Tag: Behavior

Updated Meta-Analysis Shows Consistent Benefits of Classroom Management Interventions

By Xue Wang, School of Education, Johns Hopkins University

A comprehensive update to a 2016 meta-analysis examined classroom management interventions in elementary education, adding 22 new studies (2014-2022) to the original 54 studies, for a total of 76 controlled trials spanning 20 years. The research team analyzed interventions implemented by teachers for whole classrooms, coding each intervention regarding teacher behavior, teacher-student relationships, student behavior, and social-emotional development.

The updated analysis found a small but significant average effect size (ES = +0.23), consistent with the original meta-analysis findings. This effect held steady across academic, behavioral, social-emotional, and motivational outcomes, suggesting classroom management interventions have broad rather than targeted benefits.

A notable shift emerged in intervention focus over time. Programs published between 2014 and 2022 were significantly more likely to emphasize teacher-student relationships (36% vs. 4% in earlier studies), reflecting evolving approaches to classroom management that prioritize relationship-building over compliance-based strategies.

Among specific programs evaluated in multiple studies, the analysis compared the Good Behavior Game (8 studies), PATHS (14 studies), and Incredible Years (9 studies). The newer version of Incredible Years, which uniquely addressed all four coded intervention categories, showed somewhat lower effectiveness than more focused programs, tentatively suggesting that overly broad interventions may be less effective than targeted approaches.

Shorter interventions (fewer than 13 weeks) proved more effective than longer programs, possibly due to sustained engagement challenges over time. The interventions showed equal effectiveness across socioeconomic groups, confirming that all students can benefit from improved classroom management.

A web tool to interpret the impact of programs on student social and behavioral outcomes

By Marta Pellegrini, University of Cagliari, Italy

A recent study described the use of an online application to show the results of a meta-analysis of psychological and educational programs in K–12 on student social and behavioral outcomes. The researchers highlighted the huge variability of the effects based on filtering the types of programs, contexts, and students, and proposed a way to better interpret the meta-analysis results and make use of them in future research.

Data come from a meta-analysis of 323 experiments conducted in the U.S. in K–12 on student antisocial behaviors, self-regulation, social and interpersonal adjustment, and personal adjustment. Several characteristics were extracted to describe the study setting, such as the region of study, the type of program, its duration, grade level, ethnicity, and socio-economic status–all characteristics that may play a role in explaining the variability of the program effect.

ES Contextualizer (https://ebcontextualizer.shinyapps.io/EmpBench/) is a web tool that makes it possible for users to select characteristics of a context to produce targeted estimates of the impact of programs on student outcomes. ES Contextualizer can be used by researchers to plan a new study or to facilitate effect size interpretation.The authors described several examples of how to use the web tool. In one of them, a researcher conducted an experiment on the effects of an intervention on middle school students’ social problem-solving skills based on teacher reports and obtained an average effect size of +0.15. Using ES Contextualizer, this estimate can be compared to similar interventions conducted in similar contexts and grade levels. If the effect size is compared to the correct benchmark of +0.05 for middle school students from the ES Contextualizer tool, the researchers can conclude that what they found is a meaningful impact. If the grade level is not selected, the tool shows a benchmark of +0.26 instead, possibly leading the researcher to draw a different conclusion.

The authors recommended using the web tool’s filters to generate more nuanced effect size interpretations and more accurate estimates for use in power analysis.

The ABCs of student engagement: What research reveals about its dimensions and impact

By Carmen Pannone, University of Cagliari, Italy

Student engagement remains a key factor in educational psychology, closely linked to both academic achievement and subjective well-being (SWB). A recent systematic review and meta-analysis by Wong and colleagues examined how existing studies have defined and measured three types of engagement: affective (or emotional), behavioral, and cognitive engagement, referred to as the ABC approach, and assessed their association with academic achievement and subjective well-being (SWB). The review included 137 correlational studies involving K–12 students and refined the classification of engagement subtypes. Affective engagement was further broken down into relational, school-related, and learning-related categories. Behavioral engagement included participatory and effortful components, while cognitive engagement was classified as motivational and self-regulatory.

A random-effects meta-regression model with robust variance estimation (RVE) and a small sample adjustment synthesized 533 effect sizes from 110 studies on the correlation between student engagement and academic achievement, and 158 effect sizes from 18 studies on the correlation between student engagement and SWB.

The meta-analyses found that student engagement had a moderate-to-large average correlation with academic achievement (ES = +0.33) and SWB (ES = +0.35). Academic achievement was most strongly associated with behavioral engagement (ES = +0.39), followed by cognitive (ES = +0.31) and affective (ES = +0.26) engagement. SWB showed the strongest link with affective engagement (ES = +0.40), followed by cognitive (ES = +0.35) and behavioral (ES = +0.31) engagement. Notably, the seven engagement subtypes moderated the associations with academic achievement and SWB, meaning the effect varied depending on how engagement was operationalized. Multivariate moderation analysis (possible only for academic achievement) showed stronger links with academic achievement in general subjects (ES = +0.36) than in math and science (ES = +0.30) or language and humanities (ES = +0.25). Teacher-reported engagement was more strongly associated with achievement than student-reported engagement (ES = +0.48 vs. +0.29). Engagement also correlated more strongly with grades (ES = +0.38 and +0.33) than with standardized test scores (ES = +0.22) and had a stronger association when achievement was measured in the same academic year (ES = +0.34) rather than a different one (ES = +0.29).

These findings underscore the importance of considering how engagement is defined and measured when evaluating its effects on student outcomes, highlighting the need for more nuanced research and consistent operationalization in future studies.

The effects of meta-cognition interventions on learning outcomes

By Liu Ziyu; Institute of Curriculum and Pedagogy, Faculty of Education, Beijing Normal University, China

Developing organized habits of communication and behavior is a key milestone for children and adolescents. Meta-cognitive skills such as planning, self-reflection, and behavioral adjustment are closely linked to academic success. Fortunately, targeted interventions have been shown to enhance these skills while also improving students’ motivation, learning strategies, and educational outcomes.

A systematic review evaluated 349 effect sizes from 67 meta-cognitive intervention studies conducted between 2000 and 2024. These studies examined interventions for preschool and elementary school children across subjects such as language, mathematics, science, and social studies. While research included a range of age groups, most studies focused on upper elementary students and were conducted in real classroom settings, primarily in Europe and North America.

Findings showed that meta-cognitive interventions had a positive impact on self-regulated learning and academic achievement, with an overall effect size of g = +0.48. The strongest improvements were in meta-cognitive skills, learning strategies, and executive functions. However, the interventions did not significantly impact self-efficacy or motivation orientation. Researchers suggest that as children develop better self-awareness, they may temporarily lose confidence as they reassess their abilities, which could explain the lack of measurable gains in motivation.

For kindergarten and elementary school teachers, a particularly noteworthy takeaway is that meta-cognitive interventions can be seamlessly integrated into regular academic tasks. Strategies such as modeling, prompting, and providing constructive feedback help students improve their thinking and problem-solving skills without requiring separate lessons. By using these techniques flexibly, teachers can support students’ long-term academic success and overall development.