Author: cuspbeib

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Kindergarten Social and Motivational Outcomes

An experimental study exploring human–AI complementarity in early social-emotional learning

A recent experimental study by Raave and colleagues employed a mixed factorial design to compare a pedagogical conversational agent (PCA) with human educators in facilitating early social-emotional learning (SEL). Eighteen international early childhood and primary teachers and an AI-driven PCA each conducted three standardized story-based SEL activities with a static AI child named “Ali,” designed to exhibit challenging characteristics including distractibility and limited empathy. This controlled comparison yielded 108 total observations across activities focusing on prosocial behavior, perspective-taking, and healthy guilt induction.

Expert raters, blind to facilitator type, coded interactions for three evidence-based pedagogical support techniques—cognitive-conceptual, procedural, and emotional support—using binary scales, and assessed broader teaching quality across six dimensions adapted from the Danielson Framework for Teaching on a 1-4 scale. The study maintained high inter-rater reliability across all measures (Cohen’s κ=.65−.80 for support techniques; quadratic weighted κ=.61−.76 for quality indicators).

Results revealed significant differences in facilitation approaches. Mixed ANOVA showed educators used more support techniques overall (M=7.57 vs. M=5.47) and substantially more cognitive-conceptual support than the PCA (M=15.28 vs. M=6.46, p<.001), while the PCA provided slightly more procedural support (p=.026). Quality ratings demonstrated complementary strengths: the PCA scored higher in relational domains such as respect and rapport (d=1.86) and flexibility (d=1.06), whereas educators excelled in intellectual engagement including questioning techniques (d=0.72) and engaging students in learning (d=0.96).

The findings reveal meaningful pedagogical asymmetry suggesting human-AI complementarity rather than competition. The PCA maintained consistent emotional validation and procedural structure but tended to be “caring but pedagogically shallow,” while educators provided deeper cognitive-conceptual scaffolding and moral reasoning guidance with greater affective variability. The authors propose a strategic division of labor where PCAs manage routine structuring and baseline emotional support, while human educators focus on complex social-emotional reasoning and ethical development. Future research should explore direct co-facilitation models in authentic classroom settings.

Source (Open Access): Raave, D. K., Colasante, T., Roa, E. R., Martinez, J. C. R., Li, H., Mukherjee, S., & Malti, T. (2026). An experimental study exploring human–AI complementarity in early social-emotional learning. Computers and Education Open, 100331.

https://doi.org/10.1016/j.caeo.2026.100331… Read the rest

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Primary School Education Programme Evaluation

The effects of a school-based leadership program on student leaders and their peers: A cluster randomized controlled trial

Student leadership is widely recognized as an important life skill associated with academic, psychological, and social benefits. However, school-based leadership opportunities are often offered to students who already display leadership qualities, while those who may benefit most from such opportunities are less likely to participate. Existing leadership research has also focused mainly on adults, leaving limited evidence on how leadership skills can be developed among young students. To address this gap, this study evaluated Learning to Lead, a peer-led, school-based leadership and fundamental movement skills program grounded in transformational leadership theory.

The study used a two-arm cluster randomized controlled trial design involving 20 elementary schools in Australia. A total of 1,898 students participated, including 952 older students as Leaders and 946 younger students as Peers. Schools were randomized to either the intervention group or a wait-list control group after baseline assessment. The intervention consisted of teacher professional development, six leadership lessons delivered by trained teachers to student Leaders, and twelve peer-led fundamental movement skill sessions delivered by Leaders to younger Peers. Outcomes were assessed at baseline and immediately after the intervention. Leader outcomes included teacher-reported leadership effectiveness, self-reported leadership ability, leadership self-efficacy, wellbeing, and classroom time on-task. Peer outcomes included physical activity, perceived and actual motor competence, cardiorespiratory fitness, and muscular fitness.

