Category: K-12 Education

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K-12 Education Social and Motivational Outcomes

The Gap Between Teachers’ Self-Efficacy, Management Strategies, and Actual Classroom Management Behaviors

Shi and colleagues combined questionnaire survey methods with AI-supported classroom behavior analysis to examine the relationships among teachers’ classroom management self-efficacy, self-reported classroom management strategies, and actual classroom management behaviors observed by AI. The study involved 345 Chinese K-12 in-service teachers, collected questionnaire data on their classroom management self-efficacy and strategies, and analyzed 673 valid classroom video recordings, totaling 461.74 hours. The research team developed an AI-supported multimodal classroom management behavior analysis tool that automatically identified teachers’ praise statements, criticism statements, discipline-related statements, positive tone of voice, proportion of proximity to students, and proportion of visual attention to students through text, audio, and image data. This allowed the researchers to test whether teachers’ beliefs, reported strategies, and actual behaviors were consistent.

The results showed that teachers with higher classroom management self-efficacy reported using all types of classroom management strategies more frequently, and these differences were all statistically significant. For example, in praise strategies, the high self-efficacy group had a mean rank of 214.43, significantly higher than the low self-efficacy group’s 128.84 (Z = –8.74, p < .001). In corrective feedback strategies, the high group had a mean rank of 206.27, compared with 137.54 in the low group (Z = –6.67, p < .001). In preventive management strategies, the high group had a mean rank of 221.84, whereas the low group had 120.95 (Z = –9.81, p < .001). In commands/transition strategies, the high group had a mean rank of 220.69, compared with 122.17 in the low group (Z = –9.68, p < .001). However, when actual classroom videos were analyzed through AI, no significant differences emerged between the high and low self-efficacy groups on most observable classroom management behaviors. The only finding was a marginal tendency for teachers with lower self-efficacy to use more discipline-related statements (p = .07), suggesting that they may rely more on disciplinary language to maintain order.

Regarding the relationship between self-reported strategies and AI-observed behaviors, the results showed that consistency existed only in some domains. Teachers’ self-reported praise strategies were significantly positively related to AI-detected praise statements and positive tone of voice, although the effect sizes were relatively small. In contrast, corrective feedback and preventive management strategies were not significantly associated with their corresponding AI-based behavioral indicators. Notably, self-reported commands/transition strategies were significantly negatively related to AI-observed discipline-related statements, meaning that the more often teachers reported using clear instructions and transition management, the less frequently discipline-related statements appeared in their classrooms. Overall, teachers’ reported use of strategies only partially corresponded to their actual classroom behaviors, and more concrete and observable strategies, such as praise, were more likely to be validated by AI observation.

Overall, this study suggests that teachers’ beliefs, strategies, and behaviors in classroom management are not always highly aligned. Although teachers with higher self-efficacy reported using more effective strategies, they did not necessarily demonstrate clearly different classroom management behaviors in practice. Only specific and easily identifiable strategies, such as praise, were more readily confirmed through AI observation. The study therefore highlights a misalignment between teachers’ beliefs and their actual teaching behaviors, while also demonstrating the considerable potential of AI for large-scale, non-intrusive, and evidence-based research on classroom management. For educational research and teacher development, the study serves as a reminder that relying solely on teachers’ self-report questionnaires may overestimate the consistency between reported strategies and real classroom behavior. Future work should combine self-report data with more objective methods such as AI observation to gain a fuller understanding of actual classroom management practices.

Source (Open Access): Shi, Y., Wang, Z., Chen, Z., Ren, D., Liu, H., & Zhang, J. (2026). Do teachers … Read the rest

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Effective Teaching Approach K-12 Education

The effect of AI-driven intelligent tutoring systems on K-12 students’ learning and performance: A systematic review

A recent systematic review published in npj Science of Learning examines the effects of intelligent tutoring systems (ITSs) on students’ learning and performance in K-12 education. As artificial intelligence in education (AIEd) has expanded rapidly, ITSs have emerged as a key application with the potential to personalize learning and improve educational outcomes. However, despite their growing adoption, their actual educational value remains uncertain. While some studies suggest that ITSs can enhance learning outcomes and even outperform traditional instruction, others report limited or inconsistent effects. In addition, existing research often conflates different educational contexts or focuses on broader AI applications, leaving a lack of systematic understanding of ITS effectiveness specifically in K-12 settings. This study therefore aims to assess the effects of ITSs on K-12 students’ learning and performance and to examine the experimental designs used to evaluate these systems.

The authors conducted a systematic review of 28 empirical studies involving a total of 4,597 students. Most studies adopted quasi-experimental designs, typically comparing an ITS-based intervention group with control conditions such as traditional teacher-led instruction, non-intelligent tutoring systems, modified ITSs, or no control group. The studies covered a range of countries, subjects, and school levels, with a strong concentration in middle and high school STEM education. Intervention durations varied considerably, from a single class session to several weeks or months. The review categorized studies based on educational context, experimental design, and intervention characteristics to enable a structured comparison of findings.

