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The Contribution of Teachers’ Emotional Support to
Children’s Social Behaviors and Self-Regulatory Skills in
First Grade
Eileen G. Merritt, Shannon B. Wanless, Sara E. Rimm-Kaufman, and
Claire Cameron
University of Virginia
James L. Peugh
Cincinnati Children’s Medical Center
Abstract. The present observational study used hierarchical linear modeling to
examine predictors of children’s social and self-regulatory outcomes in first-grade
classrooms. Specifically, goals were the following: (1) to explore relations be-
tween emotionally supportive teacher– child interactions and children’s social
behaviors (aggression with peers, exclusion by peers, prosocial behaviors) and
self-regulatory skills (behavioral self-control); and (2) to examine whether emo-
tionally supportive teacher–student interactions contributed differentially to social
and self-regulatory outcomes for first-graders at risk for school difficulty based on
sociodemographic characteristics compared to counterparts with fewer sociode-
mographic risk characteristics. Participants were 178 students and 36 teachers in
seven rural schools. Results indicated higher teacher emotional support related to
lower child aggression and higher behavioral self-control. Emotional support was
equally important for all children regardless of the number of sociodemographic
risk factors. Results provide evidence for the contribution of teacher behaviors to
students’ social behaviors and self-regulatory skills, and suggest the importance
of classroom interactions in children’s acquisition of social and emotional com-
petence. Discussion focuses on plausible mechanisms and implications for inter-
ventions.
First-grade children require a variety of
skills to meet the complex demands in class-
rooms. During a typical hour of instruction, a
first-grader may be required to work coopera-
tively with a group of peers, pay attention for
an extended period to a whole group lesson,
This work was supported by a National Science Foundation Grant (0418469) to the third author. Also,
Institute of Education Sciences U.S. Department of Education awards R305B040049 and R305B09002 for
predoctoral training to the University of Virginia supported the work of the first author, and Institute of
Education Sciences Grant R305B060009 supported the work of the fourth author. The opinions expressed
are those of the authors and do not represent the views of the funding agencies. We thank Bess Romberg,
Stacy Klein, and our participating principals teaching students and families.
Correspondence regarding this article should be addressed to Eileen Merritt, Social Development Labo-
ratory, 350 Old Ivy Way Suite 300, Charlottesville, VA 22903; e-mail: egm8e@virginia.edu
Copyright 2012 by the National Association of School Psychologists, ISSN 0279-6015
School Psychology Review,
2012, Volume 41, No. 2, pp. 141–159
141
wait for a turn to speak, and work indepen-
dently on an assignment with minimal adult
support. Social and self-regulatory skills that
allow children to build friendships, manage
their behaviors, and work well with others are
needed, in part, to support learning in class-
room settings. However, many children begin
their schooling with significant deficits in im-
portant behavioral skills (Rimm-Kaufman, Pi-
anta, & Cox, 2000; McClelland, Morrison, &
Holmes, 2000), which can have long-term
consequences for children’s engagement in
school and academic achievement (Ladd &
Dinella, 2009).
The quality of teacher– child interac-
tions is particularly important to children’s
social and self-regulatory development (Birch
& Ladd, 1998; Pianta & Stuhlman, 2004).
Although others have examined the impor-
tance of emotional support (Wilson, Pianta, &
Stuhlman, 2007), the contribution of emo-
tional support to child outcomes has typically
not been isolated from teachers’ classroom
management. Examining the unique contribu-
tion of emotional support, above and beyond a
teacher’s ability to manage student behavior,
could offer insight into how teachers’ sensi-
tive, responsive, and positive interactions with
their first-grade students socialize children and
contribute to children’s behaviors and skills
that are particularly relevant to first-grade
adjustment.
Classroom Social Behaviors
Early social behaviors such as aggres-
sion with peers, exclusion by peers, and proso-
cial behavior have important consequences for
children’s later social development and expe-
riences. Young children who exhibit aggres-
sion are more likely than their peers to exhibit
serious conduct problems during adolescence
and are at risk for a variety of problems later
such as delinquency, conduct problems, and
dropping out of school (Ensminger & Slusar-
cick, 1992; Khatri, Kupersmidt, & Patterson,
2000, Miller-Johnson, Coie, Maumary-Gre-
maud, & Bierman, 2002). Patterns of aggres-
sion with peers are often stable and difficult to
change (Broidy et al., 2003). Kindergarteners
who were reported by teachers to exhibit ex-
ternalizing problems, including aggression,
were more likely to show externalizing behav-
ior trajectories through third grade (Silver,
Measelle, Armstrong, & Essex, 2005). Fur-
ther, kindergarteners who were reported to be
aggressive with their peers were more likely to
suffer chronic peer abuse and exclusion by
peers throughout elementary school (Buhs,
Ladd, & Herald, 2006).
Exclusion is one form of maltreatment
by peers that reflects children’s experience of
nonaggressive rejecting behaviors. Peer exclu-
sion measures how often children are ignored
or avoided within the classroom context (Buhs
et al., 2006). Children who are excluded by
peers may be interested in social contact, but
often play alone because peers will not interact
with them (Rubin & Asendorpf, 1993). Exclu-
sion by peers may limit social interaction and
isolate children from future social learning
opportunities (Ladd & Profilet, 1996; Oden &
Asher, 1977). Buhs and others (2006) con-
ducted a longitudinal study of social relation-
ships during elementary grades (kindergarten
through fifth grade) and found that children
who were chronically excluded throughout
their elementary years were more likely to
exhibit increased disengagement in school
over time. Moreover, children who were not
accepted by peers in kindergarten were less
likely to show increases in achievement during
Grades 3–5 than children who were accepted
by peers.
In contrast to aggression or exclusion,
prosocial behaviors refer to proactive and re-
active responses to the needs of others that
promote well-being (Hastings, Utendale, &
Sullivan, 2007). For instance, children who
help other children or show concern when
other children are upset demonstrate prosocial
behaviors. Children who exhibit prosocial be-
haviors have higher social competence and are
more accepted by peers than children who
exhibit fewer prosocial behaviors (Katz & Mc-
Clellan, 1997). Prosocial behaviors appear to
originate from a combination of genetic and
environmental influences (Deater-Deckard et
al., 2001; Scourfield, John, Martin, & McGuf-
fin, 2004).
School Psychology Review, 2012, Volume 41, No. 2
142
Taken together, teachers’ reports of their
students’ aggression, exclusion by peers, and
prosocial behaviors offer insight into chil-
dren’s social experience in school. Although
these social behaviors have been shown to be
somewhat stable over time (e.g., Broidy et al.,
2003; Buhs et al., 2006; Knafo & Plomin,
2006), socialization experiences can shift chil-
dren’s trajectory in relation to these behaviors.
