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Challenges and Opportunities in Teaching through Interactions Framework: A Three-Level Meta-Analysis of the CLASS Measure and Children's Vocabulary Skills

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Title: Challenges and Opportunities in Teaching through Interactions Framework: A Three-Level Meta-Analysis of the CLASS Measure and Children's Vocabulary Skills
Language: English
Authors: Hongbin Xie, Hongliu Ouyang, Nik Rosila Nik Yaacob, Daimin Feng, Shuang Wang
Source: Early Childhood Education Journal. 2025 53(5):1605-1625.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 21
Publication Date: 2025
Document Type: Journal Articles
Information Analyses
Education Level: Early Childhood Education
Preschool Education
Descriptors: Vocabulary Development, Preschool Children, Socioeconomic Status, Meta Analysis, Databases, Classroom Environment, Preschool Teachers, Teacher Student Relationship, Correlation, Age Differences, Research Reports, Classroom Techniques, Teaching Methods, Family Characteristics, Early Childhood Education, Educational Quality
Assessment and Survey Identifiers: Classroom Assessment Scoring System
DOI: 10.1007/s10643-024-01703-y
ISSN: 1082-3301
1573-1707
Abstract: In Early Childhood Education and Care (ECEC) programs, the quality of teacher-child interactions is regarded to be important for children's vocabulary development. However, prior studies on the relationships between teacher and child, as measured by the Classroom Assessment Scoring System (CLASS), and children's vocabulary skills are inconsistent. In this study, we conducted a three-level meta-analysis to investigate the correlation between three CLASS domains and preschool children's vocabulary skills and then explored the moderating effects of vocabulary components, family SES, publication year, and sample mean age. Relevant literature was searched using four databases (Web of Science, PsycINFO, PsycARTICLES, ERIC) and Google Scholar, leading to the identification of 23 articles published between 2010 and 2022 meeting the inclusion criteria. The findings indicated that the overall effect of the associations between "Emotional Support," "Classroom Organization," "Instructional Support," and vocabulary skills was small to moderate in magnitude. Sensitivity and meta-bias analyses generally supported the robustness of the pooled effect of the association between three CLASS domains and children's vocabulary skills. Also, the association between "Emotional Support" and vocabulary skills was moderated by SES, and the components of vocabulary skills, while "Classroom Organization" and "Instructional Support" were only moderated by the components of vocabulary skills. Implications for future research on assessing the quality of early childhood education are discussed.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1470663
Database: ERIC
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  Value: <anid>AN0185036407;5mx01jun.25;2025May12.06:06;v2.2.500</anid> <title id="AN0185036407-1">Challenges and Opportunities in Teaching Through Interactions Framework: A Three-level Meta-Analysis of the CLASS Measure and Children's Vocabulary Skills </title> <p>In Early Childhood Education and Care (ECEC) programs, the quality of teacher–child interactions is regarded to be important for children's vocabulary development. However, prior studies on the relationships between teacher and child, as measured by the Classroom Assessment Scoring System (CLASS), and children's vocabulary skills are inconsistent. In this study, we conducted a three-level meta-analysis to investigate the correlation between three CLASS domains and preschool children's vocabulary skills and then explored the moderating effects of vocabulary components, family SES, publication year, and sample mean age. Relevant literature was searched using four databases (Web of Science, PsycINFO, PsycARTICLES, ERIC) and Google Scholar, leading to the identification of 23 articles published between 2010 and 2022 meeting the inclusion criteria. The findings indicated that the overall effect of the associations between Emotional Support, Classroom Organization, Instructional Support, and vocabulary skills was small to moderate in magnitude. Sensitivity and meta-bias analyses generally supported the robustness of the pooled effect of the association between three CLASS domains and children's vocabulary skills. Also, the association between Emotional Support and vocabulary skills was moderated by SES, and the components of vocabulary skills, while Classroom Organization and Instructional Support were only moderated by the components of vocabulary skills. Implications for future research on assessing the quality of early childhood education are discussed.</p> <p>Keywords: Teaching Through Interactions Framework; CLASS; Vocabulary Skills; Three-level Meta-analysis; Education Specialist Studies In Education</p> <p>Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s10643-024-01703-y.</p> <hd id="AN0185036407-2">Introduction</hd> <p>Vocabulary development falls within the domain of language content, including recognizing and understanding words (receptive vocabulary) and producing and using words actively (expressive vocabulary). Vocabulary development reflects children's overall language status and is a precursor to school achievement and progress (NICHD Early Child Care Research Network, [<reflink idref="bib71" id="ref1">71</reflink>]; Sénéchal et al., [<reflink idref="bib94" id="ref2">94</reflink>]; Storch & Whitehurst, [<reflink idref="bib99" id="ref3">99</reflink>]). Research has shown that high-quality classroom processes, especially teacher–child responsive interaction, are associated with greater gains in children's language development (Hamre et al., [<reflink idref="bib46" id="ref4">46</reflink>]; Hu et al., [<reflink idref="bib55" id="ref5">55</reflink>]).</p> <p>According to the Teaching Through Interactions (TTI) framework, the influence of teachers and classrooms on children mainly emerges through teacher–child interactions (Hamre et al., [<reflink idref="bib45" id="ref6">45</reflink>]). This framework suggests that teacher–child interactions are categorized into three domains: <emph>Emotional Support</emph>, <emph>Classroom Organization</emph>, and <emph>Instructional Support</emph> (Hamre et al., [<reflink idref="bib45" id="ref7">45</reflink>])<emph>.</emph> The theoretical foundation for this domain specificity TTI framework assumes that <emph>Emotional Support</emph> enhances children's social and emotional functioning, <emph>Classroom Organization</emph> promotes positive children's behavior and attention, and <emph>Instructional Support</emph> promotes children's language competence. The Classroom Assessment Scoring System (CLASS; Pianta et al., [<reflink idref="bib80" id="ref8">80</reflink>]), which aligns with the TTI framework, is commonly used to conceptualize and measure teacher–child interactions and has been validated and applied in many countries (e.g., Cadima et al., [<reflink idref="bib17" id="ref9">17</reflink>]; Leyva et al., [<reflink idref="bib65" id="ref10">65</reflink>]; Pakarinen et al., [<reflink idref="bib72" id="ref11">72</reflink>]; von Suchodoletz et al., [<reflink idref="bib111" id="ref12">111</reflink>]). However, there is complexity in understanding the relationship between teacher–child interactions and children's development (Downer et al., [<reflink idref="bib31" id="ref13">31</reflink>]). Although several studies support the domain specificity within the TTI framework (e.g., Mashburn et al., [<reflink idref="bib67" id="ref14">67</reflink>]; Rimm-Kaufman et al., [<reflink idref="bib87" id="ref15">87</reflink>]), evidence has shown cross-domain linkages such as <emph>Classroom Organization</emph> have been linked to language development (Yang et al., [<reflink idref="bib116" id="ref16">116</reflink>]).</p> <p>In this study, we expect to understand these complexities in the relationship between teacher–child interaction quality and children's vocabulary development, by conducting a meta-analysis. Previous studies using the CLASS measure have yielded inconsistent results (e.g., Finders et al., [<reflink idref="bib38" id="ref17">38</reflink>]; Hu et al., [<reflink idref="bib55" id="ref18">55</reflink>]; McDoniel et al., [<reflink idref="bib68" id="ref19">68</reflink>]), and a comprehensive quantitative synthesis of this relationship is lacking. We employed a three-level meta-analysis approach, allowing for a more nuanced investigation of the relationship between the three CLASS domains (e.g., <emph>Emotional Support</emph>, <emph>Classroom Organization</emph>, and <emph>Instructional Support</emph>) and children's vocabulary skills, separately. Compared to the traditional meta-analysis (two-level model), the three-level meta-analysis can address the potential problem of non-independent effect sizes when multiple effect sizes are extracted from an article (e.g., the same participants contribute to two or more effect sizes). As the three-level meta-analysis did not reduce the total number of effect sizes included in the analysis, the precision of the meta-analysis results will also be higher (Assink & Wibbelink, [<reflink idref="bib4" id="ref20">4</reflink>]). This study finding should further reveal the TTI framework's domain-specific assumptions and their relationship with children's vocabulary development. The study further clarifies the challenges and opportunities of the current knowledge regarding the relationship between the teacher–child interaction quality measured by CLASS within the TTI framework and child development. Therefore, the following sections concerning the development of children's vocabulary, the TTI framework and CLASS Measure, the cross-domain associations and non-significant associations between the CLASS and children's vocabulary skills, and potential moderators of the association between CLASS and children's vocabulary skills to further understand the complexities mentioned in the relationship between teacher–child interaction quality and children's vocabulary development.</p> <hd id="AN0185036407-3">Development of Children's Vocabulary</hd> <p>Children's vocabulary skills are usually assessed in the aspect of word comprehension (receptive vocabulary) and word production (expressive vocabulary) (Hoff, [<reflink idref="bib53" id="ref21">53</reflink>]). Receptive and expressive vocabulary is crucial to evaluate children's knowledge of word order, conceptual knowledge, word knowledge, and grammatical rules (Scarborough, [<reflink idref="bib91" id="ref22">91</reflink>]; Storch & Whitehurst, [<reflink idref="bib99" id="ref23">99</reflink>]). Children's vocabulary development is essential for their language, literacy, and communication during preschool (NICHD Early Child Care Research Network, [<reflink idref="bib71" id="ref24">71</reflink>]). Conversely, children with poor vocabulary development may have inadequate school readiness and be at risk for later academic problems (NICHD Early Child Care Research Network, [<reflink idref="bib71" id="ref25">71</reflink>]). Children's early life language experiences play a crucial role in their development. More recently, Gilkerson et al. ([<reflink idref="bib40" id="ref26">40</reflink>]) found that the frequency of conversational interactions between adults and children is significantly linked to children's later vocabulary. Also, research has found that the amount of adult language, lexical diversity, and lexical complexity are positively correlated with children's language and cognitive abilities (d'Apice & von Stumm, [<reflink idref="bib27" id="ref27">27</reflink>]). However, there have been calls to broaden the focus on language environments to include early childhood learning environments (Purpura, [<reflink idref="bib85" id="ref28">85</reflink>]), particularly the relationship between teacher–child interactions and children's development (Yang et al., [<reflink idref="bib116" id="ref29">116</reflink>]).</p> <p>Early childhood learning environments, such as preschools, significantly affect children's language skills (Hansen & Broekhuizen, [<reflink idref="bib48" id="ref30">48</reflink>]). One primary reason is that classroom teacher–child interaction provides a vital background for the development of young children. Within the Developmental Systems Theory (Bronfenbrenner & Morris, [<reflink idref="bib10" id="ref31">10</reflink>]), teacher–child relationships are dyadic systems involving biological, behavioral, cultural, psychological, and temporal processes. In this dyadic system, knowledge and experience transmitted between adults and children affect children's cognitive development (Sroufe, [<reflink idref="bib98" id="ref32">98</reflink>]). The study found that children's receptive and expressive vocabulary gains were significantly associated with their teachers' skill in identifying effective interactions (Cash & Pianta, [<reflink idref="bib22" id="ref33">22</reflink>]). However, the growing literature on teacher–child interaction reveals mixed findings regarding children's vocabulary development (Pianta et al., [<reflink idref="bib81" id="ref34">81</reflink>], [<reflink idref="bib82" id="ref35">82</reflink>]). Weiland et al. ([<reflink idref="bib113" id="ref36">113</reflink>]) found almost no correlation between the teacher–child interactions and children's vocabulary. Also, Ulferts et al. ([<reflink idref="bib103" id="ref37">103</reflink>]) suggest null associations between teacher–child interactions and children's language skills. The mixed results suggest that conceptualizations and measures of teacher–child interactions may have a complex relationship with children's cognitive development (Hamre et al., [<reflink idref="bib46" id="ref38">46</reflink>]; Pianta et al., [<reflink idref="bib81" id="ref39">81</reflink>], [<reflink idref="bib82" id="ref40">82</reflink>]).