The review finds that ITSs generally have a positive effect on students’ learning and performance in K-12 education, particularly when compared to traditional teacher-led instruction, where most studies report medium to large effects. However, when compared with non-intelligent tutoring systems, the results are more mixed, with several studies finding no significant differences. Substantial heterogeneity is observed across studies due to differences in design, duration, and context. Importantly, the effectiveness of ITSs depends on key features such as personalization, adaptivity, and real-time feedback, as well as on implementation conditions. ITSs that are integrated with teacher support, encourage self-regulated learning, and are used over longer periods tend to produce better outcomes. In contrast, short interventions may be influenced by novelty effects, and learner characteristics such as prior knowledge and educational level also shape outcomes.

Taken together, the findings suggest that ITSs can enhance learning and performance in K-12 education, but their effectiveness is contingent upon pedagogical design and implementation conditions rather than technology alone. ITSs are most effective when aligned with sound instructional principles and used in combination with teacher guidance. The study also highlights limitations in the existing literature, including short intervention durations, limited sample diversity, and a lack of attention to ethical considerations. It calls for future research with more robust experimental designs, longer interventions, and greater attention to ethical issues, particularly as AI technologies continue to evolve and play an increasing role in education.

Source (Open Access): Létourneau, A., Deslandes Martineau, M., Charland, P., Karran, J. A., Boasen, J., & Léger, P. M. (2025). A systematic review of AI-driven intelligent tutoring systems (ITS) in K-12 education. npj Science of Learning, 10(1), 29.

https://doi.org/10.1038/s41539-025-00320-7… Read the rest

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Achievement K-12 Education Maths and Science Learning

The Impact of Mathematics and Science Professional Development on Teacher Knowledge, Instruction, and Student Achievement

A recent meta-analysis by Lynch and colleagues examined the effectiveness of professional development (Professional Development) interventions for mathematics and science teachers in grades PK-12. Analyzing 200 effect sizes for teacher outcomes and 126 effect sizes for student achievement from 46 experimental studies published from 2001 to 2024, the authors investigated how PD programs affect teachers’ knowledge and classroom instruction, and whether these changes translate into improved student learning.

The authors employed Hedges’s g as the effect size metric, using randomized controlled trial designs to ensure causal inference. PD interventions were categorized by their focus areas: improving teacher knowledge (content knowledge and pedagogical content knowledge), content-specific and content-general instructional strategies, and content-specific formative assessment. The researchers also examined contextual factors such as intervention duration, inclusion of curriculum materials, and school demographics.

The results revealed a significant positive impact of PD on teacher outcomes (pooled average: +0.52 SD). Specifically, teacher knowledge improved by +0.52 SD and classroom instruction by +0.49 SD. Importantly, programs with larger impacts on teacher outcomes also demonstrated significantly larger effects on student achievement. A 1 SD improvement in teacher-level outcomes was associated with a +0.18 SD gain in student achievement. Notably, improvements in classroom instruction showed a stronger link to student learning (+0.24 SD) than knowledge gains (+0.08 SD, not statistically significant). PD programs explicitly focusing on teacher knowledge development (effect size difference: +0.18 SD) and content-specific formative assessment (+0.27 SD) showed significantly stronger impacts on classroom instruction. Interestingly, intervention duration and the inclusion of curriculum materials did not significantly moderate outcomes.

The findings underscore that the quality and specific focus of professional development matter more than duration. Schools should prioritize PD programs that explicitly target both teacher knowledge and instructional practices, particularly emphasizing formative assessment strategies. The strong link between improved instruction and student achievement validates investments in high-quality professional development as a lever for enhancing educational outcomes in mathematics and science.

Source (Open Access): Lynch, K., Gonzalez, K., Hill, H., & Merritt, R. (2025). A meta-analysis of the experimental evidence linking mathematics and science professional development interventions to teacher knowledge, classroom instruction, and student achievement. AERA Open, 11, 23328584251335302.https://doi.org/10.1177/23328584251335302… Read the rest

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K-12 Education Programme Evaluation

Gender Disparity in Computational Thinking Pedagogy and Assessment: A Three-Level Meta-Analysis

Gender disparities in computational thinking (CT) education are widely acknowledged, but few meta-analyses have investigated how particular instructional approaches and assessment settings shape these differences. To address this research gap, Liu et al. (2025) conducted a meta-analysis of 53 empirical studies, covering 100 effect sizes and a total sample of 15,454 participants, to examine the overall magnitude of gender differences in CT education and the factors that may shape them. The findings show a small but statistically significant overall gender difference (g = 0.106, 95% CI [0.024, 0.188], p < .05), suggesting a slight advantage for males.