The results showed that the L2L program produced significant benefits for both Leaders and Peers. For Leaders, teacher-reported leadership effectiveness improved significantly in the intervention group compared with the control group, with an adjusted between-group difference of 0.56 units and an effect size of d = 0.39. The intervention also produced positive spillover effects: Leaders showed significantly greater wellbeing, with an adjusted difference of 0.77 units, and their classroom time on-task increased by approximately 7 percentage points. However, the program did not significantly improve Leaders’ self-reported leadership ability or leadership self-efficacy. For Peers, the intervention significantly improved perceived motor competence, with an adjusted difference of 1.12 units, increased daily moderate-to-vigorous physical activity by 3.02 minutes per day, and improved cardiorespiratory fitness by 2.57 laps. Moderator analysis showed that the effect on perceived motor competence was significant for both boys and girls, but stronger among boys. However, the program did not significantly improve Peers’ actual motor competence or muscular fitness.

Taken together, the findings suggest that peer-led leadership programs can improve student leaders’ observable leadership effectiveness and generate broader benefits for their wellbeing and classroom engagement. The program also benefited younger peers by improving their perceived motor competence, physical activity, and cardiorespiratory fitness. These findings indicate that school-based peer-led interventions can meaningfully integrate leadership development with physical activity promotion. Nevertheless, the study has several limitations, including short-term outcome assessment, possible teacher expectancy effects in ratings of student leadership, possible awareness of group allocation among video coders, and the challenge of relying on student Leaders who were still developing their own leadership and movement skills. Future research should examine the long-term effects of such programs and consider providing stronger instructional support for student Leaders.

Source (Open Access): Wade, L., Beauchamp, M. R., Nathan, N., Smith, J. J., Leahy, A. A., Bao, R., Kennedy, S. G., Boyer, J., Diallo, T. M. O., Beacroft, S., & Lubans, D. R. (2026). Effects of a school-based leadership program on student leaders and their peers: The Learning to Lead cluster randomized controlled trial. Contemporary Educational Psychology, 102444.

https://doi.org/10.1016/j.cedpsych.2026.102444… Read the rest

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Effective Teaching Approach Kindergarten

From Worksheets to Workstations: The Impact of Play and Choice in Kindergarten Classrooms

Although high-stakes testing has increasingly shifted early childhood education toward teacher-directed academic instruction, Rodriguez-Meehan et al. (2025) argue that play and meaningful choices remain essential for children’s development. Grounded in self-determination theory (SDT), Rodriguez-Meehan et al. (2025) explore the integration of play- and choice-based workstations in a kindergarten classroom to understand how fostering autonomy, competence, and relatedness through self-directed play influences student motivation and behavior.

To capture a comprehensive view of this transition, Rodriguez-Meehan et al. (2025) conducted a qualitative case study in a public charter school in the Southeastern United States, focusing on one kindergarten teacher and a subset of her students. Data collection included four comprehensive classroom observations, a semi-structured individual interview with the teacher, and interactive focus group interviews with the children. Additionally, the research team analyzed student artifacts, such as drawings and writings. The collected data underwent holistic analysis to identify emerging themes reflecting the participants’ experiences.

The analysis revealed three primary themes regarding the classroom’s transformation. First, the teacher viewed the implementation as highly successful, noting drastic improvements in academic achievement, student engagement, and classroom behavior. Second, the transition required a “balancing act,” as the teacher navigated initial structural barriers like managing physical space and rationing access to highly preferred activities. Third, the children demonstrated immense joy and ownership over their learning, repeatedly expressing enthusiasm about picking their own workstations and peers.

Rodriguez-Meehan et al. (2025) conclude that replacing traditional morning worksheets with free play and adaptable choice centers effectively supports children’s intrinsic motivation and social-emotional needs. Although implementing these pedagogies requires teacher flexibility and a willingness to relinquish some control, the benefits strongly align with the principles of self-determination theory. Ultimately, the study advocates for school administrators, educators, and families to actively support and integrate more daily play and choice-based frameworks in early childhood environments.

Source (Open Access): Rodriguez-Meehan, M., Chobrda, T., Haughton, V. J., & Franz, M. (2025). “The best part of their day”: Play and choice in kindergarten. Journal of Early Childhood Research, 23(2), 164-178.

https://doi.org/10.1177/1476718X241293909… Read the rest

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Maths and Science Learning Primary School Education

Generative AI and Multimodal Data for Educational Feedback: Insights from Embodied Math Learning

Cosentino et al. (2025) explore the role of generative AI (GenAI) in providing formative feedback within embodied mathematics learning environments. Building on embodied cognition theory and advances in multimodal learning technologies, the study examines whether AI-generated feedback can effectively support students’ learning processes compared to traditional teacher feedback. The research focuses on children learning integer operations through a body-scale digital number line, where physical movement is integrated into mathematical reasoning.

