Elucidating Linkages of Executive Functioning to School Readiness Skill Gains: The Mediating Role of Behavioral Engagement in the PreK Classroom

Abstract

This study investigated links of executive functioning to gains in school readiness skills and explored the mediating role of children’s behavioral engagement in the PreK classroom. We collected direct assessments of executive functioning (EF) and observations of behavioral engagement for 767 children (mean age 52.63 months) from racially/ethnically diverse, low-income backgrounds three times over the PreK year. We also measured school readiness in the domains of language, literacy, and math using direct assessments and collected teacher-report measures of socialemotional-behavioral skills and approaches to learning. Our analyses addressed the following three research questions: 1) To what extent does children’s EF predict school readiness skill gains during PreK? 2) To what extent does children’s behavioral engagement in PreK classrooms predict school readiness skill gains? 3) To what extent does behavioral engagement mediate the relation of EF with school readiness skill gains? We observed that EF was positively related to gains in language, math, and approaches to learning. Regarding behavioral engagement, Negative Classroom Engagement was negatively related to gains in literacy, math, social-emotionalbehavioral skills, and approaches to learning while Positive Task Engagement was positively related to gains in approaches to learning. Negative Classroom Engagement significantly mediated the effects of EF on gains in the domains of literacy, socialemotional-behavioral skills, and approaches to learning. We describe implications of these findings for promoting children’s ability to learn and thrive in PreK contexts with a focus on their engagement with teachers, peers, and learning activities.

1. Introduction

School readiness (SR) has been conceptualized as a multidimensional construct comprising cognitive, language, social-emotional-behavioral, physical, and approaches to learning skills that enable young children to learn and thrive in school contexts (Boivin & Bierman, 2014; Peterson et al., 2018). Despite significant investments in and expansion of early childhood education (ECE) programs in the US in recent decades (e.g., state-funded preschool), SR inequities persist, reflecting extensive unmet needs and untapped talents among children from low-income backgrounds (García & Weiss, 2017). Accordingly, research directed toward understanding the skills and experiences that enable children from low-income backgrounds to learn and thrive in school contexts remains a priority (e.g., Jarrett & Coba-Rodriguez, 2018).

Cognitive and social-emotional skills emerge as particularly consistent and robust predictors of school-age success across multiple domains (e.g., Burchinal et al., 2020; McKinnon & Blair, 2019). In particular, the neurocognitive attention-regulation skills involved in conscious, goal-directed problem solving, or executive function (EF; including inhibitory control, working memory, and cognitive flexibility; Zelazo et al., 2016) provide a key foundation for classroom learning. Because children from low-income backgrounds are less likely than their peers from higher-income backgrounds to have access to high-quality early care and education (e.g., 10% of eligible children living in poverty are served by Early Head Start; National Head Start Association, 2022), they are also less likely to experience interactions that support strong EF skills prior to Pre-K entry. Poverty has thus been implicated as a key factor driving SR and early childhood development gaps (Blair & Raver, 2015; Finders et al., 2021; Olson et al., 2021). In addition to systemic social and economic issues that oppress particular family subgroups and perpetuate opportunity gaps, the bioecological model of development (Bronfenbrenner & Morris, 2007) suggests that the quality and frequency of reciprocal interactions in which children engage in their immediate environments may variously promote or disrupt development—ECE settings represent one such primary context.

Beyond home and neighborhood contexts, ECE settings afford opportunities for children to practice SR skills during naturalistic moments of challenge, guided by familiar adults, in ways that have potential for generalized gains (Bierman & Torres, 2016). Indeed, meaningful interactions with adults and peers in sociocultural contexts, such as ECE settings, have been theorized as critical drivers of learning and development (e.g., Vygotsky, 1978). As such, the present study rests on the premise that being able to learn and thrive in school contexts is a function of the nature and quality of children’s engagement with teachers, peers, and learning activities (henceforth, behavioral engagement) in ECE classroom settings. With participation of a racially/ethnically diverse sample of PreK children from low-income backgrounds, this study elucidates connections among EF, behavioral engagement, and SR skill gains.

1.1. School Readiness Skill Development for Children from Low-Income Backgrounds

Collectively, SR skills in cognitive, language, physical, social-emotional-behavioral, and approaches to learning domains affect children’s learning opportunities and their acquisition of new skills in the classroom setting (Sabol & Pianta, 2017). It is well documented that substantial socioeconomic status (SES)-related differences in cognitive and non-cognitive skills are evident prior to children’s entrance to formal schooling--differences that have persisted for decades (e.g., Hanushek et al., 2019). For instance, analyses of large-scale, longitudinal datasets with nationally representative samples such as the Early Childhood Longitudinal Study- Birth Cohort and the Fragile Families and Child Wellbeing Study indicate that children living in poverty are more likely to begin school at a disadvantage in the areas of early math and reading, learning-related and problem behaviors, social and self-regulatory school competencies, and overall physical health, as compared to their peers from higher-income backgrounds (Rouse et al., 2020; Ryan et al., 2006). Importantly, just as health inequities are not the result of individual behavior choices or genetic predisposition, economic disparities that perpetuate opportunity gaps are the result of community-level social determinants, such as economic, political, and social conditions, including racism (Trent et al., 2019). Thus, community-level disadvantage can amplify negative effects of family-level economic disadvantage on SR (Lipscomb et al., 2019).

Longitudinal studies further document differences between children of more and less advantaged backgrounds at kindergarten entry and throughout elementary school (McCarty, 2016). Long-term effects of early gaps in academic and social functioning are so pronounced that interventions reducing these disparities in the PreK period are increasingly viewed as fundamental to the developmental success of children and to the economic and social health of communities (van Huizen & Plantenga, 2018). High-quality ECE programs narrow school-readiness and opportunity gaps, alter children’s life trajectories, and yield substantial social returns (McCoy et al., 2017). Yet, the promise of ECE in the US is not being realized despite significant investments over recent decades in ECE programs; children from low-income backgrounds continue to enter kindergarten far behind their more well-off peers (Wolf et al., 2017). The fact that current investments in ECE have failed to close the opportunity gap is in large part due to the drastic variability in the quality of ECE programs across the US and inequitable access to high-quality early care and education prior to Pre-K entry. However, it is important to recognize that individual children from low-income backgrounds can and do flourish within PreK classrooms, despite having inequitable access to quality early childcare programs, highlighting the need for additional research examining how individual children within the same classroom engage with classroom teachers, peers, and learning opportunities differently from one another (e.g., Rimm-Kaufman et al., 2009).

