this
section.
School Characteristics, Facilities, and Resources
These data will allow comparisons of schools that vary by these school characteristics:
•

School type (public/private, affiliation, grades, magnet, etc.);

•

Length of school year;

•

Information on school week (days and length of each dayper week);

•

School programs including full and half-day kindergarten programming, transitional kindergarten,
and pre-first grade;

•

Enrollment and attendance;

•

Student demographics: race/ethnicity, students from migrant families, those experiencing
homelessness, language minority students, catchment area, and students with disabilities;

C-58

•

School breakfast and lunch programs and the percentage of children eligible for free or reducedprice meals;

•

State assessment data (e.g., percent of students proficient and above in reading and math);

•

Receipt of Title I and Title III funding;

•

Services and programs/ Title I;

•

Services and programs/ Title III;

•

Adequacy of facilities and resources;

•

Availability and use (e.g., instructional, administrative, and student assessment) of electronic
devices including desktop computers, laptops, Chromebooks, tablets or other;

•

School status relative to ESSA school performance categories (e.g., unclassified, comprehensive
improvement, and targeted support);

•

School problems (e.g., bullying, children bringing weapons to school, children brining drugs to
school); and

•

Recent changes at the school (e.g., funding levels, enrollment, student mobility, staffing, class size,
percent of ELL students, percent of students eligible for free and reduced priced lunch).

School Policies and Practices
The policy topics covered in the school administrator questionnaire include:
•

Measures taken to ensure school safety;

•

Emergency procedure drills (e.g., evacuation, lockdown, shelter in place);

•

School policy regarding technology use;

•

Limits on contributions of school parent teacher organizations;

•

Identification of students for gifted and talented program;

•

Identification of students for special education services;

•

Programs to support positive student behavior (e.g., MTSS, SEL, PBIS);

•

Information on suspensions and expulsions;

•

Equitable school practices (e.g., suspensions and identification for gifted and talented programs);
and

•

Retention policies and practices.

School-Family-Community Connections
The ECLS-K:2024 items that collect information on school-family-community connections include:
•

Programs or services for children on the school site;

•

School-based programs or services for parents and families (e.g., parenting education adult literacy,
and family literacy programs for families whose first language is not English);

•

Neighborhood problems (racial tensions, gangs, crime, and opioid addiction);

•

School-safety measures and drills;

C-59

•

Disruption of school activities due to school safety threats;

•

Communication with parents and families (e.g., modes of communication, reports of student
performance, parent-teacher conferences); and

•

Parent involvement (e.g., volunteering, attending school events, and PTA).

School Programs for Particular Populations
The ECLS-K:2024 data on particular populations include:
•

Delivery of instruction to English language learners (ELL) (ESL, bilingual, and dual language) and
services for language minority (LM) families (translators made available during meetings, written
materials translated into native language);

•

Delivery of special education and related services to children with disabilities;

•

Programs for gifted and talented children; and

•

Services provided to students experiencing homelessness or housing insecurity.

Staffing and Teacher Characteristics
The ECLS-K:2024 school-level data on teacher characteristics will allow researchers to evaluate the
importance of the following elements of the teaching staff for children, aside from the characteristics of
their own teacher (which will be addressed on the teacher questionnaire):
•

Total number of full- and part-time teachers, specialists, nurses, and paraprofessionals;

•

Teacher mobility;

•

The racial and ethnic composition of teaching staff;

•

Teacher compensation (base salary range, average starting salary, and monetary incentives); and

•

School climate.

Principal Characteristics
Data on the following principal characteristics will be collected in the ECLS-K:2024:
•

Principal’s gender, age, and race/ethnicity;

•

Principal’s years at the study school;

•

Principal’s years as teacher before becoming administrator;

•

Principal’s years in the role of principal;

•

Principal’s formal education;

•

Principal’s time allocation; and

•

Principal’s familiarity with students.

C-60

References
Ackerman, B., Brown, E., and Izard, C. (2003). Continuity and Change in Levels of Externalizing
Behavior in School of Children From Economically Disadvantaged Families. Child
Development, 74(3): 694-709.
Afterschool Alliance (2020). Demand grows, opportunity shrinks. Retrieved September 12, 2022,
from https://afterschoolalliance.org/documents/AA3PM-2020/AA3PM-National-Report.pdf.
Adams, G. and Todd, M. (2020). Meeting the school-age child care needs of working parents facing
COVID-19 distance learning. Retrieved September 12, 2022, from
https://files.eric.ed.gov/fulltext/ED610005.pdf.
Aikens, N., and Barbarin, O. (2008). Socioeconomic Differences in Reading Trajectories: The
Contribution of Family, Neighborhood, and School Contexts. Journal of Educational
Psychology, 100(2): 235-251.
Alexander, K., Entwisle, D.R., and Dauber, S.L. (1993). First Grade Classroom Behavior: Its Shortand Long-Term Consequences for School Performance. Child Development, 64: 801-814.
Alexander, K.L., and Entwisle, D.R. (1988). Achievement in the First Two Years of School: Patterns
and Processes. Monographs of the Society for Research in Child Development, 53(2): 1-140.
Allegretto, S.A., and Mishel, L. (2016). The Teacher Pay Gap Is Wider Than Ever. Washington, DC:
Economic Policy Institute. Retrieved July 17, 2020, from
https://www.epi.org/publication/the-teacher-pay-gap-is-wider-than-ever-teachers-paycontinues-to-fall-further-behind-pay-of-comparable-workers/.
Almond, T., and Holt, J. (2005). What Parents Do in the Home and Community That Influences Their
Child’s Reading. Paper presented at the annual meeting of the Mid-Western Educational
Research Association, Columbus, Ohio.
Amato, P.R., and Gilbreth, J.G. (1998). Nonresident Fathers and Children’s Well-Being. Unpublished
manuscript. Lincoln, NE: Department of Sociology, University of Nebraska-Lincoln.
American Academy of Audiology. (2011). American Academy of Audiology Childhood Hearing
Screening Guidelines. Retrieved July 17, 2020, from:
https://www.cdc.gov/ncbddd/hearingloss/documents/AAA_Childhood%20Hearing%20Gui
delines_2011.pdf.
American Psychological Association. (2010). Stress in America. Washington, DC: Author. Retrieved
July 8, 2019, from https://www.apa.org/news/press/releases/stress/2010/nationalreport.pdf.
American Psychological Association. (2010). Stress in America. Washington, DC: Author. Retrieved
July 8, 2019, from https://www.apa.org/news/press/releases/stress/2010/nationalreport.pdf.
American Psychological Association. (2017). Stress in America: The State of Our Nation. Stress in
America TM Survey. Washington, DC: Author. Retrieved July 8, 2019, from
https://www.apa.org/news/press/releases/stress/2017/state-nation.pdf.

C-61

Anders, Y., Rossbach, H.G., Weinert, S., Ebert, S., Kuger, S., Lehrl, S., and von Maurice, J. (2012). Home
and Preschool Learning Environments and Their Relations to the Development of Early
Numeracy Skills. Early Childhood Research Quarterly, 27(2): 231-244.
Annie E. Casey Foundation. (2017). Kids Count Data Book: State Trends in Child Well-Being.
Baltimore: Author. Retrieved May 17, 2019, from https://www.aecf.org/resources/2017kids-count-data-book.
Annie E. Casey Foundation. (2018). Kids Count Data Book: State Trends in Child Well-Being.
Baltimore: Author. Retrieved May 17, 2019, from https://www.aecf.org/resources/2018kids-count-data-book.
Annie E. Casey Foundation. (2019). 2019 Kids Count Databook: State Trends in Child Well-Being.
Baltimore: Author. Retrieved June 14, 2020,
from https://www.aecf.org/m/resourcedoc/aecf-2019kidscountdatabook-2019.pdf
Ansari, A., and Crosnoe, R. (2018). The Transition Into Kindergarten for English Language Learners.
In A. Mashburn, J. LoCasale-Crouch and K. Pears (Eds.), Kindergarten Transition and
Readiness: Promoting Cognitive, Social-Emotional, and Self-Regulatory Development (pp.185204). Cham, Switzerland: Springer International Publishing AG.
Arteaga, I., Heflin, C., and Parsons, S. (2019). Design Flaws: Consequences of the Coverage Gap in
Food Programs for Children at Kindergarten Entry. Applied Economic Perspectives and Policy,
41(2): 265-283.
Bachman, H., Elliott, L., Scott, P., and Navarro, M. (2018). Latino Children’s Academic and Behavioral
Trajectories in Early Elementary School: Examining Home Language Differences Within
Preschool Types. Early Childhood Research Quarterly, 52: 138-153.
Bane, M.J., and Ellwood, D. (1983). The Dynamics of Dependence: The Routes to Self-Sufficiency.
Report prepared for Assistant Secretary of Planning and Evaluation, Department of Health
and Human Services. Cambridge, MA: Harvard University, Kennedy School of Government.
Baroody, A.J. (2003). The Development of Adaptive Expertise and Flexibility: The Integration of
Conceptual and Procedural Knowledge. In A.J. Baroody and A. Dowker (Eds.), The
Development of Arithmetic Concepts and Skills: Constructing Adaptive Expertise Studies.
Mahwah, N.J.: Lawrence Erlbaum Associates, Inc.
Bassok, D., Finch, J., Lee, R., Reardon, S., and Waldfogel, J. (2016). Socioeconomic Gaps in Early
Childhood Experiences: 1998 to 2010. AERA Open, 2(3): 1-22. Retrieved on June 15, 2020,
from https://journals.sagepub.com/doi/full/10.1177/2332858416653924.
Bassok, D., and Latham, S. (2017). Kids Today: The Rise in Children’s Academic Skills at
Kindergarten Entry. Educational Researcher, 46(1): 7-20.
Bassok, D., Latham, S., and Rorem, A. (2016). Is kindergarten the new first grade?. AERA Open, 1(4),
1-31. DOI: 10.1177/2332858415616358.
Bassok, D., and Shapiro, A. (2021). Understanding COVID-19-era enrollment drops among early grade
public school students. Retrieved June 18, 2021, from