Behavioral Self-Control
Behavioral self-control refers to the
ability to intentionally change one’s behaviors
and exhibit a nondominant response instead of
one that is dominant (Baumeister, Vohs, &
Rice, 2007). This skill differs from classroom
social behaviors in that it reflects children’s
capacity to manage behavior in situations with
and without peers. Behavioral self-control
helps children behave in socially acceptable
ways, laying the groundwork for children to
build and maintain strong social relationships
(Rudasill & Rimm-Kaufman, 2009). Further,
behavioral self-control is a foundational pro-
cess in classroom learning and could have
implications for later achievement (Clark,
Pritchard, & Woodward, 2010; Duncan et al.,
2007).
Children with poor behavioral self-con-
trol are more likely to experience concurrent
and sustained academic difficulty (Blair &
Razza, 2007; Galindo & Fuller, 2010; McClel-
land, Acock, & Morrison, 2006; Ponitz, Mc-
Clelland, Matthews, & Morrison, 2009; Wan-
less, McClelland, Acock et al., 2011), and are
less likely to graduate from high school and
college (McClelland, Piccinin, & Stallings,
2012; Pagani et al., 2008). Moreover, early
difficulties with self-control have been shown
to be relatively stable for many children (Wan-
less, McClelland, Tominey, & Acock, 2011),
suggesting that teachers and school psycholo-
gists need to address issues of low self-control
early to avoid subsequent problems.
Classroom Influences on Social
Behaviors and Self-Regulatory Skills
Caregivers of young children play a crit-
ical role in establishing early patterns of be-
havior and self-control (Bronson, 2000,
Rimm-Kaufman, Curby, Grimm, Nathanson,
& Brock, 2009). In early childhood, parental
influences are important predictors of exter-
nalizing behaviors such as aggression (e.g.,
Moffitt & Caspi, 2007). Once children enter
school, teacher– child relationships become
a factor that influences development. First
grade represents an important period for
children’s academic and social learning (En-
twisle & Alexander, 1998), and teachers
play a prominent role in social development
for this age group (Alexander, Entwisle, &
Dauber, 1993).
Vygotsky’s sociocultural theory posits
that development cannot be separated from its
social context. Applied to a classroom context,
teachers can provide social experiences that
shape the ways that children learn and develop
(Bodrova & Leong, 2007). Vygotsky’s (1978)
Zone of Proximal Development applies to
young children’s learning of social and self-
regulatory skills behaviors. In the presence of
a caring and sensitive adult, “what the child is
able to do in collaboration today he will be
able to do independently tomorrow ” (Vy-
gotsky, 1987, p. 211). Based on Vygotskian
theory, interactions that provide emotional
support and behavior management during the
first years of school year may scaffold chil-
dren’s growth in social and self-regulatory
competence.
Emotionally Supportive Teacher–Child
Interactions
Emotionally supportive teachers, by def-
inition, can be observed as warm and kind,
sensitive to the social and emotional needs of
each child, and thoughtful about the way they
respond to children. They offer gentle guid-
ance to students, engage in positive commu-
nication with students, and demonstrate re-
spect for children through eye contact, re-
spectful language, and a warm and calm voice
(Pianta, LaParo, & Hamre, 2008). For exam-
ple, in a classroom with a high positive cli-
mate, teachers show frequent positive affect
displays toward students, encourage students
to be kind and caring to one another, appear
Teachers’ Emotional Support to Children
143
encouraging in their feedback about behavior
or schoolwork, demonstrate their understand-
ing of individual children’s likes and dislikes,
and create opportunities in the classroom for
children to voice their views and ideas (Pianta,
LaParo, & Hamre, 2008). In contrast, emo-
tionally supportive teachers do not display
controlling behaviors, criticize students, or use
sarcastic language or punitive approaches to
discipline; all behaviors that, by definition,
indicate the presence of a negative classroom
climate (National Institute of Child Health and
Human Development Early Child Care Re-
search Network [NICHD- ECCRN], 2002; Pi-
anta & Hamre, 2009). Recent large-scale stud-
ies of classrooms show that many American
children experience classroom environments
that do not offer high emotional support,
which may have negative consequences for
the social development of children (Pianta,
Belsky, Houts, & Morrison, 2007; Stuhlman
& Pianta, 2009). As a result, there is a need
for research on the potential contribution of
emotional support to social and self-regula-
tory outcomes to inform classroom-level in-
terventions designed to promote optimal so-
cial and emotional development for all
children.
The construct of emotional support can
be measured observationally in a variety of
ways. In earlier work, the Classroom Obser-
vation System for First Grade (COS-1; Na-
tional Institute of Child Health and Human
Development Early Child Care Research Net-
work, 2002) assessed emotional support by
examining classroom management, overcon-
trol, positive emotional climate, negative emo-
tional climate, and sensitivity/responsivity.
The Classroom Assessment Scoring System
(CLASS; Pianta, LaParo, & Hamre, 2008)
measures emotional support by examining
positive climate, negative climate, teacher sen-
sitivity, and regard for student perspectives.
These four dimensions observed regularly
over the course of the school year provide an
indicator of the emotional supportive interac-
tions that occur between teachers and students
in classrooms.
Teachers’ Emotional Supportiveness and
Children’s Social and Self-Regulatory
Outcomes
Previous research established associa-
tions between emotional support and chil-
dren’s positive social behaviors and self-reg-
ulatory skills. However, many studies examine
the contribution of emotional support in com-
bination with instructional support or aspects
of classroom management. For example, in a
study of 14 first-grade classrooms, higher ob-
served teacher emotional and instructional
support was associated with more positive in-
terpersonal behavior and less intrapersonal be-
havior problems in the spring (Perry, Dono-
hue, & Weinstein, 2007). Moreover, in an
examination of data from the NICHD Study of
Early Child Care and Youth Development,
Wilson and others (2007) found that children
in classrooms with high emotional support and
evaluative feedback (defined as feedback chil-
dren receive about their work, behavior, or
ideas) showed significantly better social com-
petence and teacher-reported self-control than
children in classrooms with low observed
emotional support. In a study conducted in
preschool classrooms, emotionally supportive
interactions predicted teacher-reported social
competence using a broad measure of social
skills (Mashburn et al., 2008).