1.2. Linkages between EF and School Readiness in PreK

EF is a key skillset undergirding both academic and social-emotional-behavioral skills that commonly mediates the effects of poverty on children’s SR (Raver, 2012). The attention-regulation skills EF comprises (i.e., inhibitory control; mental flexibility; working memory) support learning by enabling children to pay attention, persist during challenging tasks, hold information in memory, solve problems flexibly, and plan (e.g., Blair, 2016; Zelazo et al., 2016). EF plays a central role in the ability to regulate attention, emotion, and behavior in PreK children (Sasser, et al., 2015), skills that are needed to successfully engage in the classroom. EF skills are essential for social functioning, emotion regulation, and intentional learning, providing a foundation for academic achievement and school performance (Zelazo & Carlson, 2020). EF skills are consistently associated with children’s academic trajectories (Cameron et al., 2019; Duncan et al., 2007; McClelland et al., 2006) and play an important role in math learning and problem solving (e.g., Blair et al., 2016; Sasser et al., 2015). Although significant development in EF skills occurs between ages 3–5 years (Reilly et al., 2022; Willoughby et al., 2013), EF has long-term impacts on multiple domains across the life course (e.g., academic success, impulse control, constraint, emotion regulation; e.g., Pan et al., 2022). Much of the research reviewed here that examines connections between EF and SR has focused expressly on children from low-income backgrounds. For example, as part of the Family Life Project, Blair et al. and Willoughby et al. conducted a prospective longitudinal study of a representative sample of 1,292 babies born to mothers in six poor rural counties (oversampling for poverty). As another example, Sasser et al. followed 164 children PreK though grade 3; 68% of participating families reported incomes below the federal poverty level and all children attended Head Start, which serves families of low income. Additionally, as part of the Chicago School Readiness Project, Pan et al. followed a sample of 379 primarily Black and Hispanic youth growing up in high-poverty areas of Chicago. Accordingly, research examining connections among poverty-related risks, EF, SR and academic achievement continues to be a priority in the field of early childhood education (e.g., Micalizzi et al., 2019; Perry et al., 2018).

1.3. Linkages between Behavioral Engagement and School Readiness in PreK

There is also interest in understanding how individual children’s reciprocal interactions with teachers, peers, and learning tasks (i.e., behavioral engagement) shape their SR skill gains, because interactions are the proximal mechanism through which children learn academic and social-emotional-behavioral skills (Hamre et al., 2013; Pianta et al., 2016, Vygotsky, 1978, Williford et al., 2013). This viewpoint rests on research suggesting young children engaging in warm and sensitive reciprocal interactions with teachers have better academic, social-emotional, and self-regulatory development (Birch & Ladd, 1997; Palermo et al., 2007; Pianta & Stuhlman, 2004). Similarly, children engaging positively with peers through sharing, appropriate communication, and play have higher academic achievement (e.g., Bell et al., 2016), better social-emotional skills (Fantuzzo et al., 2004; Mendez & Fogle, 2002), and increased on-task behavior in the classroom (Elias & Berk, 2002). In addition, young children who independently, actively, and enthusiastically engage in learning tasks demonstrate better SR skills (Fantuzzo et al., 2004; Hughes & Kwok, 2006; Nesbitt et al., 2015). In contrast, children who experience negative or conflictual interactions with teachers or peers are at risk for increased problem behaviors, decreased academic and social skills, and decreased school engagement (Bierman et al., 2009; Buhs et al., 2006; Graziano et al., 2016; Pakarinen et al., 2021). Overall, children who experience higher-quality reciprocal interactions with their teachers, peers, and learning tasks fare better than their peers with lower levels of behavioral engagement on multiple SR measures (e.g., Rojas & Abenavoli, 2021; Sabol et al., 2018; Yang et al., 2022)

1.4. Behavioral Engagement as a Mediator of the Linkage between EF and School Readiness in PreK

Although the research literature has clearly shown that EF and behavioral engagement are directly linked to SR (e.g., Perry et al., 2018; Salvas et al., 2022; Vitiello & Greenfield 2017), the extent to which individual children’s behavioral engagement might underlie the relation between EF and SR has received less attention. However, studies examining linkages among aspects of EF, behavioral engagement, and SR potentially indicate a mediating role for behavioral engagement. Downer et al. (2021) found that EF was strongly related to later behavioral engagement, particularly in the areas of Positive Teacher Engagement, Positive Peer Engagement, and Negative Classroom Engagement. Additionally, teacher-reported PreK learning behaviors (Sasser et al., 2015) and observed learning behaviors (Nesbitt et al., 2015) were found to mediate the link between EF skills and academic SR skill gains.

Children in the PreK classroom must regularly recruit their EF skills to evaluate when certain behaviors are appropriate and to adjust their behavior flexibly to match changing expectations according to their interactional context—including interactions with teachers, peers, and structured learning tasks (Cameron, 2018). It thus follows that children with stronger EF skills might also derive greater benefit from learning opportunities with teachers, peers, and learning tasks, translating to greater gains in SR. However, we are aware of no research investigating whether behavioral engagement in PreK settings may explain the relations of incoming PreK EF with SR skill gains in the domains of language, literacy, math, social-emotional-behavioral skills, and learning approaches for children of low-income backgrounds.