C-62

https://www.brookings.edu/blog/brown-center-chalkboard/2021/02/22/understandingcovid-19-era-enrollment-drops-among-early-grade-public-school-students.
Berger, R.H., Diaz, A., Valiente, C., Eisenberg, N., Spinrad, T.L., Doane, L.D., Thompson, M.S.,
Hernandez, M.M., Johns, S.K., and Southworth, J. (2019). The Association Between Home
Chaos and Academic Achievement: The Moderating Role of Sleep. Journal of Family
Psychology, 33(8): 975-981.
Bergen, D., and Fromberg, D. (2009). Play and social interaction in middle childhood. Phi Delta
Kappan, 90(6): 426-430.
Berry, D., Blair, C., Willoughby, M., Garrett-Peters, P., Vernon-Feagans, L., and Mills-Koonce, W.R.
(2016). Household Chaos and Children’s Cognitive and Socio-Emotional Development in Early
Childhood: Does Childcare Play a Buffering Role? Early Childhood Research Quarterly, 34: 115127. Retrieved on July 17, 2020, from http://dx.doi.org/10.1016/j.ecresq.2015.09.003.
Betts, J. R., & Tang, Y. E. (2019). The effect of charter schools on student achievement. In M. Berends,
R. J. Waddington, & J. Schoenig (Eds.) School choice at the crossroads: Research perspectives,
(67-89). Taylor & Francis.
Bidwell, C.E., and Bryk, A.S. (1994). How teachers’ work is organized: The content and consequences
of the structure of the high school workplace. Chicago, IL: The National Opinion Research
Center at the University of Chicago.
Blair, C., and Raver, C.C. (2015). School Readiness and Self-Regulation: A Developmental
Psychobiological Approach. Annual Review of Psychology, 66: 711-731.
Blair, C., and Razza, R. (2007). Relating Effortful Control, Executive Function, and False Belief
Understanding to Emerging Math and Literacy Ability in Kindergarten. Child Development,
78(2): 647-663.
Blevins-Knabe, B., and Musun-Miller, L. (1996). Number Use at Home by Children and Their Parents
and Its Relationship to Early Mathematical Performance. Early Development and Parenting,
5(1): 35-45.
Blevins-Knabe, B., Whiteside-Mansell, L., and Selig, J. (2007). Parenting and Mathematical
Development. Academic Exchange Quarterly, 11(2): 76-80.
Bodovski, K., and Youn, M. (2011). The Long-Term Effects of Early Acquired Skills and Behaviors on
Young Children’s Achievement in Literacy and Mathematics. Journal of Early Childhood
Research, 9(1): 4-19.
Bowden, M., Bartkowski, J., Xu, X., and Lewis, R. (2018). Parental Occupation and the Gender Math
Gap: Examining the Social Reproduction of Academic Advantage Among Elementary and
Middle School Students. Social Science, 7(6): 1-17.Brooks-Gunn, J., Duncan, G.J., Klebanov, P.K.,
and Sealand, N. (1993). Do Neighborhoods Influence Child and Adolescent Development?
American Journal of Sociology, 99(2): 353-395.
Bryk, A., Lee, V., and Holland, P. (1993). Catholic schools and the common good. Cambridge, MA US:
Harvard University Press.

C-63

Buhs, E.S., Ladd, G.W., and Herald, S.L. (2006). Peer Exclusion and Victimization: Processes That
Mediate the Relation Between Peer Group Rejections and Children’s Classroom Engagement
and Achievement? Journal of Educational Psychology, 98(1): 1-13.
Burkam, D., Michaels, D., and Lee, V. (2007). School grade span and kindergarten learning. The
Elementary School Journal, 107(3): 287-303.
Burkam, D., LoGerfo, L., Ready, D., and Lee, V. (2007). The differential effects of repeating
kindergarten. Journal of Education for Students Placed at Risk, 12(2): 103-136.
Callen, J. (2020). New Household Pulse Survey Shows Concern Over Food Security, Loss of Income.
Washington, DC: U.S. Census Bureau. Retrieved on June 12, 2020,
from https://www.census.gov/library/stories/2020/05/new-household-pulse-surveyshows-concern-over-food-security-loss-of-income.html.
Campbell, F.A., Pungello, E.P., Kainz, K., Burchinal, M., Pan, Y., Wasik, B.H., Barbarin, O., Sparling, J.J.,
and Ramey, C.T. (2012). Adult Outcomes as a Function of an Early Childhood Educational
Program: An Abecedarian Project Follow-Up. Developmental Psychology, 48(4): 1033.
Casey, B.J., Giedd, J.N., and Thomas, K.M. (2000). Structural and Functional Brain Development and
Its Relation to Cognitive Development. Biological Psychiatry, 54(1-3): 241-257.
Castillo, A., Khislavsky, A., Altman, M., and Gilger, J. W. (2020). Executive function developmental
trajectories kindergarten to first grade: monolingual, bilingual and English language learners.
International Journal of Bilingual Education and Bilingualism, 1-19.
Catsambis, S., and Buttaro, A. (2012). Revisiting “Kindergarten as Boot Camp”: A Nationwide Study
of Ability Grouping and Psycho-Social Development. Social Psychology of Education: An
International Journal, 15(4): 483-515.
Cavanagh. S., and Fomby, P. (2019). Family Instability in the Lives of American Children. Annual
Review of Sociology, 45:493-513.
Centers for Disease Control and Prevention. (2020). Preventing Adverse Childhood Experiences:
What Are Adverse Childhood Experiences? Retrieved April 24, 2020, from
https://www.cdc.gov/violenceprevention/childabuseandneglect/aces/fastfact.html.
Chandra, A., Martinez, G.M., Mosher, W.D., Abma, J.C., and Jones, J. (2005). Fertility, Family Planning
and Reproductive Health of U.S. Women: Data From the 2002 National Survey of Family
Growth. Vital Health Statistics, 23(25).
Cheng, A., Hitt, C., Kisida, B., and Mills, J. N. (2017). “No excuses” charter schools: A meta-analysis of
the experimental evidence on student achievement. Journal of School Choice, 11(2), 209-238.
Child Trends. (2015). Births to Unmarried Women. Bethesda, MD: Child Trends. Retrieved June 11,
2020, from https://www.childtrends.org/indicators/births-to-unmarried-women/.
Child Trends. (2016). Racial and Ethnic Composition of the Child Population: Indicators of Child and
Youth Well-Being. Bethesda, MD: Child Trends. Retrieved July 17, 2020, from
https://www.childtrends.org/indicators/racial-and-ethnic-composition-of-the-childpopulation.