Teacher-reported measures of teacher–
child closeness also assess teacher sensitivity
and warmth and are related to student social
behaviors and self-regulatory outcomes. More
teacher– child closeness in kindergarten re-
lated to declines in externalizing behaviors
over time, suggesting the importance of posi-
tive early teacher–student relationships (Silver
et al., 2005). Furthermore, young children ex-
hibited more prosocial behavior when their
teachers showed warmth and when their rela-
tionship with their teacher was unconflicted
and close (Birch & Ladd, 1998; Howes, 2000;
Kienbaum, 2001). Thus, proximal classroom
experiences that include positive and sensitive
teacher– child interactions may be critical for
children to learn positive social behaviors and
self-regulatory skills.
School Psychology Review, 2012, Volume 41, No. 2
144
Teacher Emotional Support as a
Potential Moderator
Emotionally supportive teacher– child
interactions may not be equally consequential
for all children. Sociodemographic risks are
social constructs linked to negative outcomes
for children (McLoyd, 1998). Specifically,
single parenthood, minimal maternal educa-
tion, and low socioeconomic status are all
considered family risk factors that contribute
cumulatively to outcomes such as children’s
problem behavior, poor mental health, and low
academic performance (e.g., Morales &
Guerra, 2006; Sameroff, Bartko, Baldwin,
Baldwin, & Seifer, 1998). The effect of low
family income on child outcomes appears
strongest during preschool and early child-
hood years (Duncan & Brooks-Gunn, 1997),
showing the importance of focusing on early
experiences to mitigate risk.
Sociodemographic risk factors do not
necessarily have deleterious outcomes for all
children. Teachers’ support for children’s pos-
itive social behaviors and self-regulatory skills
and teachers’ emotional support in the class-
room may compensate for limited family and
social resources (Brody, Dorsey, Forehand, &
Armistead, 2002). For example, longitudinal
studies show how emotional support is more
important for young children with high func-
tional risks (defined as some combination of
early behavioral, attentional, social, and/or ac-
ademic problems). Specifically, students con-
sidered functionally at risk at the end of kin-
dergarten had achievement scores and teach-
er– child relationships that were similar to
their low-risk peers when they were in class-
rooms with teachers who offered strong emo-
tional support in first grade (Hamre & Pianta,
2005).
The Current Study
Our study examined the effects of ob-
served emotionally supportive teacher– child
interactions on teacher-reported social behav-
iors and self-regulatory skills in first-grade
classrooms. As stated earlier, emotional sup-
port contributes to positive social behavior and
self-regulatory skill development even after
taking teachers’ ability to manage their class-
rooms under consideration. Thus, we used
teacher ratings of student behaviors and skills
in the current study, but recognized that teach-
ers saw students in a variety of school contexts
throughout the year, and may have been more
skilled at judging aspects of children’s behav-
ior and skills than peers or observers (Ladd &
Profilet, 1996; Coie & Dodge, 1988). Three
research questions were addressed. First, to
what extent do emotionally supportive teach-
er– child interactions over the course of the
school year relate to children’s more positive
social behaviors at the end of the first-grade
year? We hypothesized that the presence of an
emotionally supportive teacher would be as-
sociated with lower levels of aggressive be-
haviors, less exclusion from peers, and more
prosocial behaviors. Second, how does ob-
served teacher emotional support relate to
children’s improved behavioral self-control?
We hypothesized that higher levels of emo-
tional support would predict greater behav-
ioral self-control. Third, how does observed
emotional support differentially relate to chil-
dren’s behaviors and skills based on children’s
exposure to family sociodemographic risk?
We hypothesized that teacher emotional sup-
port would be more strongly related to positive
social behaviors and self-regulatory skills for
children exposed to more risk factors (based
on family sociodemographic indicators) com-
pared to children with fewer risk factors.
Method
Participants
The participants for the current study
were 178 first-grade children, 53% of whom
were boys and 47% were girls. The mean age
was 6.47 years (SD ⫽ 0.30 years); demo-
graphic breakdown included 81% Caucasian
students, 13% African American students,
and 3% students who were classified as
other. The majority of participants’ parents
held a high school diploma as the highest
degree obtained (n ⫽ 123, 71% mothers;
n ⫽ 102, 59% fathers), reported an annual
combined family income above $30,000
(n ⫽ 54, 69%), and were married or had a
Teachers’ Emotional Support to Children
145
partner (n ⫽ 127, 73%), as reported upon
kindergarten recruitment.
Teacher participants included 36 fe-
male first-grade teachers who were licensed
and state-certified teachers and held be-
tween 2 and 30 years of teaching experience
(M ⫽ 14.57 years, SD ⫽ 8.8 years). Child
and teacher participants were recruited from
seven rural schools in the southeastern
United States following the procedures de-
scribed below.
All parents and children attending kin-
dergarten registration and open house at seven
rural schools were invited to participate in a
2-year longitudinal study. Parents of 333 kin-
dergarten children completed a sociodemo-
graphic questionnaire and consented to partic-
ipate, representing approximately 60% of fam-
ilies registering for kindergarten prior to the
first day of school. Child participants were
selected from the initial 333 children so that
4 – 6 children per classroom were selected and
the demographic variables matched the initial
sample. Chi-squared analyses confirmed no
systematic differences between selected and
nonselected children in terms of child gender,
2
(1,314) ⫽ 0.001, p ⬎ .05, or ethnicity,
2
(1,312) ⫽ 2.93, p ⬎ .05. Maternal education
did not differ significantly, F(1,309) ⫽ 3.52,
p ⫽ .06.
Approximately 19% of the children
(n ⫽ 33) left the study schools between the
kindergarten and first-grade year. Thus, 33
additional children were enrolled in the study
at the fall of first grade from the original 333
children whose families consented prior to
kindergarten in order to increase sample size
and statistical power. Selection of additional
children followed the same considerations as
the kindergarten year, which resulted in the
final sample of 178 first-grade child partici-
pants, 5 of whom did not have complete data.
Those with incomplete data were similar to
those with complete data in terms of gender,
age, race, maternal education, income, and
parent marital status. Sociodemographic data
for this study are reported from the beginning
of the kindergarten year.
Measures
Independent variables included child
age, gender, and family sociodemographic
characteristics; early classroom adjustment;
classroom behavior management; and emo-
tionally supportive teacher– child interactions.
Dependent variables consisted of classroom
social behaviors and self-regulatory skills in-
cluding aggression with peers, exclusion by
peers, prosocial behaviors, and behavioral
self-control.