1.5. The Present Study

The present study builds on evidence that SR skill development is individualized, in that children engage with teachers, peers, and learning activities quite differently from one another (e.g., Rimm-Kaufman et al., 2009; Sabol, 2021; Williford et al., 2013) and a recognition that EF is a core developmental capacity underlying both academic and behavioral readiness for children in poverty (Raver, 2012). This study aims to elucidate connections of these two key competencies with SR skill gains in language, literacy, mathematics, social-emotional-behavioral, and approaches to learning. Specifically, with participation from a racially/ethnically diverse sample of children from low-income backgrounds, the present study addresses the following three research questions: 1) To what extent does children’s EF predict SR skill gains during PreK? 2) To what extent does children’s behavioral engagement in PreK classrooms predict SR skill gains? 3) To what extent does behavioral engagement mediate the relationship of EF with SR skill gains? We expect that children’s incoming EF skills will be positively related to their SR skill gains during PreK. We also posit that children’s observed interactions with teachers, peers, and learning activities (behavioral engagement) will be positively associated with their SR skill gains. Finally, we hypothesize behavioral engagement will explain a significant part of the relation between EF and SR skill gains.

2. Method

We analyzed data from child direct assessments, classroom observations, and teacher reports from the PreK year for children enrolled in a two-cohort longitudinal observational study. Research activities were approved by the university’s Institutional Review Board for Social and Behavioral Sciences (approval #2015–0443–000).

2.1. Participants

A total of 767 children (379 females; 388 males) enrolled in 103 preschool classrooms (92=state-funded classrooms; 11=Head Start classrooms) and eligible to matriculate into kindergarten in September 2017 for cohort 1 (i.e., age 4 years on or before September 30, 2016) or September, 2019 for cohort 2 (i.e., age 4 years on or before September 30, 2018) participated in the study. Participating classrooms were from an urban region of the southeastern United States.

Classrooms were eligible if they primarily served 4-year-old children and the teacher signed an informed consent form. In special education inclusion classrooms with a special education aide, the general education teacher was selected for participation. In cohort 1, 50 teachers out of 67 who consented were randomly selected to participate in the study. One child transferred to a different study classroom during the year and one teacher on an extended leave was replaced with a new teacher, bringing the total to 52 teachers. In cohort 2, all 51 eligible teachers who consented were selected to participate in the study. Two children transferred to a different study classroom during the year and three teachers who moved or took an extended leave were replaced with new teachers, bringing the total to 56. The combined sample of cohort 1 and cohort 2 teachers included 106 females and 2 males. The average age of teachers at the start of the study was 43.25 years (SD = 11.23). In terms of race/ethnicity, the largest percentage of teachers were identified as White, non-Hispanic (61%), followed by Black/African-American (28%), Hispanic/Latino of any race (3%), other race (3%), two or more races, non-Hispanic (2%), or missing (7%). Teachers’ average teaching experience was 15.14 years (SD = 8.61). Head Start teachers were required to have at least an associate’s or bachelor’s degree in child development or early childhood education, or equivalent coursework. Teachers in the state-funded program were required to hold a teaching license with a Pre-K endorsement or be eligible for one. In terms of highest level of education for our sample, about 50% of teachers had a master’s degree, 48% had a bachelor’s degree, and <3% had less than a bachelor’s degree.

All children in participating preschool classrooms who were able to independently complete study assessments in English were eligible for participation. Parents/guardians were invited to complete an informed consent agreement during the first month of their child’s preschool year. Up to 8 consented children per classroom were randomly selected to participate after blocking by gender. When fewer than 8 children were consented, all consented children in the classroom were chosen. The total number of children selected for participation was 380 in cohort 1 and 387 in cohort 2, for a total of 767 children.

The average age of children at the start of the study was 52.63 months (SD = 3.60). In terms of race/ethnicity, the largest percentage of children were identified as Black/African-American (49%), followed by White, non-Hispanic (22%), Hispanic/Latino of any race (13%), two or more races, non-Hispanic (11%), other race (3%), or missing (3%). The average annual total family income was $36,342 (SD = $26,047), and the average income-to-needs ratio was 1.45 (SD=1.06), where 1.0 indicates the federal poverty line. Eligibility requirements for preschool attendance included one or more of the following: family income at or below 200% of the federal poverty guidelines (350% for students with special education needs), family homelessness, or parents/guardians lacking a high school diploma.

2.2. Measures

We collected direct assessments of EF and observations of behavioral engagement three times over the PreK year (fall, winter, spring). We also measured SR in the domains of language, literacy, and math using direct assessments and obtained teacher-report measures of social-emotional-behavioral skills and approaches to learning in fall and spring of the PreK year.

2.2.1. Executive Functioning

An executive functioning composite was created from four EF tasks. Three tasks used a computer-based administration format (EF Touch; Willoughby & Blair, 2016), and the remaining task used an interactive format (Head-Toes-Knees-Shoulders [HTKS]; Pointz et al. 2008). Overall, the EF Touch tasks exhibit good reliability for children ages 3 to 5 years (Willoughby et al., 2013). The EF Touch Pig task measures inhibitory control using 40 items in a standard go-no go format. Specifically, the task requires that children touch the screen when they see an animal (go response), unless it is a pig (no-go response). The EF Touch Pick the Picture (PtP) task measures working memory as children view increasingly larger sets of pictures on the screen (2, 3, 4, and 6 pictures) and select a picture that was not part of the series each time the set of pictures is presented in a randomized order. The EF Touch Something’s the Same (StS) task measures attention shifting and mental flexibility skills across 30 items. Children choose an item on a screen matching a certain dimension (content, color, or size) that differs from a dimension to which they initially attended. The EF Touch software automatically calculates the percentage of items correct for each task.

The HTKS task measures inhibitory control, working memory, and mental flexibility skills, as children touch the body part opposite of what the assessor says (e.g., head vs. toes; shoulders vs. knees). Advanced trials include all four body parts and involve rule changes. Children receive two points for each correct response, one point for each self-correction, and zero points for each incorrect response, with possible scores ranging from 0 to 60 across 20 trials. The HTKS is a reliable and valid measure of executive functioning for children ages 3 to 6 years (Pointz et al., 2008).

Factor scores for the executive functioning measures were estimated based on a linear factor analysis model specified in Mplus with (1) EF Touch: Pig, (2) EF Touch: Pick the Picture, (3), EF Touch: Something’s the Same, and (4) Head Toes Knees Shoulders as indicators. Standardized factor loadings were moderate in strength and ranged from .410 (EF Touch: Pig) to .727 (EF Touch: Something’s the Same). In our sample, estimated factor scores range from −2.79 to 2.38 with a mean of 0.31 and a standard deviation of 0.94. Additional details of the factor analysis are available from the authors upon request.