</p> <hd id="AN0185036407-4">Teaching Through Interactions Theoretical Framework and CLASS Measure</hd> <p>In an early childhood classroom, children's academic and social skills gains are linked to the quality of teaching they experience (Hamre et al., [<reflink idref="bib45" id="ref41">45</reflink>]). Based on prior research on effective teaching (Brophy, [<reflink idref="bib11" id="ref42">11</reflink>]), Hamre et al. ([<reflink idref="bib45" id="ref43">45</reflink>]) created the TTI framework, which focused on teacher–child interactions in the present moment and their relationships to children's social and academic development. According to the TTI framework (Hamre et al., [<reflink idref="bib45" id="ref44">45</reflink>]), the CLASS defines the multi-faceted nature of teacher–child interaction quality through three broad domains: <emph>Emotional Support</emph> (ES), <emph>Classroom Organization</emph> (CO), and <emph>Instructional Support</emph> (INS). <emph>Emotional Support</emph> focuses on teachers' response to the children's perspectives, interests, and emotional needs; <emph>Classroom Organization</emph> focuses on the behavioral support of teachers for promoting children's self-regulation ability and activity engagement (Pianta & Hamre, [<reflink idref="bib78" id="ref45">78</reflink>]; Rimm-Kaufman et al., [<reflink idref="bib87" id="ref46">87</reflink>]); <emph>Instructional Support</emph> encompasses teachers' ability to effectively implement learning activities in a way that best supports children's higher-order thinking and linguistic development (Pianta & Hamre, [<reflink idref="bib78" id="ref47">78</reflink>]). The CLASS framework is grounded not only in its theoretical basis but also in numerous empirical evidence supporting its domain-specificity hypothesis. Previous research has found that <emph>Emotional Support</emph> is associated with children's social-emotional competencies (Burchinal et al., [<reflink idref="bib16" id="ref48">16</reflink>]; Rimm-Kaufman et al., [<reflink idref="bib87" id="ref49">87</reflink>]; Wang et al., [<reflink idref="bib112" id="ref50">112</reflink>]). For instance, Zekarias Elka and Zhao ([<reflink idref="bib118" id="ref51">118</reflink>]) found that teachers' <emph>Emotional Support</emph> negatively and significantly predicted children's problem behavior. Others found that higher levels of preschool <emph>Classroom Organization</emph> are positively linked to children's executive function gains (e.g., Campos et al., [<reflink idref="bib19" id="ref52">19</reflink>]; LeBlanc, [<reflink idref="bib64" id="ref53">64</reflink>]; Pianta & Hamre, [<reflink idref="bib78" id="ref54">78</reflink>]; Rimm-Kaufman et al., [<reflink idref="bib87" id="ref55">87</reflink>]; Von Suchodoletz et al., [<reflink idref="bib110" id="ref56">110</reflink>]). Also, high-quality <emph>Instructional Support</emph> has been evidenced related to children's language and cognitive development (Burchinal et al., [<reflink idref="bib16" id="ref57">16</reflink>]; Mashburn et al., [<reflink idref="bib67" id="ref58">67</reflink>]; Yang et al., [<reflink idref="bib116" id="ref59">116</reflink>]). Our meta-analysis employed the CLASS framework, which is validated across diverse educational settings for assessing classroom quality (Perlman et al., [<reflink idref="bib75" id="ref60">75</reflink>]). The multidimensional approach of the CLASS/TTI framework is crucial for understanding the impact of teaching quality on student outcomes, including vocabulary development (Hatfield et al., [<reflink idref="bib50" id="ref61">50</reflink>]; Hu et al., [<reflink idref="bib57" id="ref62">57</reflink>]). The CLASS framework's comprehensive model aligns with diverse classroom realities and substantiates the longitudinal impact of teaching quality on student learning and development (e.g., Carr et al., [<reflink idref="bib21" id="ref63">21</reflink>]; Goble et al., [<reflink idref="bib42" id="ref64">42</reflink>]; Hatfield et al., [<reflink idref="bib50" id="ref65">50</reflink>]; Hu et al., [<reflink idref="bib55" id="ref66">55</reflink>]). This framework's applicability in varying educational contexts makes it an appropriate tool for analyzing the effectiveness of teaching practices concerning student vocabulary outcomes.</p> <p>Despite numerous studies examining the relationship between CLASS domains and child development (e.g., Goble et al., [<reflink idref="bib42" id="ref67">42</reflink>]; Hu et al., [<reflink idref="bib55" id="ref68">55</reflink>]; Perlman et al., [<reflink idref="bib75" id="ref69">75</reflink>]), recent studies have shown complexities in this relationship. Guerrero-Rosada et al. ([<reflink idref="bib43" id="ref70">43</reflink>]) found null relations between CLASS scores and gains in children's language, math, and social skills, suggesting limitations in the predictive capabilities of CLASS. Similarly, McDoniel et al. ([<reflink idref="bib68" id="ref71">68</reflink>]) suggest that widely used measures of classroom quality, including CLASS, show a limited correlation with preschool outcomes. Moreover, the CLASS is often associated with modest effect sizes on child outcomes (e.g., effect sizes in the range of 0.05 to 0.10). Pianta et al., ([<reflink idref="bib81" id="ref72">81</reflink>], [<reflink idref="bib82" id="ref73">82</reflink>]) argued that measuring quality in early education is complex, and CLASS may only capture part of this complexity. In addition to the small effect size, CLASS has known limitations, such as high correlations among three domains (e.g., range of <emph>r</emph> = 0.75–0.98), and the fit indices of the three-factor CLASS model are not ideal (Hamre et al., [<reflink idref="bib45" id="ref74">45</reflink>]; Pakarinen et al., [<reflink idref="bib72" id="ref75">72</reflink>]). This evidence and limitations suggest the need for a more nuanced understanding and application of the CLASS/TTI framework.</p> <hd id="AN0185036407-5">The Cross‑domain Associations Between the CLASS and Children's Vocabulary Skill</hd> <p>Based on the assumptions of the TTI theoretical framework, <emph>Emotional Support</emph> is related to children's social-emotional competencies (Hamre et al., [<reflink idref="bib45" id="ref76">45</reflink>]). Attachment Theory (Bowlby, [<reflink idref="bib9" id="ref77">9</reflink>]) indicates that an adult–child attachment relationship provides children with a sense of security, promoting self-reliance and risk-taking when exploring the world. Thus, teachers with high levels of <emph>Emotional Support</emph> are positively linked to children's social competence (Mashburn et al., [<reflink idref="bib67" id="ref78">67</reflink>]). In addition, <emph>Classroom Organization</emph> is related to children's self-regulation. In high-level classroom organizations, teachers typically proactively manage children's behavior, use learning time effectively, and maintain children's attention and engagement during the instructional process (Rimm-Kaufman et al., [<reflink idref="bib87" id="ref79">87</reflink>]). Research shows that when classrooms have consistent and clear organizational routines for behavior and time use, children exhibit better behavioral control and more effective time management (Hu et al., [<reflink idref="bib56" id="ref80">56</reflink>]). Also, <emph>Instructional Support</emph> is typically associated with children's cognitive and language development. The theoretical foundation for <emph>Instructional Support</emph> is underlying research on children's cognitive and language development (e.g., Catts et al., [<reflink idref="bib26" id="ref81">26</reflink>]; Taylor et al., [<reflink idref="bib100" id="ref82">100</reflink>]). Adults provide the scaffolding of more complex skills, which can enhance children's cognitive and language development (Skibbe et al., [<reflink idref="bib96" id="ref83">96</reflink>]). Prior studies have shown that teachers with higher <emph>Instructional Support</emph> scores prefer to ask open-ended questions and provide prompt, constructive feedback to enhance children's interests, efforts, creativity, motivation, and learning strategies. These factors are crucial for developing preschoolers' vocabulary skills (Paulick, [<reflink idref="bib73" id="ref84">73</reflink>], [<reflink idref="bib74" id="ref85">74</reflink>]; Pianta, [<reflink idref="bib77" id="ref86">77</reflink>]).</p> <p>However, although some studies have identified evidence regarding the domain-specific relationships between CLASS domains and children's development, other studies found that CLASS's <emph>Emotional Support</emph> and <emph>Classroom Organizations</emph> have cross-domain links to children's vocabulary skills (e.g., Hu et al., [<reflink idref="bib57" id="ref87">57</reflink>]; Ulferts et al., [<reflink idref="bib103" id="ref88">103</reflink>]). For example, Curby et al. ([<reflink idref="bib24" id="ref89">24</reflink>]) found that children who received persistent teachers' <emph>Emotional Support</emph> during preschool had higher levels of language ability than those who did not. This result is supported by Schmitt et al. ([<reflink idref="bib92" id="ref90">92</reflink>]), who show that <emph>Emotional Support</emph> is a significant predictor of children's gains in vocabulary skills. Schmitt et al. ([<reflink idref="bib92" id="ref91">92</reflink>]) found that preschool children have more significant gains in vocabulary skills in high levels of <emph>Emotional Support</emph> classrooms than those with low <emph>Emotional Support</emph>. Moreover, several studies have demonstrated a positive correlation between children's vocabulary skill development and higher-quality <emph>Classroom Organization</emph> within educational settings (Dobbs-Oates et al., [<reflink idref="bib29" id="ref92">29</reflink>]; Downer et al., [<reflink idref="bib30" id="ref93">30</reflink>]). Dickinson et al. ([<reflink idref="bib28" id="ref94">28</reflink>]) found that children's variety of vocabulary development was related to teachers organizing the class, and that teacher–child interaction quality predicts children's literacy development and class engagement (Dobbs-Oates et al., [<reflink idref="bib29" id="ref95">29</reflink>]; Downer et al., [<reflink idref="bib30" id="ref96">30</reflink>]). Hu et al. ([<reflink idref="bib57" id="ref97">57</reflink>]) show that a classroom with high-quality <emph>Classroom Organization</emph> consistently predicts children's early vocabulary skills development. The CLASS cross-domain link may have the following reasons.</p> <p>First, the CLASS has high correlations among the three domains (Hamre et al., [<reflink idref="bib46" id="ref98">46</reflink>]), which may lead to inaccurate results when analyzing the relationship between CLASS domains and children's vocabulary development. Second, theory and research suggest that responsivity is an interactive property between teachers and children (Howes & Smith, [<reflink idref="bib54" id="ref99">54</reflink>]). Responsivity refers to timely and appropriate responses to children's needs or signals (Bornstein et al., [<reflink idref="bib8" id="ref100">8</reflink>]). Attachment Theory (Bowlby, [<reflink idref="bib9" id="ref101">9</reflink>]) highlights the importance of responsivity in fostering children's positive cognitive, social, and emotional development (Ainsworth et al., [<reflink idref="bib2" id="ref102">2</reflink>]). However, responsivity is reflected in each dimension of teacher-student interaction assessed by the CLASS framework (Hamre et al., [<reflink idref="bib46" id="ref103">46</reflink>]), which may lead to a CLASS cross-domain link to children's outcomes.