Regarding moderation effects, neither general study features (e.g., publication type, geographic region, and educational level) nor CT assessment contexts (e.g., the instrument used and the learning outcome measured) significantly altered the effect sizes. In contrast, pedagogical approaches did matter: technology-integrated strategies such as mixed and plugged approaches were linked to larger gender gaps favoring boys, whereas unplugged approaches tended to narrow the gap and sometimes even shifted the advantage toward girls. In terms of assessment, gender differences were not significant when CT concepts were measured, but they became significant when outcomes involved authentic practices (such as programming tasks) and identity-related dimensions (such as motivation, learning interest, and self-efficacy).

The results highlight clear implications for improving equity in CT education. Support should start early in K–12, with a particular focus on developing students’ CT practices and perspectives so that small gender gaps do not become persistent over time. Unplugged activities can serve as a low-barrier entry point, strengthening basic understanding and confidence, especially for girls. In addition, technology use should be introduced progressively: when digital and AI tools are scaffolded within supportive, culturally relevant learning settings, students may feel less anxious about technology and experience more inclusive participation.

 

Source (Open Access): Liu, S., Dai, Y., Ng, O. L., & Cai, Z. (2025). Gender Disparity in Computational Thinking Pedagogy and Assessment: A Three-Level Meta-Analysis. Educational Psychology Review, 37(4), 114.

https://doi.org/10.1007/s10648-025-10095-3… Read the rest

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Effective Teaching Approach K-12 Education Programme Evaluation

Equity in Teacher Education Programs: Conceptions and Program-Level Efforts

Ko-Wong (2025) conducts a systematic review to examine how teacher education programs (TEPs) in the United States conceptualize, implement, and prioritize equity. Drawing on 58 empirical studies that met rigorous inclusion criteria, the review synthesizes program-level equity efforts across coursework, field placements, recruitment strategies, faculty development, and structural reforms. The analysis highlights substantial conceptual ambiguity: many programs invoke equity rhetorically while relying on race-evasive framings, thin interpretations of fairness, or narrow emphases on access and achievement. Few studies explicitly address Whiteness, racism, power, or meritocracy—core constructs in critical equity frameworks.

Using an adapted strong-equity lens, the review finds that most TEPs focus on surface-level or fragmented activities, such as required multicultural courses or isolated field experiences, which often lack coherence and long-term impact. Although coursework and community-based placements can support preservice teachers’ awareness of diverse learners, evidence suggests that these efforts frequently fall short of transforming candidates’ racial literacy or challenging institutional hierarchies. Only a limited subset of programs adopt more systemic approaches that integrate equity across curricula, partnerships, supervision, and program structures.

The findings underscore the persistent gap between equity rhetoric and equity enactment in teacher preparation. Ko-Wong argues that meaningful progress requires programs to name and confront systemic racism, destabilize dominant ideologies such as color-evasiveness and meritocracy, and reimagine TEPs as sites of structural change rather than individual skill development. The review concludes with recommendations for advancing strong equity through conceptual clarity, coherent program design, and deeper engagement with racial justice frameworks.

Source (Open Access): Ko-Wong, L. (2025). Equity in Teacher Education Programs: A Systematic Review of Conceptions and Program-Level Efforts. Review of Educational Research, 00346543251382579.

https://doi.org/10.3102/00346543251382579… Read the rest

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Effective Teaching Approach K-12 Education

The learning styles paradox: Persistent appeal despite unsupported evidence

A puzzling paradox exists in education: even though many studies show that aligning teaching methods to students’ preferred learning styles (e.g., visual or auditory) has little impact on learning achievement, learning styles persistently emerge in educational discourse and research. A recent review that synthesized evidence from 17 meta-analyses explored why learning styles repeatedly resurface and provided an explanation for their persistent appeal.

The review identified a critical distinction between two sets of meta-analyses: (1) matching meta-analyses, which tested if matching teaching methods with students’ learning styles improved learning outcomes, and (2) correlational studies, which examined the relationship between students’ learning styles and learning outcomes. Results showed that the matching studies yielded a very small effect size (d = +0.04), providing evidence for the minimal benefit of aligning teaching methods with students’ learning styles. Moreover, while correlational meta-analyses looking at effects on student achievement produced an average correlation of r = +0.24, these correlations did not clarify causality or the direction of effects. In addition, across both sets of meta-analyses, the broad and inconsistent usage of learning styles blurred the line between learning styles and learning preferences or strategies.

The authors discussed that instead of simply relying on learning styles, effective teaching should focus on adaptable, evidence-based strategies that support learning. Students learn most effectively when they develop cognitive and metacognitive strategies suited to specific task demands, rather than relying on their preferred learning styles.

 

Source (Open Access): Hattie, J., & O’Leary, T. (2025). Learning styles, preferences, or strategies? An explanation for the resurgence of styles across many meta-analyses. Educational Psychology Review, 37(2), 31. https://doi.org/10.1007/s10648-025-10002-w… Read the rest