2.2.2. Classroom Behavioral Engagement

The Individualized Classroom Assessment Scoring System (inCLASS; Downer et al., 2010) measures individual children’s interactions with teachers, peers, and learning tasks in their natural classroom environment as assessed by an independent observer. The inCLASS comprises four domains (Bohlmann et al., 2019). Positive Teacher Engagement is evidenced by behaviors such as attunement to the teacher, proximity seeking, and shared positive affect, as well as initiating communication and engaging in sustained conversation with teachers using a variety of communication functions. Positive Peer Engagement is indicated by behaviors such as proximity seeking with peers, shared positive affect, cooperation, and evidence of friendships and popularity with peers, leadership and self-advocacy, and initiating and engaging in sustained conversation with peers using a variety of communication functions. Positive Task Engagement includes behaviors such as sustained attention and active engagement, personal initiative, independence, persistence, and self-directed learning, as well as patience, physical awareness and matching classroom expectations for activity level. Finally, Negative Classroom Engagement is marked by behaviors such as aggression, negative affect, and attention seeking directed toward the teacher or peers.

Possible scores for each domain range from 1 to 7. For Positive Teacher Engagement, Positive Peer Engagement, and Positive Task Engagement, higher ratings indicate higher quality and/or more frequent positive engagement. For Negative Classroom Engagement, higher ratings indicate lower quality and/or more frequent negative engagement. Observers worked in pairs to complete six 15-minute inCLASS cycles (10 minutes observing, 5 minutes coding) for each child over a period of at least two days per observation time point (i.e., fall, winter, and spring of preschool). Observations were not completed during naptime, but they were completed during all other times of the day, including structured activities, unstructured activities (e.g., outdoor recess, lunch/mealtime), and transitions. Observers made notes and assigned codes on paper, then transferred their codes to a secure data collection application for analysis. An average score was computed for each of the four domains for each of the three observation time points.

Bohlmann et al. (2019) demonstrated stable measurement properties of the inCLASS across demographic subgroups and validated the utility of the inCLASS in a large sample of preschoolers reflecting the racial, ethnic, and socioeconomic diversity of early childhood classrooms across the United States. Additional studies demonstrated the inCLASS predicts measures of SR in the areas of language, literacy, and self-regulation (Vitiello & Williford, 2016; Williford et al., 2017). Additionally, a number of studies have used the inCLASS to measure behavioral engagement in samples of children from low-income backgrounds (e.g., Rojas & Abenavoli, 2021; Sabol et al., 2018; Sutherland et al., 2018; Williford et al., 2013). Reliability for the four domains measured in the current study sample were as follows: Positive Teacher Engagement, α = .73; Positive Peer Engagement with peers, α = .86; Positive Task Engagement, α = .55; and Negative Classroom Engagement, α = .51. Inter-rater agreement during live observations on these scales ranged from .71 to .99 in recent studies (Downer et al., 2010, Williford et al., 2013). Inter-rater reliability for the current study was calculated across 20% of all cycles (double coded across classrooms and sites) with two data collectors independently observing and rating the same children and intraclass correlations averaged .73 (ranging from .54 for Positive Task Engagement to .89 for Positive Peer Engagement).

2.2.3. School Readiness

School readiness was measured using direct assessments and teacher-report instruments in five domains: literacy, mathematics, language, social-emotional-behavioral competencies, and approaches to learning. Descriptives for all SR measures appear in Table 1.

Table 1.

Descriptive Statistics

Variable	Mean/n	SD/Percent	Range
Child characteristics/model covariates
Gender
Male	379	49.4
Female	388	50.6
Race/Ethnicity
Black or African American	374	48.8
Hispanic of any race	96	12.5
White	168	21.9
Other	26	3.4
Two or more races, non-Hispanic	84	11
Unreported	19	2.5
Primary Language
English	714	93.1
Spanish	34	4.4
Other	7	0.9
Child age in years	4.4	0.3	3.33 to 5.58
Mother’s education
HS or less	203	26.5
Some college	186	24.3
Two-year degree	94	12.3
Bachelor’s degree	92	12.0
Master's degree or PhD	4	0.5
Unreported	22	2.9
Teacher characteristics/model covariates
Gender
Female	99	91.7
Male	2	1.9
Race/Ethnicity
Black or African American	30	27.8
Hispanic of any race	3	2.8
White	66	61.1
Two or more races, non-Hispanic	2	1.9
Unreported	7	6.5
Education
Some college	1	0.9
Two-year degree	2	1.9
Bachelor’s degree	48	44.4
Master's degree	50	46.3
Years’ experience teaching PreK	9.24	7.22	0 to 30
Executive Function Measure, Fall PreK	.30	.72	−2.80 to 1.96
Behavioral Engagement Measures, Winter PreK
inCLASS Positive Teacher Engagement	2.03	0.64	1 to 4.50
inCLASS Positive Peer Engagement	2.25	0.7	1 to 5.14
inCLASS Positive Task Engagement	3.57	0.77	1.17 to 6
inCLASS Negative Classroom Engagement	1.38	0.4	1 to 3.72
School Readiness Measures, Spring PreK
WJ-III Basic Reading Total Raw Score	8.7	6.67	0 to 68
WJ-III Math Reasoning Total Raw Score	18	7.5	0 to 50
ERC Emotion Regulation	26.02	4.51	11 to 32
T-CRS Behavioral Control	30.11	736	8 to 40
PLBS Total Score	70.48	10.14	9 to 83
NAP-2 Total Score	1270	5.80	0 to 32

Note. EF = executive function; ERC = Emotion Regulation Checklist; inCLASS = Individualized Classroom Assessment Scoring System; NAP-2 = Narrative Assessment Protocol-2; PLBS = Preschool Learning Behaviors Scale; T-CRS = Teacher-Child Rating Scale; WJ-III = Woodcock Johnson-III Tests of Achievement

Literacy.