</p> <hd id="AN0185036407-6">Non‑significant Associations Between the CLASS and Children's Vocabulary Skill</hd> <p>Prior studies have investigated the association between CLASS and children's vocabulary skills, revealing consistent findings regarding their relationship. In contrast, Goble et al. ([<reflink idref="bib42" id="ref104">42</reflink>]) found a weak correlation between teacher–child interactions and children's vocabulary skills in a longitudinal study. Moreover, after controlling for the CLASS and children's baseline scores (i.e., pretest scores), improvements in teacher–child interaction quality were not significantly linked to children's vocabulary skills across the year. Similarly, two recent longitudinal studies show the null correlation of three CLASS domains on children's language gains (Guerrero-Rosada et al., [<reflink idref="bib43" id="ref105">43</reflink>]; McDoniel et al., [<reflink idref="bib68" id="ref106">68</reflink>]). Findings from these studies suggest that teacher–child interactions and child outcomes may be related to methodological factors. Longitudinal studies control for the baseline scores by statistics, which may weaken the effect of CLASS on child outcomes (Zaslow et al., [<reflink idref="bib117" id="ref107">117</reflink>]).</p> <p>In contrast, cross-sectional studies that do not adjust baseline scores tend to overestimate the impact of quality. Additionally, the demographic characteristics (e.g., sample age, gender, and family socioeconomic status (SES)) and preschool/classroom level environmental factors (e.g., class size, education of teachers, and curriculum) were potentially related to the study results (Elicker & Thornburg, [<reflink idref="bib34" id="ref108">34</reflink>]). For instance, children from disadvantaged families tend to be more likely to enroll in low-quality early childhood education (ECE) environments than those from socio-economically advantaged families (Chaudry et al., [<reflink idref="bib18" id="ref109">18</reflink>]; Hillemeier et al., [<reflink idref="bib52" id="ref110">52</reflink>]). Also, Tilbe and Gai ([<reflink idref="bib102" id="ref111">102</reflink>]) found that classroom quality was not significantly related to children's receptive vocabulary. This finding may be attributed to poor basic conditions of the preschool environment, where structural aspects of quality could be more influential than the quality of teacher–child interaction. Furthermore, teacher–child interaction quality indicators may have critical thresholds (Finch et al., [<reflink idref="bib37" id="ref112">37</reflink>]). Eadie et al. ([<reflink idref="bib33" id="ref113">33</reflink>]) argued that significant improvements in teacher–child interactions through training may not lead to immediate changes in children's vocabulary. These changes might not be observed in the short term if the improvements do not reach the minimum thresholds necessary for affecting children's development. The non-significant findings highlight the complexity between teacher–child interaction and children's vocabulary skills. Therefore, we included these non-significant studies and considered the study characteristics (e.g., sample age; SES) in the meta-analysis, which was essential to clarify the significance of the association between CLASS domains and children's vocabulary skills.</p> <hd id="AN0185036407-7">Potential Moderators of the Association Between CLASS and Children's Vocabulary Skill</hd> <p>The children's family SES was potentially associated with research outcomes. Although positive teacher–child interactions are generally beneficial to children's development (Downer et al., [<reflink idref="bib31" id="ref114">31</reflink>]), children from disadvantaged families are more likely to attend low-quality ECE settings (Zaslow et al., [<reflink idref="bib117" id="ref115">117</reflink>]). High-quality ECE settings are characterized by well-trained teachers, stimulating environments, low teacher–child ratios, child-centered curricula, and robust family engagement (Phillips & Boyd, [<reflink idref="bib84" id="ref116">84</reflink>]). Conversely, low-quality ECE settings typically lack these features, potentially impacting the efficacy of teacher–child interactions and children's vocabulary development (Tilbe & Gai, [<reflink idref="bib102" id="ref117">102</reflink>]). Thus, SES is usually a covariate to reduce the potential selection biases in ECE quality studies. In addition to SES, children's age may also exert a moderating influence on children's vocabulary acquisition. The advancement of children's language development is intricately linked to the maturation of the lateral prefrontal cortex within the brain as they progress in age (Sowell, [<reflink idref="bib97" id="ref118">97</reflink>]). It is worth noting that the development of children's expressive and receptive vocabulary may be influenced in different ways by teacher–child interactions. In contrast to expressive vocabulary, which can be learned in children's daily interactions with teachers, receptive vocabulary is more likely to increase from direct teacher instruction (Burchinal, [<reflink idref="bib15" id="ref119">15</reflink>]; Yang et al., [<reflink idref="bib116" id="ref120">116</reflink>]). The investigated vocabulary skill components may be valuable to the study results in studies that link CLASS to child outcomes.</p> <hd id="AN0185036407-8">Focus of This Study</hd> <p>In this study, we conduct a three-level meta-analysis to explore the relationship between the three CLASS domains (<emph>Emotional Support</emph>, <emph>Classroom Organization</emph>, and <emph>Instructional Support</emph>) and children's vocabulary skills. This approach is particularly advantageous in educational research, allowing for a nuanced examination of effect sizes across multiple studies while accounting for variances within and between studies, as well as among effect sizes reported within the same study (Assink & Wibbelink, [<reflink idref="bib4" id="ref121">4</reflink>]; Van den Noortgate et al., [<reflink idref="bib106" id="ref122">106</reflink>]). In turn, failing to account for the statistical dependence of multiple results from a single study can lead to misleading conclusions (Van den Noortgate et al., [<reflink idref="bib106" id="ref123">106</reflink>]). Compared to the traditional two-level models (e.g., Perlman et al., [<reflink idref="bib75" id="ref124">75</reflink>]), the three-level meta-analysis approach can more accurately handle the complexity and potential dependencies in the data, leading to more reliable and nuanced insights (Assink & Wibbelink, [<reflink idref="bib4" id="ref125">4</reflink>]; Littell et al., [<reflink idref="bib66" id="ref126">66</reflink>]; Van den Noortgate et al., [<reflink idref="bib106" id="ref127">106</reflink>]).</p> <p>Moreover, previous studies have revealed cross-domain or null associations between CLASS three domains and children's vocabulary skills (e.g., Hu et al., [<reflink idref="bib57" id="ref128">57</reflink>]; McDoniel et al., [<reflink idref="bib68" id="ref129">68</reflink>]; Pianta et al., [<reflink idref="bib81" id="ref130">81</reflink>], [<reflink idref="bib82" id="ref131">82</reflink>]; Ulferts et al., [<reflink idref="bib103" id="ref132">103</reflink>]), which is inconsistent with the domain-specific assumptions of the TTI theoretical framework about children's development outcomes. Although Veraksa et al. ([<reflink idref="bib108" id="ref133">108</reflink>]) conducted a qualitative systematic review to evaluate the association between the three CLASS domains and children's vocabulary, the effect size of these correlations is not definite. Furthermore, Perlman and colleagues' ([<reflink idref="bib75" id="ref134">75</reflink>]) traditional two-level meta-analysis showing relationships between the CLASS domains and children's receptive vocabulary was insignificant. However, the number of studies included in this meta-analysis was very sparse. <emph>Classroom Organization</emph> and <emph>Emotional Support</emph> domains only included three studies, and <emph>Instructional Support</emph> domains included five. In addition to ignoring the statistical dependence of multiple outcomes in a single study which can be misleading in traditional two-level meta-analyses model, Guolo and Varin ([<reflink idref="bib44" id="ref135">44</reflink>]) also caution that meta-analyses with less than five studies may risk producing inaccurate results. Also, Perlman et al.'s ([<reflink idref="bib75" id="ref136">75</reflink>]) meta-analysis did not analyze the effects of potential moderators on the relationship between the three domains of CLASS and children's vocabulary. Therefore, a more comprehensive meta-analysis investigation is required to establish the validity of the correlations between three CLASS domains and children's vocabulary within the TTI framework. Our study employed three separate three-level meta-analyses, including a total of 23 studies, to address the following three research questions (RQs):</p> <p></p> <ulist> <item> RQ1: Are three domains of CLASS (i.e., <emph>Emotional Support</emph>, <emph>Classroom Organization</emph>, and <emph>Instructional Support</emph>) related to children's vocabulary skills?</item> <p></p> <item> RQ2: How large are the effect sizes (<emph>r</emph>) to the <emph>Emotional Support</emph>, <emph>Classroom Organization</emph>, and <emph>Instructional Support</emph> linked to children's vocabulary skills?</item> <p></p> <item> RQ3: Do the children's characteristics (i.e., age and family SES), year of publication, and components of the vocabulary of the included studies play a moderating role in the obtained effects?</item> </ulist> <p>By addressing these questions, we hope to identify the aspects of teacher–child interactions most beneficial to children's vocabulary development. This will help educators and policymakers understand effective strategies for practicing the subject matter and ensuring children have the most beneficial educational experiences. Also, investigating the moderating role of children's characteristics (e.g., age and family SES), the year of publication, and vocabulary components may help us understand how these factors influence the effectiveness of the CLASS domains. This information allows for a more nuanced understanding of the most effective conditions in these areas, and it is particularly important to target educational interventions for different groups of children and to adapt strategies to changing educational environments.</p> <hd id="AN0185036407-9">Method</hd> <p></p> <hd id="AN0185036407-10">Literature Search</hd> <p>Initially, a systematic search was conducted from January 2008 to July 2023 across four English databases (i.e., Web of Science, ERIC, PsycARTICLES, and PsycINFO) and Google Scholar. Figure 1 illustrates the literature review process and selection of the articles. The search included multiple keywords related to outcome measures (e.g., language, vocabulary, verbal, academic achievement, child development, cognitive ability, school readiness, and reading), type of education (e.g., kindergarten, preschool, and early childhood education), classroom quality (e.g., classroom assessment scoring system, classroom process quality, classroom environment, preschool classroom quality, teacher–child interaction quality, and CLASS), and target (e.g., association, impact, and effect). The Boolean operator "OR" connected keywords within each category, while "AND" linked different categories. Additionally, a manual search complemented the systematic search, identifying individual articles (e.g., Aikens et al., [<reflink idref="bib1" id="ref137">1</reflink>]; Goble & Pianta, [<reflink idref="bib41" id="ref138">41</reflink>]; West et al., [<reflink idref="bib114" id="ref139">114</reflink>]) from existing meta-analyses and systematic reviews (e.g., Koşkulu-Sancar et al., [<reflink idref="bib61" id="ref140">61</reflink>]; Perlman et al., [<reflink idref="bib75" id="ref141">75</reflink>]). The first author then used the <emph>ASReview</emph> tool (van de Schoot et al., [<reflink idref="bib107" id="ref142">107</reflink>]), a machine-learning-assisted method that screened titles and abstracts based on inclusion criteria. For example, the studies need to investigate the relationship between CLASS domains (<emph>Emotional Support</emph>, <emph>Classroom Organization</emph>, <emph>Instructional Support</emph>) and children's vocabulary skills, measurable outcomes related to children's vocabulary development, and empirical studies employing quantitative methods, including observational and correlational designs. This tool's algorithms, refined based on the reviewer's selections, rank articles from most to least relevant. The effectiveness of the <emph>ASReview</emph> tool in accelerating the article selection process has been validated in previous studies (e.g., Harmsen et al., [<reflink idref="bib47" id="ref143">47</reflink>]; Van den Brand & van de Schoot, [<reflink idref="bib104" id="ref144">104</reflink>]). If an article was identified as fitting the criteria, it was retained, and its full text was read in the next stage. Subsequently, based on title and abstract, 5,259 records were initially excluded, leaving 78 articles for full-text examination. After this stage, 55 full-text articles were further excluded for the following reasons: eight were reviews, 20 lacked adequate measures of teacher–child interactions, 15 had outcomes unrelated to vocabulary skills, and the others had insufficient or unavailable data even after contacting authors. Ultimately, the final sample comprised 23 articles, contributing to 97 effect sizes (Fig. 1).