Sociodemographic risk. Three risk
factors were selected from the family survey
to include in a risk composite because of their
relation to poor developmental outcomes (e.g.,
Bradley & Corwyn, 2002): maternal education
(risk ⫽ 1 if mothers obtained a high school
degree or less), family income (risk ⫽ 1if
income was less than $30,000 per year), and
parents’ marital status (risk ⫽ 1 for parents
who were unmarried or did not have a part-
ner). The income-level amount was selected
by the eligibility criteria for free or reduced-
price lunch for a three-person family in the
local area. Each response was given a score
of 1 if the risk factor was present anda0ifthe
risk factor was absent. These three items were
averaged to form a single indicator of cumu-
lative sociodemographic risk (0 ⫽ no risk
factors were present to 1 ⫽ all three risk
factors were present). In our sample, 34.68%
of the children had 1 risk factor, 23.7% had 2
risk factors, and 15.03% had all 3 risk factors.
Table 1 provides more detailed descriptions of
the students in our sample.
Early classroom adjustment. Teach-
ers rated children’s difficulty adjusting to first
grade in the first 3 weeks of school using a
brief measure of behavior, social, and aca-
demic difficulty adapted from the National
Center for Early Development and Learning
Transition Practices Survey (1996; Rimm-
Kaufman et al., 2000). The original measure
included 12 items, and had teachers estimate
the number of students in their class experi-
encing difficulty in a specific area. The mea-
sure was modified to pertain to skills of indi-
School Psychology Review, 2012, Volume 41, No. 2
146
vidual students (see Nathanson, Rimm-Kauf-
man, & Brock, 2009, for a description). In our
study, teachers rated each individual study
child on 11 items using a 5-point scale, with
higher scores indicating more early adjustment
difficulty. Examples include “has shown dif-
ficulty respecting my authority as a teacher,”
“lacks academic skills,” and “shows difficulty
getting along with other children.” A compos-
ite of the 11 items was computed to represent
the construct of adjustment to first grade. The
decision to create this composite was based on
the high alpha (␣⫽.90), the theoretical basis
for the measure, and previous work reporting
that poor adjustment in the fall of first grade
predicted lower self-control and lower math
scores in the spring of first grade (Ponitz,
Rimm-Kaufman, Brock, & Nathanson, 2009).
Teacher– child interaction quality.
The CLASS was used to assess teacher– child
interaction quality in elementary classrooms.
The CLASS measure initially used a theoret-
ical framework that suggested three domains
of teacher– child interactions including emo-
tional support, classroom organization, and in-
structional support, which were later sup-
ported empirically by confirmatory factor
analyses that showed adequate internal consis-
tency for three domains in multiple samples
(Pianta, La Paro, & Hamre, 2008). Emotional
support (i.e., positive climate, negative climate
reversed, teacher sensitivity, and regard for
student perspectives) and behavior manage-
ment, a dimension within the domain of class-
room organization, were selected for the cur-
rent study based on theoretical and empirical
rationales described previously. Training for
CLASS coders occurred during a 2-day inter-
active session. After reaching a gold standard
of 80% within 1 point of master codes for five
10-min segments, observers rated classroom
quality in five 20-min observation cycles on
each of the 3–5 separate days (mode ⫽ 5 days)
over the entire year. Observers also rated three
additional 10-min video segments to check for
drift at three different time points during the
data collection process and obtained reliability
of 87% or higher. Accumulated research on
the CLASS indicates that ratings obtained
from several observation days over the year
(i.e., more than 2 but not more than 4) give
reliable and consistent indicators of classroom
quality, which predict meaningful variance in
child outcomes (Mashburn et al., 2008; Pianta,
La Paro, & Hamre, 2008).
CLASS dimensions were rated on a
7-point scale with 1 indicating low quality
and 7 indicating high quality. Scores from
items within each domain were averaged (␣⫽
.88 for emotional support), and then construct
scores from all cycles were averaged to create
one classroom composite for emotional sup-
port and one for behavioral management.
Classroom emotional support. The
emotional support domain assesses teachers’
interactions with children in four dimensions.
Positive climate refers to the emotional con-
nection, respect, and enjoyment demonstrated
between teachers and students and among stu-
dents. Classrooms rated as high for positive
climate show evidence that the teacher and
Table 1
Descriptive Statistics for Family
Sociodemographics (
N
ⴝ 178)
Risk Percentage
Household Income
Less than 10,000 8%
15–29,000 25%
30–45,000 21%
45–60,000 13%
60–75,000 17%
75–90,000 8%
90,000 and above 9%
Education
Less than a high school diploma 6%
High school diploma or equivalent 64%
Associate’s degree 11%
Bachelor’s degree 13%
Master’s degree or above 6%
Marital Status (mother)
Married 73%
Single 27%
Note. Students considered at risk for a given category are
in bold.
Teachers’ Emotional Support to Children
147
students enjoy warm and supportive relation-
ships with one another. In these classrooms,
frequent positive interactions and displays of
positive affect are exhibited. The second di-
mension, negative climate, measures the pres-
ence and level of negativity (anger, hostility,
or aggression) exhibited by teachers and/or
students. Evidence of negative climate may
include consistent irritability, anger, yelling,
threatening, or sarcasm. Teacher sensitivity
measures teachers’ awareness of and respon-
siveness to students’ academic and emotional
concerns. A sensitive teacher shows aware-
ness of students who need extra support or
attention, matches her support to students’
needs and abilities, and addresses students’
problems and concerns. In a classroom with a
sensitive teacher, the students appear comfort-
able seeking support from, sharing their ideas
with, and responding to questions from the
teacher. Regard for student perspectives mea-
sures the degree to which teachers’ interac-
tions with students and activities emphasize
students’ interests, motivations, and points of
view. A teacher who scores high for this di-
mension is flexible, goes along with students’
ideas, and organizes instruction around stu-
dents’ interests. The teacher provides consis-
tent support for student autonomy and leader-
ship, provides opportunities for student talk
and expression, and allows freedom of move-
ment and placement during activities. We re-
versed negative climate and then averaged the
four dimensions of emotional support. Higher
scores indicate a more emotionally supportive
teacher.
Classroom behavior management.
Behavior management reflects a teachers’ ap-
proach to handling classroom behavior. A
high score on behavior management indicates
that a teacher sets clear behavior expectations,
takes a proactive approach to preventing prob-
lems, and redirects misbehavior effectively.
Students frequently comply with teacher re-
quests in a well-managed classroom, and their
instances of misbehavior are absent or
infrequent.
Classroom social behaviors. Teachers
completed two surveys per child to assess four
classroom social and self-regulatory
outcomes.