C-64

Child Trends Databank. (2019). Children in Poverty. Bethesda, MD: Author. Retrieved from
https://www.childtrends.org/?indicators=children-in-poverty.
Clark, L., Gresham, F., and Elliott, S. (1985). Development and Validation of a Social Skills
Assessment Measure: The Tross-C. Journal of Psychoeducational Assessment, 3(4): 347-356.
Coie, J.D., and Kupersmidt, J.B. (1983). A Behavioral Analysis of Emerging Social Status in Boys’
Groups. Child Development, 54(6): 1400-1416.
Colby, S.L., and Ortman, J.M. (2015). Projections of the Size and Composition of the U.S. Population:
2014 to 2060, Population Estimates and Projections. Current Population Reports. Washington,
DC: U.S. Census Bureau.
Coldwell J., Pike A., and Dunn J. (2006). Household Chaos–Links with Parenting and Child
Behaviour. Journal of Child Psychology and Psychiatry, 47(11): 1116-1122.
Coleman-Jensen, A., Rabbitt, M.P., Gregory, C.A., and Singh, A. (2019). Household Food Security in the
United States in 2018 (ERR-270). Washington, DC: U.S. Department of Agriculture, Economic
Research Service.
Collaborative Longitudinal Evaluation of Ethnicity and Refractive Error Study Group. (2003).
Refractive Error and Ethnicity in Children. Archives of Opthamology, 121(8): 1141-1147.
Combs, J. P., Clark, D., Moore, G. W., Onwuegbuzie, A. J., Edmonson, S. L., and Slate, J. R. (2011).
Academic achievement for fifth-grade students in elementary and intermediate school
settings: Grade span configurations. Current Issues in Education, 14(1), 1-46.
Connell, J.P., Spencer M.B., and Aber, J.L. (1994). Educational Risk and Resilience in AfricanAmerican Youth: Context, Self, Action, and Outcomes in School. Child Development, 65(2):
493-506.
Cooper, H., Batts Allen, A., Pattall, E. A., and Dent, A. L. (2010). Effects of full-day kindergarten on
academic achievement and social development. Review of Educational Research, 80(1), 34–70.
Council of Chief State School Officers. (2021). Restart and Recovery: Declining Kindergarten
Enrollment in 2020-21: Recommendations for State Education Agencies. Retrieved June 18,
2021, from CCSSO_RR_Declining_Kindergarten_Enrollment-v3 POSTED.pdf.
Crocker, R., and Brooker, G. (1986). Classroom control and student outcomes in grades 2 and 5.
American Educational Research Journal, 23(1): 1-11.
Cruz, R.A., and Rodl, J.E. (2018). An Integrative Synthesis of Literature on Disproportionality in
Special Education. The Journal of Special Education, 52(1): 50-63.
Cunningham, M., Cox, E.O., and the Committee on Practice and Ambulatory Medicine, and the
Section on Otolaryngology and Bronchoesophagology. (2003). Hearing assessment in infants
and children: Recommendations beyond neonatal screening. Pediatrics, 111(2): 436-440.
Cunningham, S., Hardy, S., Jones, R., Ng, C., and Kramer, M. (2022). Changes in the incidence of
childhood obesity. Pediatrics, 150: 1-10.

C-65

Da Cruz, A.D., Silvério, K.C.A., Da Costa, A.R.A., Moret, A.L.M., Lauris, J.R.P., and De Souza Jacob, R.T.
(2016). Evaluating Effectiveness of Dynamic Soundfield System in the Classroom. Noise &
Health, 18(80): 42.
Danniels E, Pyle A. Defining Play-based Learning. In: Tremblay RE, Boivin M, Peters RDeV, eds. Pyle
A, topic ed. Encyclopedia on Early Childhood Development [online]. https://www.childencyclopedia.com/play-based-learning/according-experts/defining-play-based-learning.
Datar A., and Sturm R. (2004). Physical education in elementary school and body mass index:
evidence from the early childhood longitudinal study. American Journal of Public Health, 94:
1501–1506.
Datar, A., and Sturm, R. (2006). Childhood Overweight and Elementary School Outcomes.
International Journal of Obesity, 30(9): 1449-1460.
Deater-Deckard, K, Li, M., and Bell, M. (2016). Multi-Faceted Emotion Regulation, Stress, and Affect
in Mothers of Young Children. Cognition and Emotion, 30(3): 444-457.
Deming, D. (2009). Early Childhood Intervention and Life-Cycle Skill Development: Evidence from
Head Start. American Economic Journal: Applied Economics, 1(3): 111-134.
Diamond, A., Barnett, S., Thomas, J., and Munro, S. (2007). Preschool Program Improves Cognitive
Control. Science, 318(5855): 1387-1388.
Dotterer, A., McHale, S., and Crouter, A. (2009). The Development and Correlates of Academic
Interests From Childhood Through Adolescence. Journal of Educational Psychology, 101(2):
509-519.
Duncan, G.J. (1991). The Economic Environment of Childhood. In A.C. Huston (Ed.), Children in
Poverty (pp. 23-50). New York: Cambridge University Press.
Duncan, G.J., Dowsett, C., Claessens, A., Magnuson, K., Huston, A.C., Klebanov, P., Pagani, L., Feinstein,
L., Engel, M., Brooks-Gunn, J., Sexton, H., Duckworth, K., and Japel, C. (2007). School Readiness
and Later Achievement. Developmental Psychology, 43(6): 1428.
Dunifon, R., and Kowaleski-Jones, L. (2003). The Influences of Participation in the National School
Lunch Program and Food Insecurity on Child Well-Being. Social Service Review, 77(1): 72-93.
Dunifon, R., and Kowaleski-Jones, L. (2007). The Influence of Grandparents in Single-Mother
Families. Journal of Marriage and Family, 69(2): 465-481.
Durlak, J. A., Mahoney, J.L., Bohnert, A. M., and Parente, A. M. (2010). Developing and Improving
After-School Programs to Enhance Youth’s Personal Growth and Adjustment: A Special Issue
of AJCP. American Journal of Community Psychology, 45(3-4): 285-293.
Edmonds, R.R. (1979). A discussion of the literature and the issues related to effective schooling.
Cambridge, MA: Center for Urban Studies, Harvard Graduate School of Education.
Education Trust (2020). Parents overwhelmingly concerned their children are falling behind during
school closures. Retrieved September 12, 2022, from https://edtrust.org/parentsoverwhelmingly-concerned-their-children-are-falling-behind-during-school-closures.

C-66

Eide, E., and Showalter, M. (2012). Sleep and Student Achievement. Eastern Economic Journal, 38(4):
512-524.
Eisenberg, N., Fabes, R.A., and Spinrad, T.L. (2006). Prosocial Development. In W. Damon (Series
Ed.) and N. Eisenberg (Vol. Ed.), Handbook of Child Psychology (Vol. 3, pp. 646-718). New
York: Wiley.
Engel, M., Claessens, A., Watts, T., and Stone, S. (2016). Socioeconomic Inequality at School Entry: A
Cross-Cohort Comparison of Families and Schools. Children and Youth Services Review, 71:
227-232. Retrieved on June 14, 2020, from https://inid.gse.uci.edu/files/2011/03/Engel-etal.-2016-rising-inequality.pdf.
Entwisle, D.R. (1995). The role of schools in sustaining early childhood program benefits. The
Future of Children, 5(3): 133-144.
Fattore, T., and Mason, J. (2018). Constructing Indicators of Child Well-Being From a Child
Standpoint. Developing Practice: The Child, Youth and Family Work Journal, 50: 34-49.
Federal Interagency Forum on Child and Family Statistics. (2007). America’s Children: Key National
Indicators of Well-Being, 2007. Washington, DC: U.S. Government Printing Office.
Federal Interagency Forum on Child and Family Studies. (2017). America’s Children: Key National
Indicators of Well-Being, 2017. Washington, DC: Government Printing Office.
Federal Interagency Forum on Child and Family Statistics. (2019). America’s Children: Key National
Indicators of Well-Being, 2019. Washington, DC: U.S. Government Printing Office. Retrieved on
June 11, 2020, from https://www.childstats.gov/pdf/ac2019/ac_19.pdf.
First Five Years Fund. (2016). Every Student Succeeds Act (ESSA). Washington, DC: Author.
Retrieved July 17, 2020, from https://www.ffyf.org/issues/essa/.
Foster, T.D., Froyen, L.C., Skibbe, L.E., Bowles, R.P., and Decker, K.B. (2016). Fathers’ and Mothers’
Home Learning Environments and Children’s Early Academic Outcomes. Reading and
Writing, 29(9): 1845-1863.
Frey, W.H. (2011). America’s Diverse Future: Initial Glimpses at the U.S. Child Populations from the
2010 Census. Washington, D.C.: The Metropolitan Policy Program at Brookings.
Friedman, S.L., and Scholnick, E.K. (1997). An Evolving “Blueprint” for Planning: Psychological
Requirements, Task Characteristics, and Social-Cultural Influences. In E.K. Scholnick and S.L.
Friedman (Eds.), The Developmental Psychology of Planning: Why, How, and When Do We
Plan? (pp. 3-22). Mahwah, New Jersey: Lawrence Erlbaum Associates.
Fusaro, J. (1997). The effect of full-day kindergarten on student achievement: A meta-analysis. Child
Study Journal, 27(4), 269-277.
Gable, S., Chang, Y., and Krull, J.L. (2007). Television Watching and Frequency of Family Meals Are
Predictive of Overweight Onset and Persistence in a National Sample of School-Age Children.
Journal of the American Dietetic Association, 107(1): 53-61.