Data collectors administered two subtests of the Woodcock Johnson-III (WJ-III) Tests of Achievement measuring literacy. The Letter-Word Identification (LWID) subtest measures letter and word identification skills as students read individual letters and words. The Word Attack (WA) subtest measures phonics and decoding skills as students produce letter sounds and read nonsense words. Scores from the LWID subtest and the WA subtest form a Basic Reading score. Both measures forming the Basic Reading score were collected in the fall and spring of PreK. Reliability was α = 0.97 in the fall and α = 0.97 in the spring.

Mathematics.

Data collectors administered two WJ-III subtests measuring mathematics. The Applied Problems (AP) subtest measures concept of numbers and math skills as students analyze and solve math problems. The Quantitative Concepts (QC) subtest measures knowledge of math concepts, symbols, vocabulary, and number patterns as students solve problems related to Concepts (Part A) and Number Series (Part B). Scores from the AP subtest and the QC subtest form a Math Reasoning score. Both measures forming the Math Reasoning score were collected in the fall and spring of PreK. Reliability was α = 0.97 in the fall and α = 0.97 in the spring.

Language.

The Narrative Assessment Protocol-2 (NAP-2; Bowles et al., 2020) is an assessment of narrative language skill for children aged 3–6 years. The NAP-2 uses a narrative retell format with an event-based frequency scoring approach in which the scorer identifies occurrences of specific indicators reflecting an aspect of narrative skill (e.g., time reference). Specifically, the assessor scores the frequency of occurrence for a series of 20 individual items using a rating scale of 0 (no occurrence), 1 (one occurrence), 2 (two occurrences), or 3+ (three or more occurrences). This event-based frequency scoring eliminates the need for transcription of children’s narratives. A rigorous Rasch measurement item analysis indicated that the NAP-2 forms a reliable, unidimensional construct (Bowles et al., 2020).

Social-Emotional-Behavioral.

Teachers rated children’s emotion regulation in social interactions using the Emotion Regulation Checklist (ERC; Shields & Cicchetti; 1997) in fall and spring of PreK. Data collection was intentionally delayed to allow the teacher time to observe and interact with children prior to completing the measure. Specifically, fall assessments were collected in November and spring assessments were collected in May. The ERC includes 24 items pertaining to observable classroom behaviors reflecting children’s emotion regulation. Teachers rate how often they observed each behavior on a 4-point scale: rarely/never; sometimes; often; always. We focused on the ERC factor-derived subscale score for positive emotion regulation, which included 8 items (e.g., Can say when s/he is feeling sad, angry or mad, fearful or afraid). Values on this subscale ranged from 0 to 32 with higher scores indicating greater emotion regulation. Reliability for this subscale was α = 0.83 in the fall and α = 0.82 in the spring.

Teachers also rated children’s social-emotional-behavioral regulation competencies using the Teacher-Child Rating Scale (T-CRS; Hightower; et al., 1986) in the fall and spring of PreK. The T-CRS includes 32 items that teachers rate on a 5-point scale: strongly disagree; somewhat disagree; neither agree nor disagree; somewhat agree; strongly agree. We focused on the T-CRS factor-derived subscale score for behavior control, which included 8 items (e.g., Tolerates frustration). Values on this subscale ranged from 0 to 40 with higher scores indicating greater social-emotional-behavioral regulation. Reliability for this subscale was α = 0.88 in the fall and α = 0.89 in the spring.

Approaches to Learning.

Teachers rated children’s approaches to learning skills using the reschool Learning Behaviors Scale (PLBS; McDermott et al., 2002), with fall assessments collected in November and spring assessments collected in May. The PLBS includes 29 learning-related items that reflect observable classroom behaviors and is intended for use of children between ages 3 years to 5.5 years. Teachers rate each item on a 3-point scale: most often applies; sometimes applies; doesn’t apply. PLBS factor-derived subscale scores include competence motivation (11 items; e.g., Shows a lively interest in activities), attention/persistence (9 items; e.g., Sticks to an activity for as long as can be expected for a child of this age), and attitude toward learning (7 items; e.g., Is willing to be helped), in additional to a total summary score (29 items). This study used the PLBS total score. Reliability was α = 0.90 in the fall and α = 0.87 in the spring.

2.3. Data Analysis Approach

Our primary interest is in the ability of behavioral engagement (measured by the inCLASS; Downer et al., 2010) to mediate the relations of executive functioning with SR gains. We used estimates of EF from fall as our independent variable, estimates of the inCLASS domains midway through the PreK year (winter) obtained through latent growth curve modeling as our mediators, and residualized change scores in SR constructs as our outcomes. We estimated midyear inCLASS using latent growth curve modeling rather than using the single winter assessment to take advantage of the full set of inCLASS data we collected, improving the precision of our estimates. We chose to set the intercepts to midyear (winter) values so that the values represented estimated values of behavioral engagement after the assessment of executive functioning and before the assessments of school readiness to make it easier to interpret our mediation models.

We had relatively low missingness on study variables. Missingness on individual variables ranged from 1.4% to 7.7% with a median of 6.5%. Out of the 767 cases in our data set, 651 (84.9%) had complete data. Twenty-four participants (3.1%) had values for all variables except for the executive functioning composite. No other pattern of missingness represented more than 3% of the cases. Our analyses do not provide us with any reason to suspect the presence of non-random missingness in our data.

All models were estimated in Mplus 8.6 (Muthén & Muthén, 1998–2017). Model coefficients were obtained using Full Information Maximum Likelihood estimation, which has been identified as one of the optimal ways to handle missingness (Peugh & Enders, 2004). Bootstrap confidence intervals were used to test mediation because of the non-normal distribution of indirect effects (Preacher & Hayes, 2008). Each combination of six SR outcomes and four inCLASS domains was examined in a separate model. The standard errors of our coefficients were adjusted for teacher-level clustering using a sandwich estimator (see McNeish et al., 2017).

Across all models, we accounted for child characteristics (gender, race/ethnicity, primary language, and age), family factors (maternal educational attainment), and teacher characteristics (gender, race/ethnicity, education, PreK teaching experience) with established links to all child-level outcomes to better isolate linkages among EF, behavioral engagement, and SR skill gains.