</p> <p>Graph: Fig. 1 Flow diagram of the search strategy and study selection</p> <hd id="AN0185036407-11">Inclusion Criteria and Coding</hd> <p>The inclusion criteria for this meta-analysis were as follows: First, to minimize systematic bias in meta-analyses and enhance transparency and replicability of our search results, we included only articles published in English in this review, as language restrictions in literature searches can reduce bias (Morrison et al., [<reflink idref="bib70" id="ref145">70</reflink>]). Second, the studies had to involve preschool or kindergarten children; clinical samples were excluded. Third, the teacher–child interaction quality must be assessed by CLASS K or pre-K in these articles. Fourth, for measures of children's vocabulary skills, both child one-to-one behavioral assessments and adult-reported assessments were included. Finally, the studies must report sufficient statistical information to compute the effect sizes (<emph>r</emph>) for meta-analysis.</p> <p>According to the Campbell Collaboration ([<reflink idref="bib101" id="ref146">101</reflink>]) guidelines, two independent coders extracted and double-coded all studies that met the inclusion criteria. To assess the inter-rater reliability of the initial scores from the independent coding method, kappa (κ) was used for nominal data variables, and intra-class correlations (ICC) were applied for interval variables. If there was any disagreement between the two coders, a discussion took place to reach an agreement. Finally, the codes had a κ and ICC value of 1. Each study's characteristics were coded by two independent coders according to the following information: (<reflink idref="bib1" id="ref147">1</reflink>) article information (e.g., author, title, and year of publication); (<reflink idref="bib2" id="ref148">2</reflink>) correlation coefficients between three CLASS domains and children's vocabulary. For the original articles reporting only the standardized coefficients (<emph>β</emph>), we converted <emph>β</emph> to<emph> r</emph> using the formula <emph>r</emph> = <emph>β</emph> × 0.98 + 0.05 (<emph>β</emph> ≥ 0); <emph>r</emph> = <emph>β</emph> × 0.98 − 0.05 (<emph>β</emph> < 0) (<emph>β</emph> ∈ (− 0.5, 0.5))(Card, [<reflink idref="bib20" id="ref149">20</reflink>]; Peterson & Brown, [<reflink idref="bib76" id="ref150">76</reflink>]). (<reflink idref="bib3" id="ref151">3</reflink>) sample characteristics and size (e.g., mean age and family SES); (<reflink idref="bib4" id="ref152">4</reflink>) the type of children's outcome measure (e.g., expressive vocabulary or receptive vocabulary); (<reflink idref="bib5" id="ref153">5</reflink>) the type of instruments (e.g., PPVT, OWLS, WJ, and DRDP) (see Table 1).</p> <p>Table 1 Overview of studies, effect sizes, and moderators included in the meta-analysis</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Study</p></th><th align="left"><p>Publishing year</p></th><th align="left"><p>Sample size</p></th><th align="left"><p>Effect size (<italic>r</italic>)</p></th><th align="left"><p>Mean age</p></th><th align="left"><p>Family SES</p></th><th align="left"><p>Components of skills (measure)</p></th></tr></thead><tbody><tr><td align="left"><p>Aikens et al.</p></td><td align="left"><p>2012</p></td><td align="left"><p>1936</p></td><td align="left"><p>CO:0.04; IS: 0.03</p></td><td align="left"><p>5.80</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPVT-IV)</p></td></tr><tr><td align="left"><p>Bulotsky-Shearer et al.</p></td><td align="left"><p>2014</p></td><td align="left"><p>304</p></td><td align="left"><p>ES: -0.07; CO: 0.00; IS: 0.11</p></td><td align="left"><p>3.98</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Receptive vocabulary (WJ-III)</p></td></tr><tr><td align="left"><p>Burchinal et al</p></td><td align="left"><p>2012</p></td><td align="left"><p>301</p></td><td align="left"><p>ES: -0.03;</p></td><td align="left"><p>4.00</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Burchinal et al.</p></td><td align="left"><p>2014</p></td><td align="left"><p>804</p></td><td align="left"><p>ES: -0.02; CO: 0.05; IS: -0.01</p></td><td align="left"><p>5.00</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Carr et al. a1</p></td><td align="left"><p>2019</p></td><td align="left"><p>797</p></td><td align="left"><p>ES: 0.08; CO: 0.08; IS: 0.09</p></td><td align="left"><p>4.56</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Vocabulary (PPVT- III /OWLS)</p></td></tr><tr><td align="left"><p>Carr et al. a2</p></td><td align="left"><p>2019</p></td><td align="left"><p>847</p></td><td align="left"><p>ES: 0.09; CO: 0.1; IS: 0.13</p></td><td align="left"><p>6.04</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Vocabulary (PPVT- III /OWLS)</p></td></tr><tr><td align="left"><p>Curby et al. a1</p></td><td align="left"><p>2013</p></td><td align="left"><p>2127</p></td><td align="left"><p>ES: 0.20</p></td><td align="left"><p>4.62</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Curby et al. a2</p></td><td align="left"><p>2013</p></td><td align="left"><p>2433</p></td><td align="left"><p>ES: 0.20</p></td><td align="left"><p>4.62</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Curby et al. a3</p></td><td align="left"><p>2013</p></td><td align="left"><p>2113</p></td><td align="left"><p>ES: 0.12</p></td><td align="left"><p>4.62</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Expressive vocabulary (OWLS)</p></td></tr><tr><td align="left"><p>Curby et al. a4</p></td><td align="left"><p>2013</p></td><td align="left"><p>2436</p></td><td align="left"><p>ES: 0.14</p></td><td align="left"><p>4.63</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Expressive vocabulary (OWLS)</p></td></tr><tr><td align="left"><p>Dotterer et al.</p></td><td align="left"><p>2012</p></td><td align="left"><p>3584</p></td><td align="left"><p>IS: 0.18</p></td><td align="left"><p>4</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Finders et al.</p></td><td align="left"><p>2021</p></td><td align="left"><p>684</p></td><td align="left"><p>ES: 0.03; CO: 0.11; IS: -0.08</p></td><td align="left"><p>4.80</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Receptive vocabulary (PPVT-IV)</p></td></tr><tr><td align="left"><p>Futterer et al.</p></td><td align="left"><p>2022</p></td><td align="left"><p>301</p></td><td align="left"><p>ES: -0.07</p></td><td align="left"><p>3.98</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Receptive vocabulary (WJ-III)</p></td></tr><tr><td align="left"><p>Goble et al. a1</p></td><td align="left"><p>2017</p></td><td align="left"><p>1407</p></td><td align="left"><p>ES: 0.17; CO: 0.01; IS: 0.18</p></td><td align="left"><p>4.0</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Goble et al. a2</p></td><td align="left"><p>2017</p></td><td align="left"><p>1407</p></td><td align="left"><p>ES: 0.1; CO:- 0.13; IS: 0.06</p></td><td align="left"><p>4.18</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Expressive vocabulary (WJ-III)</p></td></tr><tr><td align="left"><p>Goble et al. a1</p></td><td align="left"><p>2019</p></td><td align="left"><p>1037</p></td><td align="left"><p>ES: 0.07; CO: 0.06; IS: 0.07</p></td><td align="left"><p>4.18</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Goble et al. a2</p></td><td align="left"><p>2019</p></td><td align="left"><p>1007</p></td><td align="left"><p>ES: 0.15; CO: 0.11; IS: 0.12</p></td><td align="left"><p>4.18</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Guerrero-Rosada et al. a1</p></td><td align="left"><p>2021</p></td><td align="left"><p>297</p></td><td align="left"><p>ES: 0.16; CO: 0.13; IS: 0.11</p></td><td align="left"><p>7.14</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPVT-IV)</p></td></tr><tr><td align="left"><p>Guerrero-Rosada et al. a2</p></td><td align="left"><p>2021</p></td><td align="left"><p>292</p></td><td align="left"><p>ES: 0.16; CO: 0.13; IS: 0.06</p></td><td align="left"><p>7.14</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPVT-IV)</p></td></tr><tr><td align="left"><p>Hatfield et al. a1</p></td><td align="left"><p>2016</p></td><td align="left"><p>792</p></td><td align="left"><p>ES: 0.2; CO: 0.14; IS: 0.19</p></td><td align="left"><p>4.61</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Hatfield et al. a2</p></td><td align="left"><p>2016</p></td><td align="left"><p>796</p></td><td align="left"><p>ES: 0.17; CO: 0.1; IS: 0.17</p></td><td align="left"><p>4.61</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Hu et al.</p></td><td align="left"><p>2017</p></td><td align="left"><p>587</p></td><td align="left"><p>ES: 0.44; CO: 0.27; IS: 0.55</p></td><td align="left"><p>5.1</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (C-PPVT-R)</p></td></tr><tr><td align="left"><p>Hu et al. a1</p></td><td align="left"><p>2019</p></td><td align="left"><p>586</p></td><td align="left"><p>ES: 0.4; CO: 0.517; IS: 0.305</p></td><td align="left"><p>6.12</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (C-PPVT-R)</p></td></tr><tr><td align="left"><p>Hu et al. a2</p></td><td align="left"><p>2019</p></td><td align="left"><p>656</p></td><td align="left"><p>ES: 0.39; CO: 0.505; IS: 0.282</p></td><td align="left"><p>6.72</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (C-PPVT-R)</p></td></tr><tr><td align="left"><p>Hu et al. a3</p></td><td align="left"><p>2019</p></td><td align="left"><p>584</p></td><td align="left"><p>ES: 0.484; CO: 0.513; IS: 0.37</p></td><td align="left"><p>7.22</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (C-PPVT-R)</p></td></tr><tr><td align="left"><p>McDoniel et al. a1</p></td><td align="left"><p>2022</p></td><td align="left"><p>2286</p></td><td align="left"><p>ES: -0.07; CO: -0.06; IS: -0.08</p></td><td align="left"><p>4.03</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Vocabulary (DRDP)</p></td></tr><tr><td align="left"><p>McDoniel et al. a2</p></td><td align="left"><p>2022</p></td><td align="left"><p>2286</p></td><td align="left"><p>ES: 0.11; CO: 0.11; IS: 0.10</p></td><td align="left"><p>4.63</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Vocabulary (DRDP)</p></td></tr><tr><td align="left"><p>Niklas et al. a1</p></td><td align="left"><p>2018</p></td><td align="left"><p>185</p></td><td align="left"><p>ES: 0.224; CO: 0.175; IS: 0.149</p></td><td align="left"><p>3.95</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (WJ-III)</p></td></tr><tr><td align="left"><p>Niklas et al. a2</p></td><td align="left"><p>2018</p></td><td align="left"><p>281</p></td><td align="left"><p>ES: 0.118; CO: 0.1; IS: 0.083</p></td><td align="left"><p>4.58</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (WJ-III)</p></td></tr><tr><td align="left"><p>Niklas et al. a3</p></td><td align="left"><p>2018</p></td><td align="left"><p>237</p></td><td align="left"><p>ES: 0.095; CO: 0.077; IS: 0.129</p></td><td align="left"><p>5.58</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (WJ-III)</p></td></tr><tr><td align="left"><p>Sabol et al. a1</p></td><td align="left"><p>2017</p></td><td align="left"><p>195</p></td><td align="left"><p>ES: 0.02; CO: 0.12; IS: 0.129</p></td><td align="left"><p>4.85</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>Sabol et al. a2</p></td><td align="left"><p>2017</p></td><td align="left"><p>195</p></td><td align="left"><p>ES: -0.09; CO: -0.01; IS: 0.129</p></td><td align="left"><p>4.85</p></td><td align="left"><p>Low SES</p></td><td align="left"><p>Expressive vocabulary (WJ-III)</p></td></tr><tr><td align="left"><p>Schmitt et al.</p></td><td align="left"><p>2019</p></td><td align="left"><p>99</p></td><td align="left"><p>ES: -0.16; CO: -0.13; IS: -0.18</p></td><td align="left"><p>4.46</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPVT-IV)</p></td></tr><tr><td align="left"><p>Tilbe et al.</p></td><td align="left"><p>2022</p></td><td align="left"><p>177</p></td><td align="left"><p>ES: 0.14; CO: 0.05; IS: 0.03</p></td><td align="left"><p>5</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPVT-IV)</p></td></tr><tr><td align="left"><p>Weiland et al.</p></td><td align="left"><p>2013</p></td><td align="left"><p>414</p></td><td align="left"><p>ES: -0.05; CO: -0.05; IS: 0.01</p></td><td align="left"><p>4</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPTV-III)</p></td></tr><tr><td align="left"><p>West et al.