C-67

Gabarino, J., and Kosteiny, K. (1993). Neighborhood and Community Influences on Parenting. In T.
Luster and L. Okagaki (Eds.), Parenting: An Ecological Perspective (pp. 203-227). Hillsdale, NJ:
Lawrence Erlbaum Associates, Publishers.
Galaviz, K.I., Zytnick, D., Kegler, M.C., and Cunningham, S.A. (2016). Parental Perception of
Neighborhood Safety and Children’s Physical Activity. Journal of Physical Activity and
Health, 13(10): 1110-1116.
Garrett-Peters, P.T., Mokrova, I., Vernon-Feagans, L., Willoughby, M., Pan, Y., and Family Life Project
Key Investigators. (2016). The Role of Household Chaos in Understanding Relations Between
Early Poverty and Children’s Academic Achievement. Early Childhood Research Quarterly, 37:
16-25.
Gershenson, S., Holt, S. B., and Papageorge, N. W. (2016). Who believes in me? The effect of student–
teacher demographic match on teacher expectations. Economics of education review, 52,
209-224.
Glew, G.M., Fan, M.Y., Katon, W., Rivara, F.P., and Kernic, M.A. (2005). Bullying, Psychosocial
Adjustment, and Academic Performance in Elementary School. Archives Pediatric Adolescent
Medicine, 159(11): 1026-1031.
Goddard, Y. L., Goddard, R. D., and Tschannen-Moran, M. (2007). A theoretical and empirical
investigation of teacher collaboration for school improvement and student achievement in
public elementary schools. Teachers College Record, 109(4), 877-896.
Gonzalez-DeHass, A., Willems, P., and Holbein, M. (2005). Examining the Relationship Between
Parental Involvement and Student Motivation. Educational Psychology Review, 17(2): 99-123.
Gottfried, A.W. (1984). Home Environment and Early Cognitive Development: Integration, MetaAnalyses, and Conclusions. In A.W. Gottfried (Ed.), Home Environment and Early Cognitive
Development (pp. 329-342). Orlando, FL: Academic Press.
Greenwood, C.R. (1991). A Longitudinal Analysis of Time, Engagement, and Achievement in At-Risk
Versus Non-Risk Students. Exceptional Children, 57(6): 521-535.
Greenwood, C.R., Arreaga-Mayer, C., and Carta, J. (1994). Identification and Translation of Effective
Teacher-Developed Instructional Procedures for General Practice. Remedial and Special
Education, 15(3): 140-151.
Gregory, A., and Rimm-Kaufman, S. (2008). Positive Mother-Child Interactions in Kindergarten:
Predictors of School Success in High School. School Psychology Review, 37(4): 499-515.
Gresham, F., and Elliott, S.N. (2008). Social Skills Improvement System Rating Scales. Minneapolis,
MN: Pearson Assessments.
Gresham, F.M., and Elliott, S.N. (1990). Social Skills Rating System Manual. Circle Pines, MN:
American Guidance Service.
Grieco, E., Acosta, Y., de la Cruz, G., Gambino, C., Gryn, T., Larsen, L., Trevelyan, E., and Walters, N.
(2012). The Foreign Born Population of the United States. Washington, D.C: U.S. Bureau of the
Census.

C-68

Grych, J.H., and Fincham, F.D. (1990). Marital Conflict and Children’s Adjustment: A CognitiveContextual Framework. Psychological Bulletin, 108(2): 267-290.
Guarino, C.M., Hamilton, L.S., Lockwood, J.R., and Rathbun, A.H. (2006). Teacher Qualifications,
Instructional Practices, and Reading and Mathematics Gains of Kindergartners (NCES 2006031). U.S. Department of Education. Washington, DC: National Center for Education Statistics.
Han, W. (2010). Bilingualism and Socioemotional Well-Being. Children and Youth Services Review,
32(5): 720-731.
Han, W., and Bridglall, B. (2009). Assessing School Supports for ELL Students Using the ECLS-K.
Early Childhood Research Quarterly, 24(4): 445-462.
Hanushek, E.A. (2002). Evidence, Politics, and the Class Size Debate. In L. Mishel and R. Rothstein
(Eds.), The Class Size Debate. Washington, DC: Economic Policy Institute.
Hart, C.M., and Figlio, D.N. (2015). School Accountability and School Choice: Effects on Student
Selection Across Schools. National Tax Journal, 68(3S): 875-900.
Hart, S., Petrill, S., Deckard, K., and Thompson, L. (2007). SES and CHAOS as Environmental
Mediators of Cognitive Ability: A Longitudinal Genetic Analysis. Intelligence, 35(3): 233-242.
Harter, S. (1999). The Construction of the Self: A Developmental Perspective. New York: Guildford.
Hayes, C., Palmer, J., and Zaslow, M. (Eds.). (1990). Who Cares for America’s Children? Washington,
DC: National Academy Press.
Hearing Loss Association of America. (2018). Hearing Loss Facts and Statistics. Infographic.
Retrieved June 15, 2020, from https://www.hearingloss.org/wpcontent/uploads/HLAA_HearingLoss_Facts_Statistics.pdf?pdf=FactStats.
Hedges, L.V., Laine, R.D., and Greenwald, R. (1994). Does Money Matter? A Meta-Analysis of Studies
of the Effects of Differential School Inputs on Student Outcomes. Educational Researcher,
23(3): 5-14.
Hernandez, M., Valiente, C., Eisenberg, N. Berger, R., Spinrad, T., VanSchyndel, S., Silva, K.,
Southworth, J., and Thompson, M. (2017). Elementary students’ effortful control and
academic achievement: The mediating role of teacher-student relationship quality. Early
Childhood Research Quarterly, 50: 98-109.
Hill, C., and Stafford, F. (1980). Parental Care of Children: Time Diary Estimates of Quantity,
Predictability, and Variety. Journal of Human Resources, 15(2): 219-239.
Hollingsworth, H., and Attansio, C. (2021). School across US brace for surge of kindergartners in fall.
Retrieved June 18, 2021, from https://apnews.com/article/coronavirus-pandemickindergarten-preschool-surge-enrollment95d6ce871622f527f16588c68dff3371?te=1&nl=coronavirusbriefing&emc=edit_cb_20210614.
Horowitz, J. (2020). Lower-income parents most concerned about their children falling behind amid
COVID-19 school closures. Lower-income parents worry kids are falling behind amid school

C-69

closures for COVID-19. Retrieved September 12, 2022, from
https://www.pewresearch.org/fact-tank/2020/04/15/lower-income-parents-mostconcerned-about-their-children-falling-behind-amid-covid-19-school-closures.
Hong, G., and Yu, B. (2007). Early-Grade Retention and Children’s Reading and Math Learning in
Elementary Years. Educational Evaluation and Policy Analysis, 29(4): 239-261.
Hoover-Dempsey, K., and Sandler, H. (1997). Why Do Parents Become Involved in Their Children’s
Education? Review of Educational Research, 67(1): 3.
Hussar, B., Zhang, J., Hein, S., Wang, K., Roberts, A., Cui, J., Smith, M., Bullock Mann, F., Barmer, A., and
Dilig, R. (2020). The Condition of Education 2020 (NCES 2020-144). U.S. Department of
Education. Washington, DC: National Center for Education Statistics. Retrieved July 20, 2020
from https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2020144.
Internal Revenue Service. (2018). Tax Reform Basics for Individuals and Families (5307). U.S.
Department of the Treasury. Washington, DC: Author.
Iruka, I., Gardner-Neblett, N., Telfer, N., Ibekwe-Okafor, N., Currenton, S., Sims, J., Sansbury, A., and
Neblett, E., (2022). Effects of racism on child development: Advancing antiracist
developmental science. Annual Review of Developmental Psychology, 4:1.
Jackson, A., Jeong-Kyun, C., and Franke, T. (2009). Poor Single Mothers With Young Children:
Mastery, Relations With Nonresident Fathers, and Child Outcomes. Social Work Research,
33(2): 95-106.
Jackson, A.P., Bentler, P.M., and Franke, T.M. (2006). Employment and Parenting Among Current
and Former Welfare Recipients. Journal of Social Service Research, 33(2): 13-25.
Jackson, M.T., Mcphee, C.B., and Lavrakas, P.J. (2020). Using Response Propensity Modeling to
Allocate Noncontingent Incentives in an Address-Based Sample: Evidence from a National
Experiment. Journal of Survey Statistics and Methodology, 8(2): 385-411.
Jacobs, J.E., Davis-Kean, P., Bleeker, M., Eccles, J.S., and Malanchuk, O. (2005). I Can, But I Don’t Want
To: The Impact of Parents, Interests and Activities on Gender Differences in Math. In A.
Gallagher and J. Kaufman (Eds.), Gender Differences in Mathematics (pp. 246-263). New York:
Cambridge University Press.
Jeynes, W. H. (2017). A meta-analysis: The relationship between parental involvement and Latino
student outcomes. Education and Urban Society, 49(1), 4-28.
Johnson, A., Martin, A, Brooks-Gunn, J., and Petrill, S. (2008). Order in the House! Associations
Among Household Chaos, the Home Literacy Environment, Maternal Reading Ability and
Children’s Early Reading. Merrill-Palmer Quarterly, 54(4): 445-472.
Judge, S., and Jahns, L. (2007). Association of Overweight With Academic Performance and Social
and Behavioral Problems: An Update From the Early Childhood Longitudinal Study. Journal of
School Health, 77(10): 672-678.
Kadry, D., Ali, S., and Sorour, A. S. (2017). The Role of Parenting Styles in Aggressive Behavior
Among Preschoolers Children at Zagazig City. Zagazig Nursing Journal, 13(2), 86-100.