3. Results

3.1. Linkages between Executive Functioning and School Readiness Skill Gains

To address research question 1 (To what extent does children’s EF predict SR skill gains during PreK?), we examined the relations of EF with SR outcome gains, which are presented in Supplemental Table 1. We observed that fall EF was positively related to gains in the domains of mathematics (as measured by the WJ Math Reasoning score), gains in the approaches to learning domain (as measured by the PLBS Total Score), and gains in the language domain (as measured by the NAP-2 Total Score). The associations of fall EF with gains in the domains of literacy and social-emotional-behavioral skills were not statistically significant.

3.2. Linkages between Behavioral Engagement and School Readiness Skill Gains

To address research question 2 (To what extent does children’s behavioral engagement in PreK classrooms predict SR skill gains?), we examined the relations of behavioral engagement growth coefficients with SR outcome gains. The latent growth curve models that were applied to the behavioral engagement variables are illustrated in Figure 1. These models estimated both latent intercepts and latent slopes, and the coding was designed such that the latent intercept estimated the mean value at midyear. On average, behavioral engagement was relatively low across all domains (ranging from an average of 1.38 for Negative Classroom Engagement to 3.57 for Positive Task Engagement on a scale of 1–7; see Table 1).

Figure 1.

Latent growth curve model used for behavioral engagement variables.

After estimating the latent growth curves, we then used path modeling to relate the latent intercepts and slopes to gains in SR outcomes. A conceptual illustration of these models is presented in Figure 2. The inclusion of the fall outcome as a predictor changes the interpretation of the intercept and slope coefficients so they represent relations of these variables with gains in the outcomes. The estimated coefficients from these path models are presented in Supplemental Table 2. None of the behavioral engagement latent slopes were significantly related to SR outcome gains, although the midyear estimates of several behavioral engagement variables were significantly related to SR outcome gains. Midyear Negative Classroom Engagement was negatively related to gains in the academic domains of literacy (as measured by the WJ-III Basic Reading Total Raw Score), and math (as measured by the WJ-III Math Reasoning Total Raw Score), as well as gains in the social-emotional-behavioral domain (ERC Emotion Regulation; T-CRS Behavior Control), and the approaches to learning domain (PLBS Total Score). Additionally, midyear Positive Task Engagement was positively related to gains in the approaches to learning domain (as measured by the PLBS Total Score). The other inCLASS domains (Positive Teacher Engagement; Positive Peer Engagement) were not significantly related to gains in SR outcomes.

Figure 2.

Illustration of predictive models.

3.3. Behavioral Engagement as a Mediator of the Linkage between EF and SR Skill Gains

To address research question 3 (To what extent does behavioral engagement mediate the relationship of EF with SR skill gains?), we examined the extent to which the behavioral engagement variables mediated the effects of EF on SR outcome gains. Table 2 presents the results of bootstrapped tests of indirect effects of EF on gains in outcomes through each of our behavioral engagement variables (Positive Teacher Engagement, Positive Peer Engagement, Positive Task Engagement, Negative Classroom Engagement). Each mediation test was examined in a separate model. The results indicate that Negative Classroom Engagement significantly mediates the associations of EF with gains in the domains of literacy (i.e., WJ-III Basic Reading Total Raw Score), social-emotional-behavioral skills (i.e., ERC Emotion Regulation; T-CRS Behavior Control), and the approaches to learning domain (i.e., PLBS Total Score), with all p’s < .05. In each of these cases, fall EF was negatively related to Negative Classroom Engagement, which in turn was negatively related to gains in SR outcomes. We did not find evidence that any other behavioral engagement variables mediated the effect of EF on SR skill gains.

Table 2.

Mediation tests.

			Bootstrap CI
IV	Outcome	Mediator	Lower 2.5%	Upper 2.5%	Significant
EF	WJ-III Basic Reading Total Raw Score	inCLASS Positive Teacher Engagement	−0.034	0.075
		inCLASS Positive Peer Engagement	−0.176	0.162
		inCLASS Positive Task Engagement	−0.061	0.453
		inCLASS Negative Classroom Engagement	0.087	0.313	*
EF	WJ-III Math Reasoning Total Raw Score	inCLASS Positive Teacher Engagement	−0.15	0.016
		inCLASS Positive Peer Engagement	−0.156	0.118
		inCLASS Positive Task Engagement	−0.104	0.408
		inCLASS Negative Classroom Engagement	0	0.261
EF	ERC Emotion Regulation	inCLASS Positive Teacher Engagement	−0.142	0.026
		inCLASS Positive Peer Engagement	−0.149	0.122
		inCLASS Positive Task Engagement	−0.115	0.262
		inCLASS Negative Classroom Engagement	0.051	0.289	*
EF	T-CRS Behavioral Control	inCLASS Positive Teacher Engagement	−0.155	0.018
		inCLASS Positive Peer Engagement	−0.241	0.094
		inCLASS Positive Task Engagement	−0.297	0.293
		inCLASS Negative Classroom Engagement	0.095	0.551	*
EF	PLBS Total Score	inCLASS Positive Teacher Engagement	−0.244	0.027
		inCLASS Positive Peer Engagement	−0.126	0.55
		inCLASS Positive Task Engagement	−0.035	1.012
		inCLASS Negative Classroom Engagement	0.238	0.892	*
EF	NAP-2 Total Score	inCLASS Positive Teacher Engagement	−0.018	0.108
		inCLASS Positive Peer Engagement	−0.006	0.288
		inCLASS Positive Task Engagement	−0.236	0.173
		inCLASS Negative Classroom Engagement	−0.112	0.102

Note. EF = executive function; ERC = Emotion Regulation Checklist; inCLASS = Individualized Classroom Assessment Scoring System; NAP-2 = Narrative Assessment Protocol-2; PLBS = Preschool Learning Behaviors Scale; T-CRS = Teacher-Child Rating Scale; WJ-III = Woodcock Johnson-III Tests of Achievement

4. Discussion

This study found that EF measured at the beginning of the PreK year was positively related to gains in the domains of mathematics, approaches to learning, and language, but not to gains in the domains of literacy or social-emotional-behavioral skills. Additionally, although conflictual interactions between children and their teachers and peers occur at relatively low levels overall, behavioral engagement characterized by conflict (Negative Classroom Engagement) was consistently and negatively associated with PreK SR gains in the domains of literacy, mathematics, social-emotional-behavioral skills, and approaches to learning. Positive Task Engagement was positively related to gains in the approaches to learning domain. Furthermore, the presence of significant mediation effects suggests that entering PreK with lower executive functioning skills is associated with greater levels of observed aggression, negative affect, and attention seeking toward teacher or peers, midyear (i.e., Negative Classroom Engagement), which is, in turn, associated with poorer school readiness skill gains in PreK. This study suggests the importance of aligning supports for children’s behavior and engagement in PreK classroom contexts with their developing EF to support SR skill development (such as using video to identify and analyze challenging behaviors and interactions, and plan targeted supports, which we describe later in the discussion).