</p></td><td align="left"><p>2010</p></td><td align="left"><p>643</p></td><td align="left"><p>IS: 0.09</p></td><td align="left"><p>3.6</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (PPVT-IV)</p></td></tr><tr><td align="left"><p>Yang et al. a1</p></td><td align="left"><p>2021</p></td><td align="left"><p>354</p></td><td align="left"><p>ES: 0.48; CO: 0.43; IS: 0.52</p></td><td align="left"><p>4.29</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (C-PPVT-R)</p></td></tr><tr><td align="left"><p>Yang et al. a2</p></td><td align="left"><p>2021</p></td><td align="left"><p>354</p></td><td align="left"><p>ES: 0.43; CO: 0.38; IS: 0.52</p></td><td align="left"><p>5.29</p></td><td align="left"><p>Stratified</p></td><td align="left"><p>Receptive vocabulary (C-PPVT-R)</p></td></tr></tbody></table> </ephtml> </p> <p>Study: a1, a2 denote that multiple independent samples (or studies) were reported in the same article; <emph>ES</emph> = emotional support, <emph>CO</emph> = classroom organization, <emph>IS</emph> = instructional support; <emph>PPVT-III</emph> = peabody picture vocabulary test-III, <emph>PPVT-IV = </emph>peabody picture vocabulary test-IV, <emph>C-PPVT-R</emph> = Chinese version of the peabody picture vocabulary test revised, <emph>OWLS</emph> = oral and written language scale, <emph>DRDP</emph> = desired results developmental profile, <emph>WJ-III =</emph> Woodcock–Johnson–III, <emph>SES =</emph> socioeconomic status</p> <hd id="AN0185036407-12">Statistical Analysis</hd> <p>In this study, the three-level meta-analysis was conducted using R 4.2.3 software (R Core Team, [<reflink idref="bib86" id="ref154">86</reflink>]), along with the <emph>dmetar</emph> (Harrer et al., [<reflink idref="bib49" id="ref155">49</reflink>]), <emph>metafor</emph> (Viechtbauer, [<reflink idref="bib109" id="ref156">109</reflink>]), and <emph>metaviz</emph> (Kossmeier et al., [<reflink idref="bib62" id="ref157">62</reflink>]) packages. We use the correlation coefficient (<emph>r</emph>) between variables as a metric for effect size. According to Cohen et al. ([<reflink idref="bib23" id="ref158">23</reflink>]), the <emph>r</emph> value less than 0.10 indicates a small effect size, approximately 0.30 suggests a moderate effect size, and greater than 0.50 shows a large effect size. However, it is noted that even small effect sizes may still significantly impact children's development, especially in education and psychological research (e.g., Carey et al., [<reflink idref="bib25" id="ref159">25</reflink>]). The effect sizes were calculated based on each study's correlation coefficients and sample sizes.</p> <p>Several articles in our study reported outcomes from repeated measures within the same samples, resulting in multiple interdependent effect sizes (e.g.,Curby et al., [<reflink idref="bib24" id="ref160">24</reflink>]; Hu et al., [<reflink idref="bib55" id="ref161">55</reflink>]). Traditional two-level meta-analyses often overlook the non-independence of variables measured within the same sample of individuals in a single study. Conversely, the three-level model meta-analysis accounted for the variance between the three levels: within effect sizes, within studies, and between studies. Therefore, we used a three-level random-effects model to address the non-independence of the obtained effect sizes. Using a multilevel modeling approach in meta-analysis allows for a comprehensive examination of various variance components and exploring potential moderators and biases within the included studies. This approach considers three key components of variance: each effect size's sampling variance (Level 1), which is estimated based on the sample size, variance across effect sizes of within-study (Level 2), and between-study variance (Level 3) (Assink & Wibbelink, [<reflink idref="bib4" id="ref162">4</reflink>]; Van den Noortgate et al., [<reflink idref="bib105" id="ref163">105</reflink>]). First, we employed an intercept-only random-effects model with restricted maximum-likelihood estimation to estimate the overall effect of <emph>Emotional Support</emph>, <emph>Classroom Organization</emph>, and <emph>Instructional Support</emph> on children's vocabulary separately. Then, one-tailed likelihood ratio tests were used to determine the statistical significance of the variation distributed within studies (level 2) and between studies (level 3). Effect sizes are heterogeneous if either level variance is statistically significant (<emph>p</emph> < 0.05). When significant heterogeneity is detected, moderator analyses are conducted to identify potential factors contributing to this variability. Several moderators are coded and examined to explore biases embedded within the studies. Continuous moderators such as publication year and mean sample age are considered. In contrast, categorical moderators include the vocabulary skills (receptive vocabulary [0], and expressive vocabulary [<reflink idref="bib1" id="ref164">1</reflink>]), and types of family socioeconomic status (low [0] or high [<reflink idref="bib1" id="ref165">1</reflink>]) of the sampled children. For continuous moderators like mean sample age, meta-regression is performed, while subgroup analyses are conducted for categorical moderators to compare different study characteristics.</p> <p>The issue of publication bias, which can affect the validity of meta-analysis, is also investigated. The modified Egger's regression within the multilevel framework (Rodgers & Pustejovsky, [<reflink idref="bib88" id="ref166">88</reflink>]) and the "sunset" funnel plots are employed to examine whether the tendency to publish studies with significant findings leads to overestimating the average effect size. Compared with traditional funnel plots, "sunset" funnel plots provide a better indication of the statistical power and publication bias of the studies included in the meta-analysis (Kossmeier et al., [<reflink idref="bib63" id="ref167">63</reflink>]). Additionally, the <emph>p-curve</emph> analysis was employed to examine its skewness, the right-skewed <emph>p-curve</emph> indicated the evidential value of primary studies selected, in turn, the left-skewed <emph>p-curve</emph> indicates possible bias and presence of <emph>p-hacking</emph> (Simonsohn et al., [<reflink idref="bib95" id="ref168">95</reflink>]). Finally, sensitivity analyses are conducted to assess the presence and impact of influential studies and outliers on the overall pooled effect. These analyses help evaluate the findings' robustness and identify potential studies that may significantly affect the results. By employing a multilevel modeling approach and conducting various analyses, including moderator analyses, investigation of publication bias, and sensitivity analyses, this study provides a comprehensive and rigorous examination of the data, contributing to a deeper understanding of the effect sizes and potential biases in the field under investigation.</p> <hd id="AN0185036407-13">Results</hd> <p>The summary of the studies included within the meta-analysis is in Table 1. We provided the article author, publishing year, sample sizes of each included study, the effect size, children's mean age, family SES, components of vocabulary skills, and the instruments. A total of 97 effect sizes were extracted from the 23 articles published between 2010 and 2022. Effect sizes were between -0.18 and 0.55, showing substantial variance in the results of the included studies. The number of children who took part ranged from 99 to 3584, with an average age of 3.6 to 7.22 years. In total, the meta-analysis included 77,651 participants.</p> <hd id="AN0185036407-14">Effects of Emotional Support on Vocabulary Skills</hd> <p>The overall effect of <emph>Emotional Support</emph> (35 effect sizes, <emph>k</emph> = 20, <emph>N</emph> = 29658) on vocabulary was small to moderate in magnitude (<emph>r</emph> = 0.114, se = 0.041, 95% CI = [0.032, 0.195]; see Fig. 2). The 95% prediction interval showed a 95% probability that a new study's effect would fall between -0.253 and 0.452 (<emph>r</emph>). The likelihood ratio tests showed significant variance for effects within studies (level 2; LRT = 34.753, <emph>p</emph> < 0.001) and between studies (level 3; LRT = 21.885, <emph>p</emph> < 0.001), which explained 7.86% and 88.50% of the variance, respectively. Due to the significant heterogeneity in effect sizes (<emph>I</emph><sups>2</sups> = 96.36%; Higgins et al., [<reflink idref="bib51" id="ref169">51</reflink>]), moderator analyses were conducted to identify potential factors contributing to the variance between studies.</p> <p>Graph: Fig. 2 Forest plot of effect sizes (r) synthesis: Emotional support and vocabulary</p> <hd id="AN0185036407-15">Effects of Classroom Organization on Vocabulary Skills</hd> <p>The overall effect of <emph>Classroom Organization</emph> (30 effect sizes, <emph>k</emph> = 18, <emph>N</emph> = 21883) on vocabulary was small to moderate in magnitude (<emph>r</emph> = 0.110, se = 0.041, 95% CI = [0.027, 0.191]; see Fig. 3). The 95% prediction interval showed a 95% probability that a new study's effect would fall between -0.242 and 0.436 (<emph>r</emph>). The likelihood ratio tests showed significant variance for effects within studies (level 2; LRT = 30.389, <emph>p</emph> < 0.001) and between studies (level 3; LRT = 22.889, <emph>p</emph> < 0.001), which explained 9.22% and 86.12% of the variance, respectively. Due to the significant heterogeneity in effect sizes (<emph>I</emph><sups>2</sups> = 95.34%; Higgins et al., [<reflink idref="bib51" id="ref170">51</reflink>]), moderator analyses were conducted to identify potential factors contributing to the variance between studies.</p> <p>Graph: Fig. 3 Forest plot of effect sizes (r) synthesis: Classroom organization and vocabulary</p> <hd id="AN0185036407-16">Effects of Instructional Support on Vocabulary Skills</hd> <p>The overall effect of <emph>Instructional Support</emph> (32 effect sizes, <emph>k</emph> = 20, <emph>N</emph> = 26040) on vocabulary was small to moderate in magnitude (<emph>r</emph> = 0.127, se = 0.042, 95% CI = [0.042, 0.211]; see Fig. 4). The 95% prediction interval showed a 95% probability that a new study's effect would fall between -0.257 and 0.477 (<emph>r</emph>). The likelihood ratio tests showed significant variance for effects within studies (level 2; LRT = 32.984, <emph>p</emph> < 0.001) and between studies (level 3; LRT = 15.887, <emph>p</emph> < 0.001), which explained 8.59% and 87.9% of the variance, respectively. Due to the significant heterogeneity in effect sizes (<emph>I</emph><sups>2</sups> = 96.49%; Higgins et al., [<reflink idref="bib51" id="ref171">51</reflink>]), moderator analyses were conducted to identify potential factors contributing to the variance between studies.</p> <p>Graph: Fig. 4 Forest plot of effect sizes (r) synthesis: Instructional Support and vocabulary</p> <hd id="AN0185036407-17">Sensitivity Tests</hd> <p>A range of sensitivity tests was employed to investigate the influential studies and outliers influence on overall effects. In <emph>Emotional Support</emph>, the effect with a residual greater than three standard deviations did not exist in any study. However, there are four effects for which the Cook's distance is greater than three times the mean (Bulotsky-Shearer et al., [<reflink idref="bib12" id="ref172">12</reflink>]; Futterer et al., [<reflink idref="bib39" id="ref173">39</reflink>]; Hu et al., [<reflink idref="bib56" id="ref174">56</reflink>]; Schmitt et al., [<reflink idref="bib93" id="ref175">93</reflink>]). After excluding these outliers, the overall effect size of <emph>Emotional Support</emph> on vocabulary increased by 0.014 (<emph>r</emph> = 0.128, se = 0.040, 95% CI = [0.047, 0.207]). Regarding the effects of <emph>Classroom Organization</emph> on vocabulary, no study reported the effect with a residual greater than three standard deviations. There are three effects for which Cook's distance is greater than three times the mean (Hu et al., [<reflink idref="bib56" id="ref176">56</reflink>]; Schmitt et al., [<reflink idref="bib93" id="ref177">93</reflink>]; Weiland et al., [<reflink idref="bib113" id="ref178">113</reflink>]). After excluding these outliers, the overall effect size of <emph>Classroom Organization</emph> on vocabulary increased by 0.011 (<emph>r</emph> = 0.121, se = 0.044, 95% CI = [0.032, 0.209]). In terms of <emph>Instructional Support</emph>, no residuals of effects were found that were more than three standard deviations across studies. The Cook's distance that exceeded three times the mean was observed in three effects (Finders et al., [<reflink idref="bib38" id="ref179">38</reflink>]; Hu et al., [<reflink idref="bib56" id="ref180">56</reflink>]; Schmitt et al., [<reflink idref="bib93" id="ref181">93</reflink>]). After removing these outliers, the overall effect size of <emph>Instructional Support</emph> on vocabulary is nearly constant (<emph>r</emph> = 0.127, se = 0.036, 95% CI = [0.055, 0.198]). These analyses were performed with and without the effect sizes being winsorized. The sensitivity tests indicated that the results of the meta-analysis remained reliable, and we reported the original effect sizes.