C-70

Kanaya, T., Wai, J., and Miranda, B. (2019). Exploring the links between receiving special education
services and adulthood outcomes. Frontiers in Education, 4, 56.
doi:10.3389/feduc.2019.00056.
Karweit, N. (1985). Should We Lengthen the School Term? Educational Researcher, 14(6): 9-15.
Kauerz, K. (2005). Full-Day Kindergarten: A Study of State Policies in the United States. Washington,
DC: Education Commission of the States.
Kilgore, S.B., and Pendleton, W.W. (1993). The Organizational Context of Learning: Framework for
Understanding the Acquisition of Knowledge. Sociology of Education, 66(1): 63-87.
Kimbro, R.T., and Denney, J.T. (2015). Transitions Into Food Insecurity Associated With Behavioral
Problems and Worse Overall Health Among Children. Health Affairs, 34(11): 1949-2A.
Klein, A. (2016). The Every Student Succeeds Act: An ESSA Overview. Education Week. Retrieved
July 27, 2020, from http://www.edweek.org/ew/issues/every-student-succeeds-act/.
Klingberg, T., Fernell, E., Olesen, P., Johnson, M., Gustafsson, P., Dahlstrom, K., Gillberg, C.G.,
Forssberg, H., and Westerberg, H. (2005). Computerized Training of Working Memory in
Children With ADHD: A Randomized, Controlled Trial. Journal of the American Academy of
Child and Adolescent Psychiatry, 44(2): 177-186.
Kochenderfer, B. and Ladd, G. (1996). Peer Victimization: Cause or Consequence of School
Maladjustment? Child Development, 67(4): 1305-1317.
Kremer, K.P., and Kremer, T.R. (2019). Bullying Victimization and Disability Status Are Associated
With Television Watching in Adolescence. Journal of Child and Family Studies, 28(12): 34793486.
Krueger, A.B. (2002). Understanding the Magnitude and Effect of Class Size on Student
Achievement. In L. Mishel and R. Rothstein (Eds.), The Class Size Debate. Washington, DC:
Economic Policy Institute.
Kochenderfer, B., and Ladd, G. (1996). Peer Victimization: Cause or Consequence of School
Maladjustment? Child Development, 67(4): 1305-1317.
Ladd, G.W., Buhs, E.S., and Seid, M. (2000). Children’s Initial Sentiments About Kindergarten: Is
School Liking an Antecedent of Early Classroom Participation and Achievement? MerrillPalmer Quarterly. 46(2): 255-279.
Ladd, G.W., and Dinella, L.M. (2009). Continuity and Change in Early School Engagement: Predictive
of Children’s Achievement Trajectories From First to Eighth Grade? Journal of Educational
Psychology, 101(1): 190-206.
LaParo, K.M., and Pianta, R.C. (2000). Predicting Children’s Competence in the Early School Years: A
Meta-Analytic Review. Review of Educational Research, 70(4): 443-484.
Larsen, L.J. (2004). The Foreign-Born Population in the United States: 2003. Current Population
Reports P20-551. Washington, DC: U.S. Bureau of the Census.

C-71

Lee, V., and Burkam, D.T. (2002). Inequality at the Starting Gate: Social Background Differences in
Achievement as Children Begin School. Washington, DC: Economic Policy Institute.
Leithwood, K., Seashore Louis, K., Anderson, S., and Wahlstrom, K. (2004). How leadership influences
student learning. New York: Wallace Foundation.
LeFevre, J., Skwarchuk, S.L., Smith-Chant, B.L., Fast, L., Kamawar, D., and Bisanz, J. (2009). Home
Numeracy Experiences and Children’s Math Performance in the Early School Years. Canadian
Journal of Behavioural Science, 41(2): 55-66.
Li-Grining, C., Votruba-Drzal, E., Maldonado-Carreno, C., and Haas, K. (2010). Children’s Early
Approaches to Learning and Academic Trajectories Through Fifth Grade. Developmental
Psychology, 46(5): 1062-1077.
Lim, H., and Kim, J. (2011). A Longitudinal Study of Children’s Social Behaviors and Their Causal
Relationship to Reading Growth. Asia Pacific Education Review, 12(2): 197-213.
Lo Casale-Crouch, J., Mashburn, A.J., Downer, J.T., and Pianta, R.C. (2008). Pre-Kindergarten
Teachers’ Use of Transition Practices and Children’s Adjustment to Kindergarten. Early
Childhood Research Quarterly, 23:124-139.
Lou, Y., Abrami, P.C., Spence, J.C., Poulsen, C., Chambers, B., and d’Apollonia, S. (1996). Within-Class
Grouping: A Meta-Analysis. Review of Educational Research, 66(4): 423-458.
Ma, X., Shen, J., Krenn, H. Y., Hu, S., and Yuan, J. (2016). A meta-analysis of the relationship between
learning outcomes and parental involvement during early childhood education and early
elementary education. Educational Psychology Review, 28(4), 771-801.
Maccoby, E., and Martin, J. (1983). Socialization in the Context of the Family: Parent-Child
Interaction. In E.M. Hetherington (Ed.), P.H. Mussen (Series Ed.), Handbook of Child
Psychology: Vol. 4. Socialization, Personality, and Social Development (pp.1-101). New York:
Wiley.
Manlove, J. (1993). Multiple Correlates of Burnout in Child Care Workers. Early Childhood Research
Quarterly, 8(4): 499-518.
Manning, D. (2015). Cohabitation and Child Wellbeing. Future Child. 25(2):51-56. Retrieved on June
11, 2020,
from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4768758/pdf/nihms730958.pdf.
Martínez, J., Stecher, B., and Borko, H. (2009). Classroom Assessment Practices, Teacher Judgments,
and Student Achievement in Mathematics: Evidence From the ECLS. Educational Assessment,
14(2): 78-102.
Matheny, A., Wachs, T., Ludwig, J., and Phillips, K. (1995). Bringing Order Out of Chaos:
Psychometric Characteristics of the Confusion, Hubbub and Order Scale. Journal of Applied
Developmental Psychology, 16(3): 429-444.
McCartney, K. (1984). Effect of Quality of Day Care Environment on Children’s Language
Development. Developmental Psychology, 20(2): 244-260.

C-72

McClelland, M.M., Acock, A.C., Piccinin, A., Rhea, S.A., and Stallings, M.C. (2013). Relations Between
Preschool Attention Span-Persistence and Age 25 Educational Outcomes. Early Childhood
Research Quarterly, 28: 314-324.
McClelland, M.M., Cameron, C.E., Connor, C.M., Farris, C.L., Jewkes, A.M., and Morrison, F.J. (2007).
Links Between Behavioral Regulation and Preschoolers’ Literacy, Vocabulary and Math Skills.
Developmental Psychology, 43(4): 947-959.
McClelland, M.M., John Geldhof, G., Cameron, C.E., and Wanless, S.B. (2015). Development and Self‐
Regulation. In R.M. Lerner (Ed.), Handbook of Child Psychology and Developmental Science
(pp.1-43). Hoboken, NJ: John Wiley & Sons.
McCoach, D.B., O’Connell, A.A., and Levitt, H. (2006). Ability Grouping Across Kindergarten Using an
Early Childhood Longitudinal Study. The Journal of Educational Research, 99(6): 339-346.
McCormick, M.C., Gortmaker, S.L., and Sobol, A.M., (1990). Very-Low Birthweight Children: Behavior
Problems and School Difficulty in a National Sample. Journal of Pediatrics, 117(5): 687-693.
McDermott, P.A. (2018). Learning-To-Learn Scales. Philadelphia: Edumetric and Clinical Science.
McDermott, P.A., Fantuzzo, J.W., Warley, H.P., Waterman, C., Angelo, L.E., Gadsden, V.L., and Sekino,
Y. (2011). Multidimensionality of Teachers’ Graded Responses for Preschoolers’ Stylistic
Learning Behavior: The Learning-to-Learn Scales. Educational and Psychological
Measurement, 71: 148-169.
McLoyd, V., and Wilson, L. (1991). The Strain of Living Poor: Parenting, Social Support, and Child
Mental Health. In A.C. Huston (Ed.), Children in Poverty: Child Development and Public Policy
(pp. 105-135). New York: Cambridge University Press.
Medway, R.L., and Tourangeau, R. (2015). Response Quality in Telephone Surveys: Do Prepaid Cash
Incentives Make a Difference? Public Opinion Quarterly, 79: 524-543.
Meisels, S.J., Atkins‐Burnett, S., and Nicholson, J. (1995). Assessment of Social Competence, Adaptive
Behaviors, and Approaches to Learning. Background paper prepared for the Assessment
Technical Review Panel, Early Childhood Longitudinal Study, National Opinion Research
Center.
Mercer, A., Caporaso, A., Cantor, D., and Townsend, R. (2015). How Much Gets You How Much?
Monetary Incentives and Response Rates in Household Surveys. Public Opinion Quarterly, 79:
105-29.
Monte, L. (2020). New Census Household Pulse Survey Shows More Households With Children Lost
Income, Experienced Food Shortages During Pandemic. Washington, DC: U.S. Census Bureau.
Retrieved June 12, 2020, from https://www.census.gov/library/stories/2020/05/adults-inhouseholds-with-children-more-likely-to-report-loss-in-employment-income-during-covid19.html.
Moore, K., Hair, E., Vandivere, S., McPhee, C., McNamara, M., and Ling, T. (2006). Depression Among
Moms: Prevalence, Predictors, and Acting Out Among Third Grade Children. Child Trends
Research Brief, 19: 1-8.