Analyses linking incoming PreK EF skills to SR skill gains produced mixed results, with significant associations in the areas of math, approaches to learning and language and non-significant associations for literacy and social-emotional-behavioral skills. These findings are consistent with prior work with children from economically disadvantaged backgrounds showing associations between EF and certain SR skills (e.g., Cameron et al., 2019; Finders et al., 2021; Morgan et al., 2017). However, the current study was inconsistent with prior findings indicating direct associations of EF skills with literacy (e.g., Finders et al., 2021; Hooper et al., 2020; Morgan et al., 2017) and social-emotional-behavioral skills (e.g., Vernon-Feagans et al., 2016). The present study’s mixed results are not entirely surprising considering prior research indicating stronger associations of EF with math than with literacy (e.g., Schmitt et al., 2017) and meta-analytic results suggesting that the relationship between EF and academic skills depends on the specific aspects of EF being measured (Allan et al., 2014).

Unexpectedly, children’s behavioral engagement with teachers, peers, and learning tasks were mostly not significantly associated with SR skill gains, with the exception of positive engagement with tasks being related to gains in teacher-reported approaches to learning. This association comports with expected congruence between observed behaviors (e.g., sustained attention, active engagement, persistence, and self-directed learning) and teacher-reported behaviors (e.g., competence motivation, attention/persistence, attitude toward learning) within the same SR domain. It may be the case that positive engagement with teachers and peers were not related to gains in cross-domain SR skills (i.e., language, literacy, math) or partially within-domain SR skills (i.e., social-emotional-behavioral skills). That within-domain associations were stronger than cross-domain associations is consistent with prior research (Pace et al., 2019).

In contrast, as expected, Negative Classroom Engagement was negatively associated with gains for four of the five SR skill domains. Importantly, behavioral engagement was relatively low across all domains measured. For example, mean scores were highest for the inCLASS Positive Task Engagement domain (3.57), on a scale where scores of 1 to 2 represent lower levels of behavioral engagement quality overall, scores of 3 to 5 represent mixed or medium levels of engagement, and scores of 6 to 7 represent high levels of engagement. By comparison, mean scores were in the low-level range for the domains of Positive Teacher Engagement (2.03) and Positive Peer Engagement (2.25). The Negative Classroom Engagement domain mean (1.36) indicates particularly low rates of negative engagement with teachers, peers, and learning tasks.

In addition to examining the means, we can consider the ranges of the observed scores to obtain information about what types of interactions might be possible within our sample. Scores on the Positive Task Engagement domain ranged from 1.17 to 6, suggesting some of the children in the sample had the potential to be positively engaged with their teacher at high levels. In comparison, scores for Positive Teacher Engagement ranged from 1 to 4.50 and scores for Positive Peer Engagement ranged from 1 to 5.14, suggesting lower potential for these domains than for Positive Task Engagement. Scores on Negative Classroom Engagement ranged from 1 to 3.72, indicating low potential for children to be negatively engaged in the classroom. Our findings are consistent with a recent latent profile analysis of behavioral engagement (Rojas & Abenavoli, 2021) that found mean scores to be highest for aspects of Positive Task Engagement and lowest for aspects of Negative Classroom Engagement. In that study, even children classified in the two profiles with the most elevated ratings for conflict with teachers and peers had low mean scores for conflict with teachers and conflict with peers. Crucially, these descriptive results in conjunction with associations of behavioral engagement with SR skill gains suggest that even low levels of negative classroom engagement (or some cycle scores at the lower end of the measurement range) may hinder children’s SR skill development.

For example, Rojas and Abenavoli’s profile analysis found that children classified in the mild conflict profile also had lower language scores in spring of PreK, regardless of whether their teacher rated their relationship in fall of PreK to be close or conflictual. Similarly, Weiss et al., (2023) found even moderate levels of conflictual behavior during learning activities in preschool and kindergarten were associated with lower literacy skills in first grade.

We found that Negative Classroom Engagement significantly mediates the associations of EF with gains in the domains of literacy, social-emotional-behavioral skills, and approaches to learning. In each case, fall EF was negatively related to Negative Classroom Engagement, which in turn was negatively related to SR skill gains. Put another way, entering PreK with lower executive functioning skills is associated with greater levels of observed aggression, negative affect, and attention seeking directed toward the teacher or peers, midway through the year, which is in turn, associated with smaller gains in literacy, social-emotional-behavioral skills, and approaches to learning. None of the other behavioral engagement variables mediated the effects of EF on SR skill gains. Findings from the present study are consistent with those of Alamos et al. (2022), who found that children beginning PreK with lower inhibitory control (an aspect of EF) engaged in more conflictual interactions, and that the conflictual interactions were associated with lower ratings on teacher-reported measures of emotion regulation (an aspect of SR). Taken together with the present study, it appears that even mild levels of negative classroom engagement can lead to decrements in aspects of SR. Relatedly, additional research demonstrates that SR gains may in fact be conditional on close and less conflictual relationships with teachers, even in the presence of high-quality classroom environments (Nguyen et al., 2020). Knowing that children arrive to PreK with wide variability in their EF skills, this mediational pathway underscores the importance of teacher support for translating incoming EF skills into engagement behaviors in the classroom to ensure optimal exposure to learning opportunities that lead to SR skill development. In the PreK classroom, activities that support this mediational pathway could include playing games that encourage flexible thinking, and that require children to pay attention, listen and follow directions, wait, and switch their focus (e.g., change tempo, change direction). Other activities could support aspects of working memory (e.g., using visuals and songs to keep things in mind and by providing hints or prompts to help children remember rules and expectations) and inhibitory control, such as by supporting children to plan and individualize their learning activities and by monitoring and supporting their engagement stay on task (ECE Resource Hub, 2024).