</p> <hd id="AN0185036407-18">Moderator Analyses</hd> <p>The moderator analyses outcome for three CLASS domains and vocabulary are shown in Table S1-S3. In terms of <emph>Emotional Support</emph>, the components of vocabulary skills moderated the overall effect of <emph>Emotional Support</emph> on vocabulary outcomes (<emph>F</emph> (<reflink idref="bib1" id="ref182">1</reflink>, 29) = 15.852, <emph>p</emph> < 0.001), compared to the effect sizes of studies on expressive vocabulary (<emph>r</emph> = 0.060, 95% CI = [-0.038, 0.156]), receptive vocabulary of studies had larger effect sizes and significant (<emph>r</emph> = 0.127, 95% CI = [0.034, 0.216]). Also, the effect sizes of the low family SES studies were smaller (<emph>r</emph> = 0.015, 95% CI = [-0.118, 0.147]) compared to family SES selected using the stratified sampling approach (<emph>r</emph> = 0.189, 95% CI = [0.083, 0.290]). However, two continuous moderators, mean sample age and year of publication, did not impact the effect size. In terms of <emph>Classroom Organization</emph>, of four proposed moderators, only the components of vocabulary skills moderated the overall effect of <emph>Classroom Organization</emph> on vocabulary outcomes (<emph>F</emph> (<reflink idref="bib1" id="ref183">1</reflink>, 24) = 14.191, <emph>p</emph> < 0.001), the effect size of studies on receptive vocabulary (<emph>r</emph> = 0.125, 95% CI = [0.035, 0.214]) was higher than that of studies on expressive vocabulary (<emph>r</emph> = 0.018, 95% CI = [-0.088, 0.122]). Regarding the <emph>Instructional Support</emph>, of the four proposed moderators, the components of vocabulary skills moderated the overall effect of <emph>Instructional Support</emph> on vocabulary outcomes (<emph>F</emph> (<reflink idref="bib1" id="ref184">1</reflink>, 26) = 6.441, <emph>p</emph> < 0.05), compared to the effect sizes of studies on expressive vocabulary (<emph>r</emph> = 0.057, 95% CI = [-0.058, 0.171]), the receptive vocabulary of studies had larger effect sizes and significant (<emph>r</emph> = 0.141, 95% CI = [0.045, 0.234]).</p> <hd id="AN0185036407-19">Assessment of Publication Bias</hd> <p>We conducted different strategies to examine the effect of publication bias. In terms of <emph>Emotional Support</emph>, Egger's regression test with multilevel extension (Rodgers & Pustejovsky, [<reflink idref="bib88" id="ref185">88</reflink>]) indicated no asymmetry in the funnel plot (<emph>B</emph> = − 0.914, 95%CI = [− 3.026, 1.198], <emph>p</emph> = 0.385). The visual inspection of the sunset funnel plot also suggests no significant asymmetry (Fig. 5). The sunset funnel plot showed that under a real effect of 0.15 (<emph>p</emph> = 0.05), the median power of studies is 94.3%, and the test for excess significance indicated that these studies have a 100% replication (R-index = 100%) (Fig. 5). The <emph>p-curve</emph> was right-skewed, showing that the correlations established from the original research had evidential significance (Fig. 6). In terms of <emph>Classroom Organization</emph>, the multilevel extension of Egger's regression test (Rodgers & Pustejovsky, [<reflink idref="bib88" id="ref186">88</reflink>]) indicated no asymmetry in the funnel plot (<emph>B</emph> = -0.261, 95%CI = [− 2.400, 1.877], <emph>p</emph> = 0.804). The visual inspection of the sunset funnel plot also suggests no significant asymmetry (Figure S1). The sunset funnel plot showed that under a real effect of 0.14 (<emph>p</emph> = 0.05), the median power of studies is 91.9%, and the test for excess significance indicated that these studies have a 100% replication (R-index = 100%) (Figure S1). The <emph>p-curve</emph> was right-skewed, indicating that the correlations established from the original research had evidential significance (Figure S2). In terms of <emph>Instructional Support</emph>, the multilevel extension of Egger's regression test (Rodgers & Pustejovsky, [<reflink idref="bib88" id="ref187">88</reflink>]) indicated no asymmetry in the funnel plot (<emph>B</emph> = -0.635, 95%CI = [− 2.706, 1.437], <emph>p</emph> = 0.536). The visual inspection of the sunset funnel plot also suggests no significant asymmetry (Figure S3). The sunset funnel plot showed that under a real effect of 0.15 (<emph>p</emph> = 0.05), the median power of studies is 95%, and the test for excess significance indicated that these studies have a 100% replication (R-index = 100%) (Figure S3). The <emph>p-curve</emph> was right-skewed, indicating that the correlations established from the original research had evidential significance (Figure S4).</p> <p>Graph: Fig. 5 Sunset plots of publication bias: Emotional support and vocabulary Note: Each dot represents a single effect size and is shown as a function of standard error. Dark shaded areas indicate significance contours at.05 and.01 levels, and discrete color-coded power zones were estimated using a two-tailed test with significance set at. 05</p> <p>Graph: Fig. 6 P-curve of the correlations between measures of Emotional support and vocabulary</p> <p>Although publication bias may not be completely ruled out in any meta-analysis (Fernández-Castilla et al., [<reflink idref="bib36" id="ref188">36</reflink>]), we employed as many multiple approaches as possible to investigate the effects of publication bias (i.e., Egger's test, sunset enhanced funnel plot, and <emph>p-curve</emph> analysis). Briefly, the publication bias analysis results for the three CLASS domains showed that publication bias was unlikely in this meta-analysis.</p> <hd id="AN0185036407-20">Discussion</hd> <p>This meta-analysis investigated the relationship between the domains of CLASS and children's vocabulary skills. We employed the three-level random-effects modeling to comprehensively review and synthesize the existing studies about the connections between three CLASS domains and children's vocabulary skills. In this study, we found that the positive, significant, and small to moderate in magnitude effect sizes relation between <emph>Emotional Support</emph> (<emph>r</emph> = 0.114), <emph>Classroom Organization</emph> (<emph>r</emph> = 0.110), <emph>Instructional Support</emph> (<emph>r</emph> = 0.127), and children's vocabulary skills. These effect sizes were influenced by variations within and between samples (i.e., the components of vocabulary skills and/or family SES). The findings of this research may potentially provide new insights into the factors contributing to differences in related research outcomes as well as provide new implications for assessing the quality of ECE, thus enriching the scholarly discourse and the educational implications.</p> <hd id="AN0185036407-21">The Association Between Three CLASS Domains and Children's Vocabulary Skills</hd> <p>The finding of the meta-analysis was inconsistent with the result of Perlman et al.'s ([<reflink idref="bib75" id="ref189">75</reflink>]) meta-analysis, which showed null associations between <emph>Emotional Support</emph> and <emph>Classroom Organization</emph> and children's vocabulary, except for <emph>Instructional Support</emph>. Our three-level meta-analysis indicated significant but small to moderate effect sizes for cross-domain relationships between the three CLASS domains and children's vocabulary skills. The inconsistent results might be due to methodological differences and the number of included studies. Perlman et al. ([<reflink idref="bib75" id="ref190">75</reflink>]) employed a traditional two-level meta-analysis model and did not consider the non-independence of variables measured within the same sample of individuals in a single study, which may lead to misleading conclusions (Assink & Wibbelink, [<reflink idref="bib4" id="ref191">4</reflink>]). In addition, when the number of studies included in the meta-analysis is less than five, it may lead to imprecise results (Guolo & Varin, [<reflink idref="bib44" id="ref192">44</reflink>]). Also, the demographic composition of our study sample differs from that of Perlman et al. ([<reflink idref="bib75" id="ref193">75</reflink>]), in which all the studies included in the meta-analysis were from the United States, primarily from the same database. Conversely, we included a more diverse range of socio-economic backgrounds, which could influence the relationship between CLASS domains and children's vocabulary skills.</p> <p>The results of our analysis evidence a cross-domain link between the TTI framework and children's vocabulary skills. The teacher's high-quality <emph>Emotional Support</emph> was linked to the children's vocabulary skills, which the children's cognitive resources can explain. Compared to high-quality <emph>Emotional Support</emph> environments, children may pay more demands placed on their attentional network in low-quality <emph>Emotional Support</emph> classrooms (Kaplan & Berman, [<reflink idref="bib59" id="ref194">59</reflink>]). Children need to be attentive to the teacher's emotional state due to unpredictable teacher interactions and are thus less available for academic or social learning (Kaplan & Berman, [<reflink idref="bib59" id="ref195">59</reflink>]). In turn, high-quality <emph>Emotional Support</emph> classrooms may provide a more positive learning environment because children know what to expect, feel safer, and can focus on learning tasks with fewer interruptions (Curby et al., [<reflink idref="bib24" id="ref196">24</reflink>]). Moreover, preschool teachers can be regarded as attachment sources for children, and this relational substrate can promote children's learning in the future (Mitchell-Copeland et al., [<reflink idref="bib69" id="ref197">69</reflink>]; Pianta et al., [<reflink idref="bib79" id="ref198">79</reflink>]; Wood, [<reflink idref="bib115" id="ref199">115</reflink>]). In summary, teachers who provide high-quality <emph>Emotional Support</emph> in the classroom can convey a sense of security to children and support them in exploring the world autonomously (Pianta et al., [<reflink idref="bib80" id="ref200">80</reflink>]), which in turn allows children to focus more on learning tasks, including vocabulary learning.</p> <p>Furthermore, teachers can enhance children's learning experience through positive behavior management and incorporating diverse and engaging learning modalities, thereby optimizing children's learning efficacy and active participation in the learning process (Hu et al., [<reflink idref="bib57" id="ref201">57</reflink>]). Effective organization of classrooms and days at preschools by teachers can foster diverse language development in young children, as skillful classroom management relies on teachers engaging in meaningful communication with their students (Dickinson et al., [<reflink idref="bib28" id="ref202">28</reflink>]). In other words, in highly organized classrooms, preschool teachers employ suitable instructional approaches and design meaningful activities that enhance children's chances to participate in social interaction and foster their language development. It should be pointed out that compared to the other two domains (<emph>Emotional Support</emph>, <emph>r</emph> = 0.114; <emph>Classroom Organization</emph>, <emph>r</emph> = 0.110), <emph>Instructional Support</emph> had a larger overall effect on vocabulary (<emph>r</emph> = 0.127). This result is consistent with the TTI theoretical framework, which suggests that high-quality <emph>Instructional Support</emph> plays a pivotal role in promoting children's vocabulary development (Pianta & Hamre, [<reflink idref="bib78" id="ref203">78</reflink>]). Based on the assumptions of the TTI framework, <emph>Instructional Support</emph> directly targets cognitive and language abilities, often involving activities that require higher-order thinking and language processing (Hamre et al., [<reflink idref="bib45" id="ref204">45</reflink>]). Thus, providing a more immediate impact on these skills compared to <emph>Emotional Support</emph> and <emph>Classroom Organization</emph>. Specifically, activities under <emph>Instructional Support</emph>, such as vocabulary practice and storytelling, require active language engagement. This direct engagement with language processing skills may make <emph>Instructional Support</emph> more effective in promoting children's vocabulary development. Moreover, empirical studies comparing CLASS three domains show that the content of <emph>Instructional Support</emph> is often rich in specific vocabulary and concepts, directly introducing and practicing new words and ideas (Yang et al., [<reflink idref="bib116" id="ref205">116</reflink>]). Therefore, the stronger association of <emph>Instructional Support</emph> with vocabulary skills can be attributed to its direct targeting of language-related activities and cognitive engagement, making it a key domain for enhancing children's vocabulary development.