C-73

Moore, K.A., Zaslow, M., Coiro, M.J, Miller, S.M., and Magenheim, F.B. (1995). How Well Are They
Faring? AFDC Families with Preschool-Aged Children in Atlanta at the Outset of the JOBS
Program. Washington, DC: U.S. Department of Health and Human Services.
Moore, K.A., Zaslow, M., Coiro, M.J., and Morrison, D.R. (1993). Tabulations of the National
Longitudinal Survey of Youth-Child Supplement. Unpublished manuscript prepared for OMB
submission for JOBS Observational Study, Washington, DC: Child Trends, Inc.
Morgan, P., Farkas, G., Tufis, P., and Sperling, R. (2008). Are Reading and Behavior Problems Risk
Factors for Each Other? Journal of Learning Disabilities, 41(5): 417-436.
Morgan, P.L., Frisco, M.L., Farkas, G., and Hibel, J. (2010). A Propensity Score Matching Analysis of
the Effects of Special Education Services. The Journal of Special Education, 43(4): 236-254.
Morrow, L.M., Strickland, D.S., and Woo, D.G. (1999). Literacy Instruction in Half- and Whole-Day
Kindergarten: Research to Practice. Newark, DE: International Reading Association.
Moss, K., Dawson, L., Long, M., Kates, J., Musumeci, M. Cubanski, J. and Pollitz, K. (2020). The Families
First Coronavirus Response Act: Summary of Key Provisions. Retrieved July 18, 2020, from
https://www.kff.org/coronavirus-covid-19/issue-brief/the-families-first-coronavirusresponse-act-summary-of-key-provisions.
Moulding, B., R. Bybee, and N. Paulson. (2015). A Vision and Plan for Science Teaching and Learning.
Author: Essential Teaching and Learning Publications.
Mullis, I., Campbell, J., and Farstrup, A. (1993). NAEP 1992 Reading Report Card for the Nation and
the States. Washington, D.C.: National Center for Education Statistics.
Nansel, T., Overpeck, M., Pilla, R.S., Ruan, W.J., Simmons-Morton, B., and Schmidt, P. (2001). Bullying
Behaviors Among U.S. Youth. Journal of American Medical Association, 285: 2094-2100.
National Association for the Education of Young Children. (1998). Learning to Read and Write:
Developmentally Appropriate Practices for Young Children. Young Children 53(4): 30-45.
National Hearing Conservation Association. (2004). Crank It Down. NHCA Task Force on Hearing
Conservation Education for Children and Adolescents, American Academy of Audiology.
Aurora, CO: Author.
Neuman, S.B. (2002). What Research Reveals: Foundations for Reading Instruction in Preschool and
Primary Education. Washington, DC: U.S. Department of Education.
Newacheck, P.W., and Hallfon, N. (1988). Preventive Care Use by School-Aged Children: Differences
by Socioeconomic Status. Pediatrics, 82: 462-468.
Newman, L.F. (1990). Preventable Causes of Learning Impairment. Unpublished manuscript, Brown
University.
Nord, C.W., Brimhall, D., and West, J. (1998). Fathers’ Involvement in Their Children’s School (NCE 98091). U.S. Department of Education, National Center for Education Statistics. Washington, DC:
U.S. Government Printing Office.

C-74

Nystrand M., and Gamoran A. (1991). Instructional Discourse, Student Engagement, and Literature
Achievement. Research in the Teaching of English, 25: 261-290.
Ogletree, C., and Robinson, K. (2016). The K-12 Funding Crisis. Education Week, 35(31): 26-27.
Padilla, C.M., Cabrera, N., and West, J. (2017). The Development and Home Environments of LowIncome Hispanic Children: Kindergarten to Third Grade. Research Brief #2017-37. Bethesda,
MD: National Research Center on Hispanic Children & Families. Retrieved July 17, 2020,
from https://www.hispanicresearchcenter.org/wpcontent/uploads/2019/08/Developmental-Profiles-V21.pdf.
Parker, J.G., and Asher, S.R. (1987). Peer Relations and Later Personal Adjustment: Are LowAccepted Children “At Risk”? Psychological Bulletin, 102: 357-389.
Patterson, G.R., Reid, J., and Dishion, T.J. (1992). Antisocial Boys. Eugene, OR: Castalia.
Peisner-Feinberg, E., Burchinal, M., Clifford, R., Culkin, M., Howes, C., and Kagan, S. (2001). The
Relation of Preschool Child-Care Quality to Children’s Cognitive and Social Developmental
Trajectories Through Second Grade. Child Development, 72(5): 1534-1553.
Pellegrini, A.D., and Bohn, C.M. (2005). The Role of Recess in Children’s Cognitive Performance and
School Adjustment. Educational Researcher, 34(1): 13-19.
Peterson, J.L., and Zill, N. (1986). Marital Disruption, Parent-Child Relationships, and Behavior
Problems in Children. Journal of Marriage and the Family, 48: 295-307.
Pettit, G.S., Laird, R.D., Bates, J.E., and Dodge, K.A. (1997). Patterns of After-School Care in Middle
Childhood: Risk Factors and Developmental Outcomes. Merrill-Palmer Quarterly, 43: 515-538.
Philbin, M.M., Parker, C.M., Hirsch, J.S., and Flaherty, M.G. (2004). Public Libraries: A CommunityLevel Resource to Advance Population Health. Journal of Community Health, 44: 192–199.
Retrieved September 14, 2023 from
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329675/
Pianta, R.C., and Stuhlman, M.W. (2004). Teacher-Child Relationships and Children’s Success in the
First Years of School. School Psychology Review, 33(3): 444-458.
Ponitz, C.C., McClelland, M.M., Matthews, J.M., and Morrison, F.J. (2009). A Structured Observation of
Behavioral Self-Regulation and Its Contribution to Kindergarten Outcomes. Developmental
Psychology, 45(3): 605-619.
Posner, M.I., and Rothbart, M.K. (2006). Educating the Human Brain. Washington DC: American
Psychological Association.
Powell, D.R. (1992). Families and Young Children’s School Readiness. Paper prepared for the National
Center for Education Statistics, Office of Educational Research and Improvement. Washington,
DC: National Center for Education Statistics.
Puckering, C. (1989). Maternal Depression. Journal of Child Psychology and Psychiatry, 30(6): 807817.