Social behaviors. Teachers rated chil-
dren’s social behaviors using an adapted ver-
sion of the Child Behavior Scale (Ladd &
Profilet, 1996). The Child Behavioral Scale
has established reliability and validity in pre-
dicting student social outcomes. As one exam-
ple, children rated by their teachers as high on
the aggressive with peers subscale were ob-
served concurrently as more aggressive. Scale
items were rated using a 3-point scale (1 ⫽
does not apply,2⫽ applies sometimes,3⫽
definitely applies). The validation work (Ladd
& Profilet, 1996) used principal-components
analysis and established six factors that ac-
counted for 70% of the item variance. In the
present study, we examined three dimensions
of the scale: aggressive with peers, excluded
by peers, and prosocial behaviors. Aggressive
with peers was measured with 4 items includ-
ing “bullies other children” and “is an aggres-
sive child” (␣⫽.91). Excluded by peers in-
cluded 4 items such as “not much liked by
other children” and “not chosen as a playmate
by peers” (␣⫽.85). Prosocial behaviors in-
cluded 4 items such as “helps other children”
and “seems concerned when others are dis-
tressed” (␣⫽.90).
Behavioral self-control. Teachers re-
ported on children’s behavioral self-control
using the Teacher’s Self-Control Rating Scale.
The scale was developed and validated using
observational work in classrooms (Humphrey,
1982). Humphrey found that behavioral self-
control was related to school adjustment and
achievement for fourth- and fifth-grade stu-
dents. Humphrey’s original 5 items measuring
behavioral self-control showed strong reliabil-
ity (␣⫽.91) for the present sample, which
were similar to results in the original sample
(␣⫽.88). Items include “talks out of turn,”
“disrupts other students when they are doing
things,” and “gets into fights or arguments
with other children.” Teachers used a 5-point
Likert-type scale to rate students on each be-
School Psychology Review, 2012, Volume 41, No. 2
148
havior. Almost never (1) indicated that the
behavior was rarely observed and very often
(5) meant the behavior was observed fre-
quently. A composite (mean) was created and
reversed so that higher scores indicated greater
behavioral self-control.
Procedures
Data for this study were gathered from
three sources: parents, first-grade teachers, and
classroom observations conducted by research
assistants. First, parents completed brief de-
mographic questionnaires at kindergarten en-
rollment. Later, first-grade teachers rated stu-
dent participants on their adjustment to school
after the first 3 weeks of school. In the spring
of first grade, teachers also rated students on
three social behaviors (aggression, rejection
by peers, and prosocial behavior) and behav-
ioral self-control. Classroom observations
were made throughout the first-grade school
year, as described in the following.
Research assistants blind to the purpose
of the study conducted three to five classroom
observations for each teacher. These occurred
throughout the year within the first 2.5 hr of
the school day. Typically, two observations
were conducted in the fall observation window
(October to December), two were conducted
in the winter observation window (January to
March), and one observation was conducted in
the spring observation window (March to
May). Child observational data were based
on 50 min over the course of the year (on at
least 3 separate days with 1 day per observa-
tion window) and teacher emotional support
composites were based on 300 –375 min of
teacher observation (on at least 3 separate days
with 1 day per observation window). The first
half of the school day was selected for obser-
vation to ensure content consistency across
classrooms and to include literacy instruction,
which was designated to the morning and was
viewed by teachers in the sample as the pri-
mary focus of first grade. Observations were
scheduled for the “typical day”—that is, when
the regular teacher was present and no special
activities or disruptions were expected.
Analytic Strategy
Analyses for the first two research ques-
tions, those examining main effects of class-
room emotional support on children’s social
behaviors and self-regulatory skills, were con-
ducted in four steps for each dependent
variable.
Step 1. Descriptive statistics and bivari-
ate correlations were used to examine missing
data, model assumptions, and associations
among independent and dependent variables.
Model assumptions, including checking for
outliers, linearity, and normality, were tested
and found to be met. One outlier was detected
for aggression and excluded behaviors. Data
were examined and each of the outliers fell
within the expected range of the data; removal
of the outlier did not change the significance
of the results, so outliers were retained. Miss-
ing data for all variables was handled using the
Bayesian estimator in MPlus. Similar to full
information maximum likelihood, the Bayes-
ian estimator uses all available data to estimate
parameters. Bayesian estimation was chosen
since it can provide more accurate estimates of
standard errors with small samples sizes in
clustered data (Raudenbush & Bryk, 2002).
Specifically, Bayesian estimation treats esti-
mated parameters as random variables that
follow a specified distribution (Rupp, Dey, &
Zumbo, 2004). We did not specify priors,
and 10,000 iterations were used in our model.
The results were the same using listwise dele-
tion or Bayesian estimation, which supports
the assumption that missing data were missing
completely at random.
Step 2. Unconditional models were es-
timated using two-level models in MPlus soft-
ware to account for the nesting of children
within classrooms (Muthe´n & Muthe´n, 2008).
These models indicated the amount of vari-
ance available to explain at each level of the
models (children at Level 1, teachers at Level
2). Unconditional models enable the compu-
tation of intraclass correlation coefficients
(ICCs) that quantify the proportion of student
outcome variation that occurs across class-
Teachers’ Emotional Support to Children
149
rooms. ICCs for response variables ranged
from 0.03 to 0.13, indicating that between 3%
and 13% of the variance in behavioral out-
comes occurred across classrooms.
Step 3. In line with recommended prac-
tice, models were built incrementally begin-
ning with the unconditional model, then add-
ing Level 1 variables (child gender, age, ad-
justment difficulty, and risk), a Level 2 control
variable (classroom behavior management),
and a Level 2 predictor (classroom emotional
support; Raudenbush & Bryk, 2002). Building
our model in this way allowed us to assess the
relative effect of each covariate. Risk was
centered at the group mean because it was a
variable of interest, and the Level 1 control
variables and Level 2 variables were centered
at the grand mean (Enders & Tofighi, 2007).
We included teachers’ ratings of children’s
adjustment difficulty in the first 3 weeks of
school as a covariate to account for potential
teacher bias. This allowed us to consider dif-
ferences at the end of the year while account-
ing for similar behaviors that were reported at
the beginning of the year.
Step 4. Finally, to quantify the effect
size for classroom emotional support, the pro-
portion of variance reduction (PVR) was cal-
culated. Specifically, we subtracted the
Level 2 intercept variance in the final model
from the variance in the Level 2 control
model, and divided by the variance in the
Level 2 control model (Equation 1):
PVR ⫽ 共VAR
no predictor
⫺ VAR
predictor
)/VAR
no predictor
(1)
This effect size could be interpreted as
the amount of variance in the outcome ex-
plained by classroom emotional support.
The combined main effects model for all
three classroom social outcomes and behav-
ioral self-control is described by Equation 2.
The final equation defines the outcome Y for
child i in classroom j as the classroom mean
score (␥
00
) plus the contribution of the two
classroom variables (␥
01, 2
) and the child vari
-
ables (␥
10, 20, 30, 40
), added to error for each
child (r
ij
) and the error for each classroom
(u
0j
).