</p> <hd id="AN0185036407-22">The Moderator Between Three CLASS Domains and Children's Vocabulary Skills</hd> <p>This meta-analysis showed that the effect sizes of <emph>Emotional Support</emph>, <emph>Classroom Organization</emph>, and <emph>Instructional Support</emph> with children's receptive vocabulary were significant and larger than their effect sizes with expressive vocabulary. Some possible explanations: First, when teachers provide emotional support and organize the classroom effectively, children may feel more engaged and motivated to participate in language-rich activities, such as reading, discussions, and interactive tasks. This exposure to rich language input can enhance receptive vocabulary growth (Barnes & Dickinson, [<reflink idref="bib5" id="ref206">5</reflink>]). Second, effective <emph>Emotional Support</emph> and <emph>Classroom Organization</emph> can promote meaningful interactions between teachers and students (Hamre et al., [<reflink idref="bib46" id="ref207">46</reflink>]). Interactive discussions, questions, and conversations stimulate children's active listening and cognitive engagement. This heightened engagement can lead to better comprehension and retention of words and their meanings, contributing to receptive vocabulary gains. Finally, in high-quality teacher <emph>Instructional Support</emph> classrooms, teachers provide children with more opportunities to model talk and exposure to more complex vocabulary (Paulick, [<reflink idref="bib73" id="ref208">73</reflink>], [<reflink idref="bib74" id="ref209">74</reflink>]). Teachers with elevated <emph>Instructional Support</emph> scores frequently utilize open-ended queries and prompt, constructive feedback. This approach acts as a catalyst, fostering children's motivation, effort, curiosity, creativity, and learning strategies—all contributing as beneficial factors in the development of preschoolers' receptive vocabulary (Pianta, [<reflink idref="bib77" id="ref210">77</reflink>]).</p> <p>Furthermore, family SES would also impact the correlation between <emph>Emotional Support</emph> and children's vocabulary. The effect sizes of the low family SES studies were smaller compared to the family SES selected using the stratified sampling approach. This suggests that while <emph>Emotional Support</emph> from teachers may benefit children's vocabulary development, its association is stronger in children from a broader range of SES backgrounds. This may be because children from medium/high SES have greater economic and educational resources, richer cognitive stimulation from parents, and enhanced learning and adaptive skills development (Anders et al., [<reflink idref="bib3" id="ref211">3</reflink>]). In turn, children may develop better learning and migratory skills and benefit more from teacher–child interactions. Also, children from disadvantaged families are more likely to attend low-quality ECE settings and receive less <emph>Emotional Support</emph> than children from socio-economically advantaged families. This might result in teacher–child interactions being less associated with vocabulary development for low SES children than for middle/high SES children.</p> <hd id="AN0185036407-23">Potential Factors Influencing the Relationship Between CLASS Domains and Children's Vocabular...</hd> <p>Our meta-analysis indicates the cross-domain relationship between CLASS domains and children's vocabulary skills and aligns with recent findings (e.g., Carr et al., [<reflink idref="bib21" id="ref212">21</reflink>]; Hu et al., [<reflink idref="bib57" id="ref213">57</reflink>]; Goble et al., [<reflink idref="bib42" id="ref214">42</reflink>]). However, several studies have shown no significant correlation between the three CLASS domains and children's language development (e.g., Sabol et al., [<reflink idref="bib90" id="ref215">90</reflink>]; Schmitt et al., [<reflink idref="bib93" id="ref216">93</reflink>]; Tilbe & Gai, [<reflink idref="bib102" id="ref217">102</reflink>]). One possible explanation for these mixed results between CLASS domains and children's outcomes is selection bias. Compared to children in high-SES families, children in low-SES families are less likely to enroll in high-quality classrooms. For example, Tilbe and Gai ([<reflink idref="bib102" id="ref218">102</reflink>]) suggested that no significant relationship between <emph>Emotional Support</emph> and children's vocabulary may be related to the lower preschool environment in Ethiopia. This result aligns with our meta-analysis, which shows that <emph>Emotional Support</emph> is not significantly linked with children's vocabulary in low-SES family children. Also, although our meta-analysis included studies from various cultural contexts and yielded a significant relationship between the CLASS domain and children's vocabulary development, cultural differences between studies cannot be ignored. For example, Yang et al. ([<reflink idref="bib116" id="ref219">116</reflink>]) found that CLASS domains are significantly linked to children's language in China.</p> <p>In contrast, Weiland et al. ([<reflink idref="bib113" id="ref220">113</reflink>]) found that CLASS domains had a null correlation with children's language development in the United States. One possible reason is that Chinese parents generally emphasize children's academic skills before entering school (Kim & Hua, [<reflink idref="bib60" id="ref221">60</reflink>]), which results in children entering school with potentially higher baseline levels. In empirical studies on ECE quality, children's baseline scores are identified as an important confounder of the quality-outcome association. For instance, Hu et al. ([<reflink idref="bib57" id="ref222">57</reflink>]) indicated that CLASS three domains are significantly related to children's vocabulary. However, when controlling for children's baseline scores, the relationship between <emph>Emotional Support</emph> and vocabulary is insignificant. This could be because longitudinal studies, which control for baseline levels, reduce bias. Conversely, cross-sectional studies are likely to have a higher level of bias due to the lack of this control. In summary, these potential factors are essential in explaining the relationship between CLASS and child development.</p> <hd id="AN0185036407-24">Challenges and Opportunities of Teaching Through Interactions Framework</hd> <p>This meta-analysis has uncovered cross-domain associations between the CLASS framework and children's vocabulary skills. However, it also highlights certain challenges inherent in the TTI/CLASS framework, particularly its struggle to capture the nuanced and variable nature of teacher–child interactions in diverse contexts. One key limitation lies in the domain-specific approach of the TTI/CLASS framework. As Dunn ([<reflink idref="bib32" id="ref223">32</reflink>]) notes, although the domain-specific approach offers conceptual clarity, it does not adequately address the real-world overlap among domains regarding inputs and outcomes. The framework also faces significant challenges, such as limited effect sizes and high correlations between the three CLASS domains. Moreover, the fit indices for the three-factor CLASS model are less than ideal. These small effect sizes might hinder the broader applicability of CLASS, and the high correlation among domains can obscure the clear examination of how different interaction domains relate to specific child development areas. In summary, these limitations and challenges show the need for a more nuanced understanding and application of the CLASS/TTI framework in educational research.</p> <p>First, the bifactor modeling approach is suggested to explore the relationship between specific domains within the TTI framework and child development. Hamre et al. ([<reflink idref="bib46" id="ref224">46</reflink>]) employed a bifactor approach to reconceptualize the TTI framework and evaluate a model for examining domain-general and domain-specific relationships between teacher–child interactions and children's development. The bifactor model distinguishes between domain-general (responsive teaching) and domain-specific factors (positive management, routines, cognitive facilitation), offering a more nuanced understanding of the impact of teacher–child interactions on child development. Compared with the typical three-factor model, the bifactor mode effectively reduces multicollinearity in teacher–child interactions, enhancing predictions of children's outcomes. However, it is noted that the bifactor model did not fit as well as the three-factor model in some studies, including in different cultural contexts (Bihler et al., [<reflink idref="bib6" id="ref225">6</reflink>]).</p> <p>Second, conducting <emph>post-hoc</emph> analyses is crucial to adapting the CLASS framework to specific cultural contexts and educational practices, ensuring validity. For example, Bihler et al. ([<reflink idref="bib6" id="ref226">6</reflink>]) noted that compared to teachers in the United States, displays of enthusiasm by teachers are rarer in the German context. They achieved a satisfactory model fit for the TTI framework with a <emph>post-hoc</emph> analysis of the three-factor model, which included the addition of two correlated residuals and cross-loading the language modeling dimension on <emph>Emotional Support</emph>.</p> <p>Third, a broader range of moderators should be included to capture the nuances of the relationship between teacher–child interactions and children's outcomes within the TTI framework. Previous findings of inconsistency between CLASS and child outcomes suggest that potential moderating variables may not have been considered. For instance, this meta-analysis indicated that the effect size of <emph>Emotional Support</emph> on children's vocabulary development was significant in the stratified sample but not among children from low SES backgrounds. Therefore, future research should explore more diverse and stable moderating variables, such as a child's learning motivation, self-perception of abilities, family upbringing practices, and structural quality of preschools. For instance, children who exhibit a learning goal orientation might derive greater benefits from teacher–child interactions than those with a performance goal orientation, as they tend to be more motivated to learn, engaged, and focused on acquiring knowledge rather than merely performing temporarily (Bjørnebekk et al., [<reflink idref="bib7" id="ref227">7</reflink>]). Also, it is noted that, with the advent of the information age, the role of technology and digital media cannot be overlooked, as their integration into the TTI framework may provide insights into how these elements affect teacher–child interactions (Plowman & McPake, [<reflink idref="bib83" id="ref228">83</reflink>]). In summary, these factors also might have varying impacts across different cultural contexts and provide a more comprehensive understanding of the underlying mechanisms that drive the relationship between teacher–child interactions and child outcomes. Exploring moderators between CLASS and children's outcomes can reveal the most effective interaction conditions, assisting kindergarten practitioners and guiding the development of more targeted preschool education policies.</p> <p>Fourth, conducting prospective longitudinal research designs to test and validate an expanded TTI framework. Prospective longitudinal studies can provide a more comprehensive understanding of the causal relationship between the CLASS domains and children's academic and cognitive growth. Prospective longitudinal research can also reveal potential nonlinear relationships between the quality of early childhood education and child outcomes (e.g., Burchinal et al., [<reflink idref="bib13" id="ref229">13</reflink>]). For example, employing piecewise growth curve modeling (PGCM) to capture multi-stage developmental patterns and the comprehensive understanding of growth trajectories and the influence of TTI quality across various developmental periods (e.g., Hu et al., [<reflink idref="bib55" id="ref230">55</reflink>]). In summary, we expect to adopt bifactor modeling, <emph>post-hoc</emph> analyses, diversified moderating factors, and prospective longitudinal research to future studies to refine and expand the TTI theoretical framework and enhance our understanding of teacher–child interactions and their impact on child development.</p> <hd id="AN0185036407-25">Limitations</hd> <p>Several limitations present in this meta-analysis. First, the results of our analysis are confined to CLASS research. Therefore, it is essential to note that these findings cannot be generalized to other measures of outcomes. Second, in our moderated analyses of <emph>Emotional Support</emph> aspects, the family SES explained between-study variation significantly. However, the types of SES measures differed across studies. As Rutkowski and Rutkowski ([<reflink idref="bib89" id="ref231">89</reflink>]) emphasized, the comparability, or rather, the measurement invariance, of seemingly "simple" SES indicators, such as the number of household book holdings, may not hold across disparate national, cultural, and student subgroup contexts. This lack of comparability or measurement invariance of SES measurements requires more caution in interpreting the results of our moderated analyses. Third, this meta-analysis emphasized children's vocabulary skills as a representative domain-specific skill. This study did not address the importance of early domain-general skills, such as self-regulation, for children's learning and development. To fully comprehend the impact of teacher–child interactions, it would be beneficial for a future review of research to consider other early areas of the child's development.