4.1. Limitations and Future Directions

Although the present study provides a better understanding of connections among EF, behavioral engagement, and SR for PreK children of low-income backgrounds, there are limitations to consider. First, the study was observational rather than experimental. Although we controlled for child-, teacher-, and classroom-level factors that may account for variance in the associations between EF, behavioral engagement, and SR, the study design precludes drawing any causal conclusions. It is also possible that we failed to measure some constructs that would provide a better understanding of these connections. As one example, there are inequities in classroom interactions between children of racially minoritized backgrounds as compared to their White peers, and it may be advantageous to triangulate measurement of behavioral engagement with additional tools, such as the Assessing Classroom Sociocultural Equity Scale (ACSES; Curenton et al., 2020). As another example, having more information about children’s home and early care and education experiences (prior to Pre-K entry) might have been helpful in better understanding children’s EF and behavioral engagement at Pre-K entry. According to the National Center for Education Statistics (Cui & Natzke, 2021), roughly 42% of children < age 1 year, 55% of children ages 1 to 2 years, and 74% of children ages 3 to 5 years have at least one weekly nonparental care arrangement. It is thus likely that there was variation in children’s early care and education experiences (e.g., access to and enrollment in high-quality early care), and that such variation would have been associated with children’s incoming EF and behavioral engagement.

Second, three of the four SR outcomes showing significant mediation did not show significant overall effects of EF. While these findings might appear to be inconsistent, it is a known characteristic of mediation analysis that tests of the indirect effect of a predictor on an outcome through a mediator can be more powerful than the overall test of that predictor on the outcome (Kenny & Judd, 2014). Separating the effect of the predictor on the outcome into smaller components – the effect of the predictor on the mediator and the effect of the mediator on the outcome – can reduce the extraneous variability being considered in each test, leading to greater precision in the individual estimates and more power when testing the influence of the predictor on the outcome. As the power of the experimental design increases, we would expect the discrepancy in these results to disappear, but at certain levels of power, the ability to detect the mediated effect can outstrip the ability to detect the overall effect. It would therefore appear that our design was powerful enough to detect the effects of EF on gains in outcomes through mediation, but not powerful enough to detect the same effects in overall tests.

Third, the study sample was restricted to PreK children attending publicly funded preschool programs with eligibility requirements for socioeconomic risk (e.g., family income ≤200% of the federal poverty guidelines (350% for students with special education needs), family homelessness, or parents/guardians lacking a high school diploma.). Thus, our findings may not generalize to students from higher SES backgrounds or to students attending PreK programs serving socioeconomically heterogeneous populations. However, the present study’s findings extend prior research using a more comprehensive set of EF measures and by examining linkages between EF, individualized behavioral engagement, and multiple SR domains.

Finally, although psychometric work supports examining behavioral engagement using the four inCLASS domains used in the present study, Negative Classroom Engagement combines individual children’s negative interactions with teachers, peers, and learning tasks in a way that does not permit examination of whether one or more interaction types may be driving associations for negative classroom engagement (Sabol et al., 2018). However, research by Rojas and Abenavoli (2021) suggests children who engage negatively in the classroom, as indicated by latent profiles marked by mild, high, or extreme conflict levels, tend to engage negatively with teachers, peers, and learning tasks, rather than in only one or two of these contexts.

Despite its limitations, this study adds to our understanding of how executive functioning links to gains in SR skills, highlighting the mediating role of negative behavioral engagement in the PreK classroom. Although this study found that the association of EF with SR skill gains was mediated by negative behavioral engagement rather than positive engagement with teachers, peers, or learning tasks, it is reassuring that negative classroom engagement was observed to occur at relatively low levels. The present study suggests a number of implications of these relations. For example, it is critical that aspiring EC educators have the opportunity to learn about and practice supporting young children’s EF and behavioral engagement before entering the workforce. Thus, teacher preparation programs should offer coursework and field experiences focused on these areas (e.g., Neitzel, 2018). For in-service EC professionals, observing and monitoring individual children’s behavioral engagement in PreK classrooms may help support the development of SR skills and early school performance. EC mental health consultation models represent one such avenue for incorporating data-driven feedback to support children’s positive engagement (and reduce negative engagement) with teachers, peers, and learning activities in the PreK classroom. For example, applying the Learning to Objectively Observe Kids (LOOK) model, EC educators use video to objectively observe their own classroom, identify and analyze contexts in which challenging behaviors occur, and plan with a consultant for how to support children in regulating their behavior, attention, and emotions (Downer et al., 2018). Although EC mental health consultation is now prevalent in all 50 US states (Silver et al., 2022), not all ECE providers have equitable access to high-quality professional development that involves a coaching or consultation component (Lang et al., 2023). Initiatives that focus on enhancing access to underrepresented ECE providers and communities are a critical area for continued investment. Additional applied research is also warranted to inform how the ECE field can improve current Quality Rating and Improvement Systems (QRIS) measures. Current QRIS approaches gloss over potential individual differences in children’s moment-to-moment interactions in the PreK classroom, as they aggregate quality information to the center level. Measuring children’s individual experiences is recommended to enhance the accuracy and equity of QRIS (Sabol, 2021). Our study findings also suggest that efforts be made to identify children with lower EF skills at PreK entry (e.g., see Silva et al., 2022) so that additional supports can be provided to reduce the likelihood of the child engaging in negative interactions and establish a positive trajectory for school readiness skill development.

Highlights.

• Executive functioning at preschool entry is positively related to school readiness skill gains.

• Children’s negative classroom engagement is negatively associated with school readiness gains.

• Observed positive task engagement positively predicts teacher-reported learning approaches.

• Negative classroom engagement may underlie executive functioning—school readiness linkage.