Y
ij ⫽
␥
00
⫹␥
01
(behavior management)
⫹␥
02
(emotional support)
⫹␥
10
(adjustment difficulty)
⫹␥
20
(child gender)⫹␥
30
(child age)
⫹␥
40
(child risk) ⫹ u
0j
⫹ r
ij
(2)
To address our third research question
regarding a cross-level interaction between
classroom emotional support and child risk,
we repeated the earlier model building process
allowing the effect of child risk on our out-
comes to vary across classrooms. Next, we
tested for a cross-level interaction between
child risk and teachers’ emotional support for
each of the four outcomes to determine
whether the level of classroom emotional sup-
port could lessen or intensify the effect of
child risk on social and self-regulatory out-
comes.
Results
Classrooms in this study showed mod-
erate emotional support (M ⫽ 4.94) and be-
havior management (M ⫽ 4.77). Averages
were slightly lower than scores from nation-
ally representative kindergarten classrooms
(emotional support M ⫽ 5.08; behavioral
management M ⫽ 5.18 in Pianta, La Paro, &
Hamre, 2007). Most teachers (83%) fell in the
midrange (with average scores between 3 and
5) of emotional support on the CLASS scale
(83%), and 17% of teachers offered high lev-
els of emotional support (⬎5.5). None of the
teachers in our study had an emotional support
average that fell in the low range of support (1
or 2). Aggressive and excluded behaviors
were near the lower end of the scale showing
low frequency. Means for prosocial behaviors
with peers and behavioral self-control were
near the scale midrange. Descriptive statistics
showed sufficient variability in the sample for
all outcomes. See Table 2 for descriptive sta-
tistics for all variables.
School Psychology Review, 2012, Volume 41, No. 2
150
Table 3 reports relations between depen-
dent and independent variables. Some of the
child-level variables were related. Girls were
more likely to exhibit prosocial behaviors than
boys (r ⫽⫺.26). Children who were reported
as aggressive were more likely to be excluded
by peers (r ⫽ .64), and less likely to demon-
strate prosocial behaviors (r ⫽⫺.38) and be-
havioral self-control (r ⫽⫺.72). Boys were
more likely than girls to have difficulty adjust-
ing to first grade, according to their teachers.
Also, children who were reported to have dif-
ficulty adjusting to first grade were more likely
to be reported as being aggressive with peers
and excluded by peers, and less likely to dem-
onstrate prosocial behaviors by peers or be-
Table 2
Descriptive Statistics of Predictors and Outcomes
Variable NMSDRange ␣
Child-level predictors
Child age (years) 174 6.47 .30 5.75–7.25 –
Sociodemographic risk 178 .43 .33 0.00–1.00 –
Child-level outcomes
Adjustment difficulty (11 items) 178 1.86 .82 1.00–4.30 .90
Aggression with peers (4 items) 173 1.29 .47 1.00–3.00 .91
Excluded by peers (4 items) 173 1.22 .40 1.00–2.75 .85
Prosocial with peers (4 items) 173 2.21 .57 1.00–3.00 .90
Behavioral self-control (4 items) 173 3.67 1.06 1.00–5.00 .91
Classroom-level predictors
Classroom behavior management 178 4.77 1.05 2.36–6.25 –
Classroom emotional support 178 4.94 .59 3.50–5.98 .88
Note. Risk includes mothers’ education level, mother’s marital status, and family income.
Table 3
Summary of Correlations among Predictor and Outcome Variables
(
N
ⴝ 173)
Variable 1234 567 8910
1. Child age (months) –
2. Gender (boys ⫽ 1) ⫺.11 –
3. Risk .04 .01 –
4. Adjustment difficulty ⫺.16 .24* .19 –
5. Classroom Behavioral
Management .04 .00 ⫺.11 ⫺.03 –
6. Classroom Emotional
Support .10 ⫺.01 ⫺.16 ⫺.03 .54* –
7. Aggression with peers ⫺.10 ⫺.02 .13 .51* ⫺.01 ⫺.15 –
8. Excluded by peers ⫺.15 .06 .08 .57* .04 ⫺.08 .64* –
9. Prosocial with peers .16 ⫺.26* ⫺.20 ⫺.47* .03 .12 ⫺.38* ⫺.45* –
10. Behavioral Self-Control .11 ⫺.14 ⫺.17 ⫺.58* .07 .17 ⫺.72* .53* .43* –
Note. Values are reported after applying the Holm-Bonferonni (Holm, 1979) method to account for multiple tests.
* p ⬍ .01.
Teachers’ Emotional Support to Children
151
havioral self-control in the spring. Results of
multilevel analyses, which account for the
nesting of 178 children in 36 classrooms, are
reported in Table 4 and summarized in the
following.
Relationship Between Emotional
Support and Classroom Social Behaviors
Aggression. Based on the uncondi-
tional model, there was significant variance at
the classroom level (ICC ⫽ .08). In the final
model, higher classroom emotional support,
but not classroom management, significantly
predicted lower aggression. For every 1-point
decrease in classroom emotional support, a
student had a 0.16 increase in reported aggres-
sion, which is about one-third the standard
deviation of aggression. Emotionally support-
ive teacher– child interactions explained 36%
of the classroom-level variance in aggression.
Exclusion by peers. In the uncondi-
tional model, the proportion of variance in
exclusion by peers between classrooms was
not significant (ICC ⫽ .03). Neither emotional
support nor classroom management was sig-
nificantly related to exclusion by peers in the
final model.
Prosocial behaviors. The proportion
of variance in prosocial behaviors between
classrooms in the unconditional model was
significant (ICC ⫽ .12). Emotional support
and behavior management were not significant
predictors of prosocial behavior in our final
model.
Relationship Between Emotional
Support and Behavioral Self-Control
Behavioral self-control. We found
that a significant amount of the variance in
behavioral self-control was between class-
rooms in the unconditional model (ICC ⫽
.13). In addition, higher levels of emotional
support predicted higher behavioral self-con-
trol. For every 1-point increase in emotional
support, students were reported to be .32
points higher on the behavioral self-control
scale, or about one-third of a standard devia-
tion. Behavior management was not signifi-
cantly related to self-control, however. In the
final model, emotional support explained 21%
Table 4
Hierarchical Linear Model Results: Emotional Support Predicting Social
Behaviors and Self-Regulatory Skills (
N
ⴝ 178)
Parameter
Aggressive Excluded Prosocial
Behavioral
Self-Control
Coefficient SD Coefficient SD Coefficient SD Coefficient SD
Fixed effects
Intercept ␥
00
1.29* .03 1.22* .03 2.21* .05 3.68* .11
Level 2
Behavior Management .05 .04 .05 .03 ⫺.03 .06 ⫺.06 .10
Emotional Support ⫺.16* .07 ⫺.09 .06 .13 .11 .33* .17
Random effects
Level 1
Intercept
2
.16* .02 .11* .01 .21* .03 .70* .09
Level 2
Intercept ⌻
00
.01* .01 .01* .01 .05* .03 .09* .07
Note. Coefficient ⫽ fixed effect Bayesian coefficient estimate SD ⫽ Posterior Standard Deviation.