C-75

Raffaele Mendez, L. Kim, E., Ferron J., and Woods, B. (2015). Altering School Progression through
Delayed Entry or Kindergarten Retention: Propensity Score Analysis of Long-Term Outcomes.
Journal of Educational Research, 108(3):186-203.
Rathbun, A., and West, J. (2004). From Kindergarten Through Third Grade: Children’s Beginning
School Experiences (NCES 2004-007). U.S. Department of Education, National Center for
Education Statistics. Washington, DC: U.S. Government Printing Office.
Ready, D., LoGerfo, L., Burkam, D., and Lee, V. (2005). Explaining Girls’ Advantage in Kindergarten
Literacy Learning: Do Classroom Behaviors Make a Difference? The Elementary School
Journal, 106(1): 21-38.
Reardon, S., and Portilla, X. (2016). Recent Trends in Income, Racial, and Ethnic School Readiness
Gaps at Kindergarten Entry. AERA Open, 2(3): 1-8. Retrieved June 14, 2020,
from https://journals.sagepub.com/doi/pdf/10.1177/2332858416657343.
Reeves, P. M., Pun, W. H., and Chung, K. S. (2017). Influence of teacher collaboration on job
satisfaction and student achievement. Teaching and Teacher Education, 67, 227-236.
Reczek, C., Spiker, R., Liu, H., and Crosnoe, R. (2016). Family structure and child health: Does the sex
composition of parents matter? Demography, 5: 1605-1630.
Reuben, A., Rutherford, G. W., James, J., Razani, N. (2020). Association of neighborhood parks with
child health in the United States, Preventive Medicine, 141: 1-18. Retrieved September 14,
2023 from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034548/pdf/nihms1681367.pdf.
Rice, J.K. (2002). Making the Evidence Matter: Implications of the Class Size Research Debate for
Policy Makers. In L. Mishel and R. Rothstein (Eds.), The Class Size Debate. Washington, DC:
Economic Policy Institute.
Rideout, V., & Robb, M. B. (2020). The Common Sense census: Media use by kids age zero to eight,
2020. San Francisco, CA: Common Sense Media.
Robers, S., Kemp, J., and Truman, J. (2013). Indicators of School Crime and Safety: 2012 (NCES 2013‐
036/NCJ 241446). National Center for Education Statistics, U.S. Department of Education, and
Bureau of Justice Statistics, Office of Justice Programs, U.S. Department of Justice. Washington,
DC: National Center for Education Statistics.
Roberts, J., Jurgens, J., and Burchinal, M. (2005). The Role of Home Literacy Practices in Preschool
Children’s Language and Emergent Literacy Skills. Journal of Speech, Language, and Hearing
Research, 48(2): 345‐359.
Rose, C.A., and Espelage, D.L. (2012). Risk and Protective Factors Associated With the Bullying
Involvement of Students With Emotional and Behavioral Disorders. Behavioral Disorders,
37(3): 133-148.
Rosenthal, M. (1991). Behaviors and Beliefs of Caregivers in Family Day Care: The Effects of
Background and Work Environment. Early Childhood Research Quarterly, 6: 263-283.

C-76

Rucinski, C.L. (2019). Variation in Exposure to Early Elementary Classroom Racial/Ethnic Diversity
and Child Development in a Nationally Representative Sample (Doctoral dissertation, Fordham
University).
Rueda, M.R., Rothbart, M.K., McCandliss, B.D., Saccomanno, L., and Posner, M.I. (2005). Training,
Maturation, and Genetic Influences on the Development of Executive Attention. Proceedings
from the National Academy of Sciences, 102(41): 14931-14936.
Ruiz-Soto, A., Hooker, S., and Batalova, J. (2015). Top Languages Spoken by English Language
Learners Nationally and by State. Washington, DC: Migration Policy Institute. Retrieved June
11, 2020, from https://www.migrationpolicy.org/research/top-languages-spoken-englishlanguage-learners-nationally-and-state.
Ruopp, R., Travers, J., Glantz, F., and Goelen, C. (1979). Children at the Center: Final Results of the
National Day Care Study. Cambridge, MA: Abt Associates.
Saitadze, I. (2021). Mediating the Effects of Early Childhood Programs and High Quality Home
Environments on the Cognitive Development of Poor Children Involved in the Child Welfare
System. Children Youth and Services Review, 120.
https://doi.org/10.1016/j.childyouth.2020.105736
Santana, C.C.A., Hill, J.O., Azevedo, L.B., Gunnarsdottir, T., and Prado, W.L. (2017). The Association
Between Obesity and Academic Performance in Youth: A Systematic Review. Obesity
Reviews, 18(10): 1191-1199.
Sarampote, N.C., Bassett, H.H., and Winsler, A. (2004). Afterschool Care: Child Outcomes and
Recommendations for Research and Policy. Child and Youth Care Forum, 35: 329-348.
Scarborough, H.S. (2001). Connecting Early Language and Literacy to Later Reading (Dis)abilities:
Evidence, Theory, and Practice. In S.B. Neuman and D.K. Dickinson (Eds.), Handbook of Early
Literacy Research. New York: The Guilford Press.
Schneider, B., and J.S. Coleman. (1993). Parents, Their Children, and Schools. Boulder, CO: Westview
Press.
Schneider, M., and Buckley, J. (2002). What Do Parents Want From Schools? Evidence From the
Internet. Educational Evaluation and Policy Analysis, 24(2): 133-144.
Schulting, A.B., Malone, P.S., and Dodge, K.A. (2005). The Effects of School-Based Kindergarten
Transition Practices on Child Academic Outcomes. Developmental Psychology, 41: 860-871.
Semega, J.L., Fontenot, K.R., and Kollar, M.A. (2017). Income and Poverty in the United States: 2016.
(Report No. P60-259). Current Populations Reports. Retrieved July 27, 2020, from
https://www.census.gov/library/publications/2017/demo/p60-259.html.
Shaefer, H., and Edin, K. (2018). Welfare Reform and the Families It Left Behind. Retrieved June 14,
2020,
from https://inequality.stanford.edu/sites/default/files/Pathways_Winter2018_FamiliesLeft-Behind.pdf.

C-77

Shonkoff, J.P. (1992). Health Care Policy and Part H Services: Early Intervention as a Concept. In J.J.
Gallagher and P.K. Fuller (Eds.), The Coordination of Health and Other Services for Infants and
Toddlers With Disabilities: The Conundrum of Parallel Service Systems. Urbana-Champaign, IL:
University of North Carolina at Chapel Hill.
Shonkoff, J., Slopen, N., and Williams, D. (2021). Early childhood adversity, toxic stress, and the
impacts of racism on the foundation of health. Annual Review of Public Health, 42: 115-134.
Singer, D.G., and Singer, J.L. (2006). Fantasy and Imagination. In D.P. Fromberg and D. Bergen (Eds.),
Play From Birth to 12: Contexts, Perspectives, and Meanings (pp. 371-378). New York:
Routledge.
Singer E., Van Hoewyk J., and Maher M.P. (2000). Experiments with incentives in telephone surveys.
Public Opinion Quarterly, 64(2):171-188.
Singer, E., and Cong, Y. (2013). The Use and Effects of Incentives in Surveys. Annals of the American
Academy of Political and Social Science, 645: 112-141.
Skinner, A. C., Ravanbakht, S. N., Skelton, J. A., Perrin, E. M., and Armstrong, S. C. (2018). Prevalence
of obesity and severe obesity in US children, 1999–2016. Pediatrics, 141(3).
Skinner E.A., Wellborn J.G., and Connell J.P. (1990). What It Takes to Do Well in School and Whether
I’ve Got It: The Role of Perceived Control in Children’s Engagement and School Achievement.
Journal of Educational Psychology, 90(82): 22-32.
Slavin, R.E. (1987). Ability Grouping and Student Achievement in Elementary Schools: A BestEvidence Synthesis. Review of Educational Research, 57(3): 293-336.
Smaldone, A., Honig, J., and Byrne, M. (2007) Sleepless in America: Inadequate Sleep and
Relationships to Health and Well-Being of Our Nation’s Children. Pediatrics, 119(1): S29 -S37.
Snow, C.E., Burns, M.S., and Griffin, P. (1998). Preventing Reading Difficulties in Young Children.
Committee on the Prevention of Reading Difficulties in Young Children. Washington, DC:
National Academy Press.
Society for Research in Child Development. (2018). January 2018 Policy Update. Retrieved July 17,
2020, from https://mailchi.mp/srcd/january-2018-policy-update-1240941?e=23b1c0acc6.
Sonnenschein, S., and Sun, S. (2017). Racial/Ethnic Differences in Kindergartners’ Reading and Math
Skills: Parents’ Knowledge of Children’s Development and Home‐Based Activities as
Mediators. Infant and Child Development, 26(5).
Spreen, T.L., House, L.A., and Gao, Z. (in press). The Impact of Varying Financial Incentives on Data
Quality in Web Panel Surveys. Journal of Survey Statistics and Methodology.
Stähli, E. and Joye, D. (2016). Incentives as a Possible Measure to Increase Response Rates. The
SAGE Handbook of Survey Methodology (pp. 425-440). California: Sage Publications, Ltd.
Stallings, J.A., and Stipek, D. (1986). Research on Early Childhood and Elementary School Teaching
Programs. In M.C. Wittrock (Ed.), Handbook of Research on Teaching (pp. 727-753). New
York: Macmillan Publishing Company.