</p> <p>Also, the limited quantity of incorporated studies and the high heterogeneity in the meta-analysis results may also restrict the applicability of the research findings. Moderate to high heterogeneity is commonly observed in meta-analyses of educational research (e.g., Emslander & Scherer, [<reflink idref="bib35" id="ref232">35</reflink>]) because of the variations in the study design, sample characteristics, measurement methods, culture, and context of the samples from the included studies (Imrey, [<reflink idref="bib58" id="ref233">58</reflink>]). For example, differences in sample characteristics such as age, gender, educational background, and geographic location can impact study results.</p> <p>Additionally, cultural and environmental contexts play a crucial role, as they can lead to different responses to educational or psychological interventions (Imrey, [<reflink idref="bib58" id="ref234">58</reflink>]). Although we used a three-level random effects model and moderated analyses to reduce heterogeneity's influence on the results' reliability, readers are advised to exercise caution when extrapolating the outcomes to a broader populace or alternative sociocultural environments.</p> <p>Furthermore, although restricting literature searches to English may reduce the likelihood of systematic bias in meta-analyses (Morrison et al., [<reflink idref="bib70" id="ref235">70</reflink>]), this approach potentially introduces language bias and affects the generalizability of our findings regarding CLASS domains and children's vocabulary skills. While English-language publications dominate much of the scientific literature, important research contributions from non-English sources could provide additional insights or differing perspectives. Future research should include a broader range of language sources to mitigate this.</p> <p>Moreover, the three-level meta-analysis using the REML (Restricted Maximum Likelihood) method in multilevel meta-analytic models with a smaller number of studies can lead to underestimated standard errors. This increases the risk of type I errors when testing overall effect sizes and moderator effects (Assink & Wibbelink, [<reflink idref="bib4" id="ref236">4</reflink>]). Finally, rather than considering the composite score of the CLASS as a factor to investigate its correlation with children's vocabulary skills, this study concentrated on analyzing the three sub-domains of the CLASS.</p> <hd id="AN0185036407-26">Recommendations</hd> <p>This study employed a three-level meta-analysis method to synthesize 23 studies from 2010 to 2022, investigating the relationship between CLASS domains and preschool children's vocabulary skills. The meta-analysis results showed that the overall effect of <emph>Emotional Support</emph>, <emph>Classroom Organization</emph>, and <emph>Instructional Support</emph> on vocabulary skills was small to moderate in magnitude. Among them, the association between <emph>Instructional Support</emph> and vocabulary skills was the strongest. Additionally, the association between <emph>Emotional Support</emph> and vocabulary skills was moderated by SES and the components of vocabulary skills. While <emph>Classroom Organization</emph> and <emph>Instructional Support</emph> were only moderated by the components of vocabulary skills. The results of this study suggest that while the relationship between teachers' <emph>Instructional Support</emph> and children's vocabulary development has a larger overall effect on vocabulary compared to teachers' <emph>Emotional Support</emph> and <emph>Classroom Organization</emph>, it may also be important to focus on teachers' <emph>Emotional Support</emph> and <emph>Classroom Organization</emph>. Young children require scaffolded interactions with wealthy, extended communication to acquire the language that builds the foundation for academic achievement, but they also need sensitive, warm interactions with teachers and effective <emph>Classroom Organization</emph> to thrive (Burchinal, [<reflink idref="bib14" id="ref237">14</reflink>]). The teacher needs to employ instructional strategies like open-ended questioning and providing constructive feedback may foster children's vocabulary usage and understanding. Language-rich classroom activities, including storytelling, shared reading, and interactive word-based games, are critical to increasing children's receptive vocabulary (Barnes & Dickinson, [<reflink idref="bib5" id="ref238">5</reflink>]). Additionally, positive <emph>Emotional Support</emph> and effective <emph>Classroom Organization</emph> can foster a sense of engagement and motivation among children and create a conducive atmosphere for language learning. In terms of family SES, children in lower SES families may require additional support and resources to bridge the gap in cognitive stimulation experienced outside the school environment. For example, providing children with books and educational toys that promote language and cognitive development.</p> <hd id="AN0185036407-27">Acknowledgements</hd> <p>The study and the preparation of the manuscript were supported by the following grant: "An Empirical Study of the Relationship between the Quality of Teacher-child Interaction and the Development of Children's Language Competence in a Rural Area of Sichuan Province (A Project Supported by Center for Rural Childhood Education Research; Project number: NYJ20230604)". The authors of this paper deeply appreciate the support.</p> <hd id="AN0185036407-28">Supplementary Information</hd> <p>Below is the link to the electronic supplementary material.</p> <p>Graph: Supplementary file1 (DOCX 307 KB)</p> <hd id="AN0185036407-29">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0185036407-30"> <title> References </title> <blist> <bibl id="bib1" idref="ref137" type="bt">1</bibl> <bibtext> Aikens, N, Tarullo, L, Hulsey, L, Ross, C, West, J, & Xue, Y. (2010). A year in Head Start: Children, families and programs. (ACF-OPRE Report). U.S. Department of Health and Human Services, Administration for Children and Families, Office of Planning, Research and Evaluation.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref102" type="bt">2</bibl> <bibtext> Ainsworth MDS, Blehar MC, Waters E, Wall S. 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Header DbId: eric
DbLabel: ERIC
An: EJ1470663
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Challenges and Opportunities in Teaching through Interactions Framework: A Three-Level Meta-Analysis of the CLASS Measure and Children's Vocabulary Skills
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Hongbin+Xie%22">Hongbin Xie</searchLink><br /><searchLink fieldCode="AR" term="%22Hongliu+Ouyang%22">Hongliu Ouyang</searchLink><br /><searchLink fieldCode="AR" term="%22Nik+Rosila+Nik+Yaacob%22">Nik Rosila Nik Yaacob</searchLink><br /><searchLink fieldCode="AR" term="%22Daimin+Feng%22">Daimin Feng</searchLink><br /><searchLink fieldCode="AR" term="%22Shuang+Wang%22">Shuang Wang</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Early+Childhood+Education+Journal%22"><i>Early Childhood Education Journal</i></searchLink>. 2025 53(5):1605-1625.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 21
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2025
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Information Analyses
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Early+Childhood+Education%22">Early Childhood Education</searchLink><br /><searchLink fieldCode="EL" term="%22Preschool+Education%22">Preschool Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Vocabulary+Development%22">Vocabulary Development</searchLink><br /><searchLink fieldCode="DE" term="%22Preschool+Children%22">Preschool Children</searchLink><br /><searchLink fieldCode="DE" term="%22Socioeconomic+Status%22">Socioeconomic Status</searchLink><br /><searchLink fieldCode="DE" term="%22Meta+Analysis%22">Meta Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Databases%22">Databases</searchLink><br /><searchLink fieldCode="DE" term="%22Classroom+Environment%22">Classroom Environment</searchLink><br /><searchLink fieldCode="DE" term="%22Preschool+Teachers%22">Preschool Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Student+Relationship%22">Teacher Student Relationship</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Age+Differences%22">Age Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Reports%22">Research Reports</searchLink><br /><searchLink fieldCode="DE" term="%22Classroom+Techniques%22">Classroom Techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Family+Characteristics%22">Family Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Early+Childhood+Education%22">Early Childhood Education</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Quality%22">Educational Quality</searchLink>
– Name: SubjectThesaurus
  Label: Assessment and Survey Identifiers
  Group: Su
  Data: <searchLink fieldCode="SU" term="%22Classroom+Assessment+Scoring+System%22">Classroom Assessment Scoring System</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s10643-024-01703-y
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1082-3301<br />1573-1707
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In Early Childhood Education and Care (ECEC) programs, the quality of teacher-child interactions is regarded to be important for children's vocabulary development. However, prior studies on the relationships between teacher and child, as measured by the Classroom Assessment Scoring System (CLASS), and children's vocabulary skills are inconsistent. In this study, we conducted a three-level meta-analysis to investigate the correlation between three CLASS domains and preschool children's vocabulary skills and then explored the moderating effects of vocabulary components, family SES, publication year, and sample mean age. Relevant literature was searched using four databases (Web of Science, PsycINFO, PsycARTICLES, ERIC) and Google Scholar, leading to the identification of 23 articles published between 2010 and 2022 meeting the inclusion criteria. The findings indicated that the overall effect of the associations between "Emotional Support," "Classroom Organization," "Instructional Support," and vocabulary skills was small to moderate in magnitude. Sensitivity and meta-bias analyses generally supported the robustness of the pooled effect of the association between three CLASS domains and children's vocabulary skills. Also, the association between "Emotional Support" and vocabulary skills was moderated by SES, and the components of vocabulary skills, while "Classroom Organization" and "Instructional Support" were only moderated by the components of vocabulary skills. Implications for future research on assessing the quality of early childhood education are discussed.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2025
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1470663
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1470663
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10643-024-01703-y
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 21
        StartPage: 1605
    Subjects:
      – SubjectFull: Vocabulary Development
        Type: general
      – SubjectFull: Preschool Children
        Type: general
      – SubjectFull: Socioeconomic Status
        Type: general
      – SubjectFull: Meta Analysis
        Type: general
      – SubjectFull: Databases
        Type: general
      – SubjectFull: Classroom Environment
        Type: general
      – SubjectFull: Preschool Teachers
        Type: general
      – SubjectFull: Teacher Student Relationship
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Age Differences
        Type: general
      – SubjectFull: Research Reports
        Type: general
      – SubjectFull: Classroom Techniques
        Type: general
      – SubjectFull: Teaching Methods
        Type: general
      – SubjectFull: Family Characteristics
        Type: general
      – SubjectFull: Early Childhood Education
        Type: general
      – SubjectFull: Educational Quality
        Type: general
      – SubjectFull: Classroom Assessment Scoring System
        Type: general
    Titles:
      – TitleFull: Challenges and Opportunities in Teaching through Interactions Framework: A Three-Level Meta-Analysis of the CLASS Measure and Children's Vocabulary Skills
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Hongbin Xie
      – PersonEntity:
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            NameFull: Hongliu Ouyang
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            NameFull: Nik Rosila Nik Yaacob
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            NameFull: Daimin Feng
      – PersonEntity:
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            NameFull: Shuang Wang
    IsPartOfRelationships:
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          Dates:
            – D: 01
              M: 06
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 1082-3301
            – Type: issn-electronic
              Value: 1573-1707
          Numbering:
            – Type: volume
              Value: 53
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: Early Childhood Education Journal
              Type: main
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