In all four models, we controlled for child adjustment, child age, and child gender.
* p ⬍ .05
School Psychology Review, 2012, Volume 41, No. 2
152
of the classroom-level variance in behavioral
self-control.
Overall, findings showed higher emo-
tional support related to teachers’ perception
of students as lower in aggression and higher
in behavioral self-control. Higher emotional
support was not associated with teachers’ per-
ceptions of students’ excluded or prosocial
behaviors.
Emotional Support as a Moderator for
Child Sociodemographic Risk
The interaction between classroom emo-
tional support and child sociodemographic
risk did not significantly predict aggressive
behavior, exclusion by peers, prosocial behav-
iors, or behavioral self-control. Findings
showed that emotional support was equally
important for children with all levels of so-
ciodemographic risk represented in this sam-
ple.
Discussion
Three findings emerged from the current
data. First, emotionally supportive teacher–
child interactions were associated with lower
levels of teacher-reported child aggression.
However, emotional support was not a signif-
icant predictor of exclusion by peers or proso-
cial behaviors. Second, children with more
emotionally supportive classrooms were more
likely to show more behavioral self-control
than children with less supportive classrooms.
Third, emotionally supportive classrooms
were equivalently important for children of
high and low levels of sociodemographic risk
for students in our sample.
Taken together, the current findings sug-
gested the importance of emotionally support-
ive teacher– child interactions for aspects of
children’s behaviors and skills often viewed as
important to early school adjustment (e.g.,
Ladd, 1990). Results support and extend prior
work by examining observed emotionally sup-
portive interactions while controlling for other
aspects of teacher–child interactions that can
be important, such as teachers’ perception of
the students at the beginning of the year and
teachers’ behavior management. Such work
builds on existing evidence (e.g., Perry et al.,
2007; Pianta, La Paro, Payne, Cox, & Bradley,
2002; Wilson et al., 2007) and indicates that
interventions that aim to improve emotionally
supportive interactions hold promise for im-
proving children’s social behaviors and self-
regulatory skills, a premise necessitating both
intervention development and empirical test-
ing.
Teacher Emotional Support and Social
Behaviors
The present findings suggest the impor-
tance of offering emotional support such as
warmth, encouragement, and comfort to re-
duce problems with aggression. The link be-
tween emotional support and lower aggression
can be understood in relation to other work
showing that emotionally supportive teachers
enhance children academic outcomes as well
in the early years of school (Connor, Son,
Hindman, & Morrison, 2005; Curby, Rimm-
Kaufman, & Ponitz, 2009). Taken together,
findings suggest the complementarity between
teacher behaviors that may prevent aggression
and teacher behaviors that promote academic
development in early childhood.
Several mechanisms are plausible to ex-
plain the relation between teachers’ emotional
support and children’s decreased aggression.
Emotionally supportive teachers may be more
adept than other teachers at noticing the be-
havior patterns and social and emotional needs
of students. For example, a teacher high in
emotional support may be better able to ob-
serve which students are struggling socially
and help them by facilitating positive interac-
tions with peers. In addition, sensitive teachers
may be more adept at scaffolding instruction
to target individual children’s Zone of Proxi-
mal Development for students as they learn
social skills (Vygotsky, 1978). Teachers who
show high regard for students’ perspectives
may be more skilled in recognizing when a
child is showing normative, developmentally
typical play versus signs of aggression.
Emotionally supportive teaching strate-
gies may be particularly useful for decreasing
aggressive behaviors. Aggressive children are
Teachers’ Emotional Support to Children
153
challenging to teach in classroom settings.
Emotionally supportive interactions may help
aggressive children resolve conflicts peace-
fully. When children are feeling angry or act-
ing out, encountering a negative climate with
an adult who is rigid and punitive will likely
exacerbate behavior problems. On the other
hand, a teacher who takes the time to listen to
children’s perspectives and offers warmth and
support is more likely to diffuse aggression.
Moreover, teachers who model sensitive re-
sponses to aggression may set into motion
appropriate classroom norms and peer behav-
iors. Specifically, peers may learn how to help
classmates who are feeling angry or upset and
diffuse situations that would otherwise result
in aggression. Finally, teachers who foster a
positive climate may help children feel more
at ease and relaxed, and less likely to display
aggression.
Emotionally supportive teacher– child
interactions did not predict prosocial or ex-
cluded behaviors. Although some research
links teacher– child relationships to prosocial
behaviors (Birch & Ladd, 1998), other work
suggests that other factors play a greater role
in relation to prosocial behaviors. For exam-
ple, genetic factors appear to play a majority
role in the prosocial behavior of first-grade
children. Specifically, the effect of genetics
appears to almost double between years 2
and 7 (Knafo & Plomin, 2006). Moreover,
excluded behaviors were reported infrequently
in our sample as compared with all of the other
outcomes. It is possible that constrained vari-
ability made it difficult to detect patterns of
relations with teacher emotional support. Fu-
ture work with larger samples or children of
varying ages is needed to provide further in-
sight into this relation.
Teacher–Child Interactions Are Critical
for Young Children Who Are Learning
Self-Control
As one example, teachers high in emo-
tional support demonstrate sensitivity toward
their students. Sensitive teachers notice when
students are having difficulty and provide in-
dividualized support, matching the level of
support offered with students’ needs and abil-
ities. When a teacher is responsive and pro-
vides scaffolding for student engagement and
attention, children may learn to make better
intentional choices about their behavior. Fur-
ther, a teacher who is sensitive and responsive
to her students may teach behavioral self-con-
trol implicitly through her interactions with
her students. In contrast, a teacher who is
controlling and punitive may not provide stu-
dents enough independent learning opportuni-
ties to support their development of autonomy.
By supporting children’s efforts as needed,
pacing their work efforts, guiding attention,
and encouraging students to wait when neces-
sary, a teacher may provide external controls
that become internalized over time (Bronson,
2000).