C-78

Stanley, M., Roycroft, J., Amaya, A., Dever, J.A., and Srivastav, A. (2020). The Effectiveness of
Incentives on Completion Rates, Data Quality, and Nonresponse Bias in a Probability-Based
Internet Panel Survey. Field Methods, 32: 159-179.
Storch, S., and Whitehurst, G. (2001). The Role of Family and Home in the Literacy Development of
Children From Low-Income Backgrounds. New Directions for Child and Adolescent
Development, 92: 53-72.
Stutz, F., Schaffner, E., and Schiefele, U. (2016). Relations Among Reading Motivation, Reading
Amount, and Reading Comprehension in the Early Elementary Grades. Learning and
Individual Differences, 45:101-113.
Sullivan, A. L., Houri, A., and Sadeh, S. (2016). Demography and early academic skills of students
from immigrant families: The kindergarten class of 2011. School Psychology Quarterly, 31(2),
149–162. https://doi.org/10.1037/spq0000137.
Supovitz, J., Sirinides, P., and May, H. (2010). How principals and peers influence teaching and
learning. Educational Administration Quarterly, 46(1), 31-56.
doi:10.1177/1094670509353043.
Sy, S., and Schulenberg, J. (2005). Parent Beliefs and Children’s Achievement Trajectories During the
Transition to School in Asian American and European American Families. International
Journal of Behavioral Development, 29(6): 505-515.
Talbert, J.E., and McLaughlin, M.W. (1994). Teacher professionalism in local school contexts.
American Journal of Education, 102: 123-153.
Tamis-LeMonda, C.S., Luo, R., McFadden, K.E., Bandel, E.T., and Vallotton, C. (2019). Early Home
Learning Environment Predicts Children’s 5th Grade Academic Skills. Applied Developmental
Science, 23(2): 153-169.
Taylor, R.D., Oberle, E., Durlak, J.A., and Weissberg, R.P. (2017). Promoting Positive Youth
Development Through School-Based Social and Emotional Learning Interventions: A MetaAnalysis of Follow-Up Effects. Child Development, 88(4): 1156-1171.
Teddlie, C., Kirby, P., and Stringfield, S. (1989). Effective Versus Ineffective Schools: Observable
Differences in the Classroom. American Journal of Education, 97: 221-236.
Thompson, J. A., and Sonnenschein, S. (2016). Full-day kindergarten and children’s later reading:
The role of early word reading. Journal of Applied Developmental Psychology, 42, 58-70.
Tompson, M., Pierre, C., Boger, K., McKowen, J., Chan, P., and Freed R. (2010). Maternal Depression,
Maternal Expressed Emotion, and Youth Psychopathology. Journal of Abnormal Child
Psychology, 38(1): 105-17.
Ujifusa, A., and Tully, S. (2016). ESSA May Offer Megaphone for Parent, Community Voices:
Advocates See Chance for Greater Impact Under New K-12 Law. Education Week, 35(25): 1.
Retrieved April 25, 2020, from https://www.edweek.org/ew/articles/2016/03/23/essamay-offer-megaphone-for-parent-community.html.

C-79

Umberson, D., and Thomeer, M. (2020). Family Matters: Research on Family Ties and Health, 2010
to 2020. Journal of Marriage and Family, 82: 404-419.
Underwood, M., Beron, K., Gentsch, J., Galperin, M., and Risser, S. (2008). Family Correlates of
Children’s Social and Physical Aggression With Peers: Negative Interparental Conflict
Strategies and Parenting Styles. International Journal of Behavioral Development, 32(6): 549562.
U.S. Department of Agriculture (USDA), Food and Nutrition Service (2020). State Guidance on
Coronavirus Pandemic EBT (P-EBT). Retrieved July 18, 2020, from
https://www.fns.usda.gov/disaster/pandemic/covid-19/maryland#snap.
U.S. Department of Agriculture (USDA), Food and Nutrition Service (2021). Fact Sheet: United States
Department of Agriculture Provisions in H.R. 1319, the American Rescue Plan. Retrieved May 5,
2021, from
https:// www.usda.gov/media/press-releases/2021/03/10/fact-sheet-united-statesdepartment-agriculture-provisions-hr-1319.
U.S. Department of Education, National Center for Education Statistics. (2000). America’s
Kindergartners (NCES 2000-070). By Denton, K., Germino-Hausken, E., and Project Officer,
Jerry West. Washington, DC: Author.
U.S. Department of Education. (2015). The Condition of Education. Washington, DC: Author.
Retrieved July 17, 2020, from https://nces.ed.gov/programs/coe/indicator_cgf.asp.
U.S. Department of Education. (2017). Reimagining the Role of Technology in Education: 2017
National Education Technology Plan Update. Washington, DC: U.S. Department of Education,
Office of Educational Technology.
U.S. Department of Education, National Center for Education Statistics. (2020). The Digest of
Education Statistics, 2019 (NCES 2020-009).
U.S. Department of the Treasury (2020). The CARES Act Work for All Americans. Retrieved July 18,
2020, from https://home.treasury.gov/policy-issues/cares.
U.S. Department of the Treasury (2021). Fact Sheet: The American Rescue Plan Will Deliver
Immediate Economic Relief to Families. Retrieved May 5, 2021, from
https://home.treasury.gov/system/files/136/Fact-Sheet-03-18-21.pdf.
Ventura, S.J. (2009). Changing Patterns of Nonmarital Childbearing in the United States. NCHS data
brief, no. 18. Hyattsville, MD: National Center for Health Statistics.
Walston, J., and West, J. (2004). Full-Day and Half-Day Kindergarten in the United States: Findings
From the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99. (NCES 2004078). Washington, DC: National Center for Education Statistics.
Wang, M., Haertel, G., and Walberg, H. (1990). What Influences Learning? A Content Analysis of
Review Literature. Journal of Educational Research, 84: 30-43.

C-80

Waters, T., Marzano, R. J., and McNulty, B. (2003). Balanced leadership: What 30 years of research
tells us about the effect of leadership on student achievement. Aurora, CO: Mid-Continent
Research for Education and Learning.
Webb, N., and Lowther, M. (1993). Organizational Commitment of Child Care Providers Employed in
Centre Facilities. Journal of Child and Youth Care, 8: 1-16.
Weeland, J., Keijsers, L. and Byrne, S. (2021) Introduction to the Special Issue: Parenting and Family
Dynamics in Times of the COVID-19. Developmental Psychology, 57: 1559-1562.
Wilkinson, S. (2017). Mathematics development in Spanish-speaking English language learners. PhD
(Doctor of Philosophy) thesis, University of Iowa. Retrieved July 27, 2020, from
https://ir.uiowa.edu/cgi/viewcontent.cgi?article=7356&context=etd.
Williams, D., Brick, J.M., Montaquila, J.M., and Han, D. (2016). Effects of Screening Questionnaires on
Response in a Two-Phase Postal Survey. International Journal of Social Research
Methodology, 19: 51-67.
Wimberley, C. E. (2011). Teacher collaboration and student achievement (Doctoral dissertation,
Lindenwood University).
Witte, J. (2001). The Market Approach to Education: An Analysis of America’s First Voucher Program.
Princeton, NJ: Princeton University Press.
Wolf, S., Magnuson, K., and Kimbro, R. (2017). Family Poverty and Neighborhood Poverty: Links
With Children’s School Readiness Before and After the Great Recession. Children and Youth
Services Review, 79: 368-384. Retrieved June 15, 2020,
from https://scholarship.rice.edu/bitstream/handle/1911/107874/nihms984695.pdf?sequence=1.
Xue, Y., and Meisels, S.J. (2004). Early Literacy Instruction and Learning in Kindergarten: Evidence
From the Early Childhood Longitudinal Study – Kindergarten Class of 1998-1999. American
Educational Research Journal, 41 (4): 191-229.
Yoshikawa, H., Weiland, C., Brooks-Gunn, J., Burchinal, M.R., Espinosa, L.M., Gormley, W.T., Ludwig,
J., Magnuson, K.A., Phillips, D., and Zaslow, M.J. (2013). Investing in Our Future: The Evidence
Base on Preschool Education. New York: Foundation for Child Development.
Zhou, Q., Hofer. C., Eisenberg, N., Reiser, M., Spinrad, T., and Fabes, R (2007). The developmental
trajectories of attention focusing, attentional and behavioral persistence, and externalizing
problems during school-age years. Developmental Psychology,43(2):369-85.
Zosh, J. M., Hopkins, E. J., Jensen, H., Liu, C., Neale, D., Hirsh-Pasek, K., Solis, S. L., & Whitebread, D.
(2017). Learning through play: a review of the evidence (white paper). The LEGO Foundation,
DK.
Zill, N., Moore, K.A., Smith, E.W., Stief, T., and Coiro, M.J. (1991). Life Circumstances and Development
of Children in Welfare Families: A Profile Based on National Survey Data. Washington, DC: Child
Trends, Inc.

C-81


File Typeapplication/pdf
File Modified2024-04-25
File Created2024-04-25

© 2024 OMB.report | Privacy Policy