Using a between-group experimental design, 34 students aged 11-13 were assigned to either a GenAI feedback condition or a human teacher feedback condition. Students interacted with a multisensory learning environment (MOVES), where their movements were tracked and used to generate real-time, adaptive feedback through a GPT-4–based system. Multimodal data, including eye-tracking, system logs, and behavioral measures, were collected to assess task performance, cognitive load, and information processing patterns.

Results show no significant differences in task-based learning performance between the GenAI and teacher feedback conditions. However, students receiving GenAI feedback demonstrated significantly lower cognitive load and more balanced information processing strategies, as indicated by eye-tracking metrics such as pupil dilation and the Information Processing Index (IPI). In contrast, students in the teacher feedback condition exhibited higher cognitive load and more frequent attention shifts toward irrelevant or incorrect options, suggesting less efficient processing.

Overall, the findings highlight the potential of GenAI as an effective tool for delivering structured, adaptive feedback that enhances learning efficiency without compromising learning outcomes. Rather than replacing teachers, the study emphasizes the value of hybrid intelligence approaches that integrate AI and human feedback to optimize learning experiences. The results provide important implications for designing AI-enhanced, multimodal learning environments that support cognitive engagement and personalized learning in mathematics education.

Source (Open Access): Cosentino, G., Anton, J., Sharma, K., Gelsomini, M., Giannakos, M., & Abrahamson, D. (2025). Generative AI and multimodal data for educational feedback: Insights from embodied math learning. British Journal of Educational Technology, 56(5), 1686-1709.

https://doi.org/10.1111/bjet.13587… Read the rest

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Programme Evaluation Secondary School Education

Teaching Quality in STEM Enrichment Programs: Gifted Students’ Perceptions of In-School and Out-of-School Learning Environments

Jaggy et al. (2025) investigate how gifted students perceive teaching quality in specialized STEM enrichment programs compared with their regular school classrooms. Previous research has shown that high-ability students often experience learning environments differently from their peers, yet little is known about how participation in extracurricular enrichment programs influences students’ evaluation of teaching quality in both in-school and out-of-school settings. To address this gap, the study examines students attending the Hector Seminar, a specialized STEM enrichment program for gifted secondary school students in Germany and compares their perceptions of teaching quality across learning contexts.

The study uses cross-sectional data from a large-scale talent development project including academically advanced sixth- and seventh-grade students in the German state of Baden-Württemberg. Teaching quality was assessed using student reports on six indicators derived from the three-basic-dimensions model of instructional quality: effective classroom management, cognitive activation, student support, adaptivity, interestingness, and motivational climate. Two research questions guided the analysis: whether gifted students evaluate teaching quality in the enrichment program higher than in regular school classes, and whether students attending the program perceive regular classroom teaching differently from comparable students who do not participate in the program.

Results show that students attending the specialized STEM enrichment program rated teaching quality significantly higher in the program than in their regular school classes across most indicators, particularly in interestingness, motivational climate, and adaptivity. These findings suggest that enrichment programs provide highly stimulating and supportive learning environments for gifted students. Importantly, however, participation in the enrichment program did not lead students to evaluate their regular school teaching more negatively compared with non-participants, indicating that potential reference effects between learning contexts were limited.

Overall, the study highlights the importance of specialized enrichment programs as high-quality learning environments for gifted students while showing that such programs do not necessarily undermine students’ perceptions of regular classroom instruction. The findings contribute to research on gifted education and teaching quality by demonstrating that macro-level adaptations, such as structured STEM enrichment programs, can enhance learning experiences without producing negative comparison effects. The results also underscore the need for teacher professional development and more individualized instruction to better support diverse student needs across learning settings.

 

Source (Open Access): Jaggy, A. K., Wagner, W., Fütterer, T., Göllner, R., & Trautwein, U. (2025). Teaching quality in STEM education: Differences between in-and out-of-school contexts from the perspective of gifted students. International Journal of STEM Education, 12(1), 53.

https://doi.org/10.1186/s40594-025-00576-w… Read the rest

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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