Emotional Support as a Potential
Moderator
Findings show that emotional support
did not moderate the relation between sociode-
mographic risk and children’s social and self-
regulatory outcomes. Thus, teachers’ emo-
tional supportiveness was equally important in
predicting social behaviors and self-regulatory
skills regardless of students’ level of sociode-
mographic risk. Findings are consistent with
some work showing that relationships with
teachers had significance for all children in
promoting adaptive developmental trajectories
(Silver et al., 2005). However, results are
somewhat different from other research sug-
gesting that quality classroom environments
have greater consequence for children with
more functional or demographic risks (Hamre
& Pianta, 2005). The sample in the Hamre and
Pianta study included a larger population of
students with multiple risks, and the outcomes
examined were different from those in our
study. Risk factors other than maternal educa-
tion, family income, and single parent status
may be more salient when considering the
contribution of teacher emotional support to
social and self-regulatory outcomes. Also, the
range of emotional support in our study was
limited. Extreme cases of higher or lower sup-
port may be more likely to influence outcomes
School Psychology Review, 2012, Volume 41, No. 2
154
than moderate support for children with so-
ciodemographic risks.
It is important to consider to whom
these findings generalize. Specifically, the
present sample is from a predominantly work-
ing class, rural area. Although the design does
not permit causal assertions and prescriptive
recommendations, the findings do suggest that
school psychologists’ efforts to support teach-
ers’ emotional support of children may have a
promotive contribution to young children’s
outcomes in comparable rural schools.
Limitations
Several limitations require mention.
First, teacher-reported measures of behaviors
and skills were used to assess student out-
comes in the spring. Some research suggests
that teacher bias of individual students may
influence results of teacher-reported measures
(Mashburn, Hamre, Downer, & Pianta, 2006).
We controlled for teacher-reported adjustment
in the fall of first grade to account for potential
teacher bias. However, including both ob-
served and teacher-reported measures of social
behaviors and self-regulatory skills would
have strengthened the results. Second, the
population of students in this study was from
a small sample of rural schools. On one hand,
this is strength of the study because it exam-
ines a population that is not understood as well
as some other populations; more than half of
all school districts in the United States are
located in rural areas (Provasnik et al., 2007).
On the other hand, the results of these analyses
may not generalize to students in urban set-
tings with sociodemographic risk factors.
Third, the limited variability in exclusion by
peers made it difficult to detect patterns of
relations with teacher– child interactions. Fur-
ther work on clinically referred samples of
children with high levels of problem behaviors
can address this issue. Finally, we ran separate
multilevel models for each of the four out-
comes. Our outcomes were related to each
other and the results do not account for their
shared variance. The small sample of class-
rooms in our study and research questions that
focused on specific outcomes led us to this
analytic approach, but future work with larger
studies could use multilevel structural equa-
tion modeling approaches to account for the
relationships between outcomes.
Future Directions and Practical
Implications
Children who exhibit signs of aggres-
sion or show poor self-control in early grades
have many obstacles to overcome, but high
emotional support from teachers may be one
approach to reduce the prevalence of these
problems in first grade. Many interventions
available focus on teaching social and self-
regulatory skills to children directly (Green-
berg, Domitrovich, & Bumbarger, 2001), but
several newer universal school-based inter-
ventions (e.g., Responsive Classroom Ap-
proach; Rimm-Kaufman & Chiu, 2007; the
Seattle Social Development project, Hawkins,
Kosterman, Catalon, Hill, & Abbott, 2005)
focus on building the capacity of teachers and
staff to enhance children’s skills and prevent
violence in schools (Domitrovich et al., 2010).
Further, professional development approaches
that provide teachers with feedback about their
interactions with children can be successful in
improving the quality of interactions that
teachers offer their students (Pianta, Mash-
burn, Downer, Hamre, & Justice, 2008).
Providing emotionally supportive teacher–
child interactions can be an important part of a
teacher’s daily work. Many teachers know that
relationship building is an important focus at
the beginning of the year, and believe it is
important to take the time each day to make
connections with their students and convey
genuine interest in their students’ lives (Wil-
liams et al., 2008). It is plausible that teachers
are more supportive at the beginning of the
year when establishing new relationships, and
less supportive at other times, such as during
testing situations. Examining whether the
amount of support offered is stable or changes
throughout the year and whether the trajectory
of support predicts student outcomes would be
important future work.
Teachers’ emotionally supportive inter-
actions with their students do not occur in
Teachers’ Emotional Support to Children
155
isolation. Positive and negative forces within
teachers’ schools and communities (e.g., level
of trust and collective efficacy) and the district
policies in place appear to influence teachers’
ability to behave in warm and responsive ways
to children (Bryk, Sebring, Allensworth, &
Luppescu, 2010; Goddard, Hoy & Hoy, 2004).
Given the social interdependencies within a
school, school psychologists can play an im-
portant role in facilitating a community of
trust and communication. Specifically, school
psychologists can help teachers understand
how their daily interactions with children sup-
port development of social behaviors. Further,
school psychologists can offer support and
feedback to teachers as they strive to establish
and sustain warm and responsive classroom
cultures.
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Date Received: June 18, 2010
Date Accepted: November 17, 2011
Action Editor: Joseph Betts 䡲
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Eileen G. Merritt, PhD, is a postdoctoral research associate at the Curry School of
Education and the Social Development Lab through the Center for the Advanced Study
of Teaching and Learning, University of Virginia. She was a classroom teacher for many
years in Albemarle County, Virginia. Her research focuses on classroom factors that
contribute to elementary students’ social and academic development.
Shannon B. Wanless, PhD, is an assistant professor at the University of Pittsburgh in the
Department of Psychology in Education. Her research examines the cross-cultural mea-
surement and development of children’s social and self-regulatory skills, and ways to
increase fidelity of implementation of social-emotional learning interventions that support
these outcomes.
Sara Rimm-Kaufman, PhD, is an associate professor in the Department of Leadership,
Foundations , and Policy at the Curry School of Education, University of Virginia. Her
research examines classroom social processes and their influence on children’s social and
academic growth during the elementary years. She directs the Educational Psychology–
Applied Developmental Science Doctoral and Masters Programs.
Claire Cameron, PhD, is a research scientist at the Center for Advanced Study of Teaching
and Learning, University of Virginia. Her research addresses child development within
school contexts, measurement of learning processes, and teachers’ organizational strate-
gies. She has done extensive work to develop and validate the Head-Toes-Knees-
Shoulders (HTKS) measure of self-regulation in early childhood.
James Peugh, PhD, is an assistant professor of quantitative psychology at the Cincinnati
Children’s Hospital Medical Center. His research uses Monte Carlo simulation techniques
to examine the accuracy of finite mixture models used to analyze cross-sectional,
longitudinal, and multilevel (cluster sampled) data.
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