Category: Types of Evidence

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Effective Teaching Approach Secondary School Education

LLM-Based Collaborative Programming: Effects on Computational Thinking and Self-Efficacy

Yan et al. (2025) examine whether integrating large language models (LLMs) into collaborative programming can enhance students’ computational thinking, self-efficacy, and learning processes. Recognizing that traditional collaborative programming is often constrained by uneven skill levels among students, the study proposes an LLM-supported collaborative framework in which AI acts as a learning partner, transforming the conventional human–human interaction into a human–human–AI collaboration model. A quasi-experimental design was conducted with 82 sixth- and seventh-grade students in China, who were randomly assigned to either an LLM-supported collaborative programming group (experiment group) or a traditional collaborative programming group (control group).

The intervention lasted five weeks and included 12 programming sessions (90 min each) using C++ as the instructional language. Students in both groups worked in teams, but the experimental group used an LLM-based platform that provided structured, problem-based, and knowledge-based scaffolding throughout the programming process, including problem analysis, coding, debugging, and evaluation. Pre- and post-tests measured students’ computational thinking and self-efficacy, while cognitive load was assessed through questionnaires, complemented by semi-structured interviews.

Results indicate that students in the LLM-supported collaborative programming group achieved significantly higher gains in computational thinking compared to those in the traditional group, though the effect size was relatively small. In addition, students in the experimental group reported significantly lower cognitive load, particularly in mental load, suggesting that LLMs can reduce the cognitive burden associated with complex programming tasks. However, no statistically significant differences were found in self-efficacy between the two groups. Both groups showed a decline in self-efficacy over time, likely due to the transition from graphical programming to more abstract text-based coding, though the decline was less pronounced in the LLM-supported group.

Qualitative findings further reveal that LLM integration enhanced students’ learning experiences by increasing interest, improving problem-solving efficiency, and supporting collaboration. Students reported that LLMs provided immediate feedback, multiple solution strategies, and personalized guidance, enabling more effective engagement in programming tasks. Overall, the study demonstrates that LLMs can function as effective scaffolding tools in collaborative learning, reducing cognitive load and enhancing higher-order thinking. While their impact on self-efficacy remains inconclusive, the findings highlight the potential of AI-supported collaborative learning environments as a promising approach for programming education in K–12 contexts.

Source (Open Access): Yan, Y. M., Chen, C. Q., Hu, Y. B., & Ye, X. D. (2025). LLM-based collaborative programming: Impact on students’ computational thinking and self-efficacy. Humanities and Social Sciences Communications, 12(1), 149.https://doi.org/10.1057/s41599-025-04471-1… Read the rest

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Primary School Education Social and Motivational Outcomes

Effects of virtual reality exercise on social skills and emotional recognition among children with autism spectrum disorder: a meta-analysis of randomized controlled trials

A meta-analysis by Cui and colleagues assessed the effects of virtual reality (VR) exercise on social skills (SS) and emotional recognition (ER) among children with autism spectrum disorder (ASD). Analysing data from randomized controlled trials published between January 2005 and October 2025 across PubMed, Web of Science, Scopus, and EBSCO databases, the authors investigated the relationship between VR exercise interventions and children’s social-emotional development outcomes.

The authors employed standardized mean difference (SMD) as the effect size, utilizing random-effects models to synthesize results across studies. VR exercise interventions were compared with standard treatment approaches. The methodology included comprehensive database searches using keywords: virtual reality, autism spectrum disorder, and children. Quality assessment followed Cochrane Handbook guidelines, with heterogeneity evaluated through I² statistics. Subgroup analyses examined intervention duration effects (< 14 weeks versus ≥ 14 weeks), and secondary outcomes included cognitive function, anxiety, language function, and depression.

The results revealed significant positive effects of VR exercise on SS (SMD = 0.94 [0.71, 1.17], p < 0.05, I² = 74%) and ER (SMD = 0.42 [0.18, 0.65], p < 0.05, I² = 0%). Furthermore, subgroup analysis demonstrated that interventions lasting less than 14 weeks (SMD = 0.63 [0.36, 0.91], p < 0.05, I² = 0%) and those exceeding 14 weeks (SMD = 1.70 [1.27, 2.13], p < 0.05, I² = 44%) both substantially improved SS, with longer interventions showing greater effect sizes. Additionally, VR exercise improved cognitive function (SMD = 0.49 [0.06, 0.93], p < 0.05, I² = 0%) and reduced anxiety (SMD = 0.56 [1.10, 0.02], p < 0.05, I² = 0%). Notably, effects on language function and depression remained unclear due to insufficient evidence.

The findings underscore the effectiveness of VR exercise as a technological intervention modality superior to standard treatment approaches in enhancing social-emotional competencies among children with ASD. Therefore, future clinical practice should consider integrating VR exercise interventions into rehabilitation programs for children with ASD, particularly emphasizing intervention duration optimization to maximize therapeutic benefits. The moderate effect sizes and cautious interpretation regarding cognitive and anxiety outcomes require validation through larger-scale longitudinal studies with standardized outcome measures.

Source (Open Access): Cui, T., Ariffin, R. B., Wang, X., & Wang, X. (2026). Effects of virtual reality exercise on social skills and emotional recognition among children with autism spectrum disorder: a meta-analysis of randomized controlled trials. BMC psychology.

https://doi.org/10.1186/s40359-026-04160-x… Read the rest

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Effective Teaching Approach Kindergarten Language Development

The Playful Pen: Strategies for embedding Writing Instruction into Daily Play

To explore how educators can integrate early writing instruction into kindergarten classrooms through guided play. Sanchez (2025) addresses the growing tension between play-based learning and the rigid, policy-driven academic curricula common in modern early childhood education. Because strict mandates often cause frustration for young learners during formal writing tasks, Sanchez (2025) proposes guided play—a blend of child-led exploration and intentional adult scaffolding—as a pedagogical solution to meet literacy goals while preserving autonomy.

The study was designed as a five-month participatory action research project conducted by Sanchez (2025) in a public kindergarten classroom of 25 students. Sanchez (2025) dedicated one hour daily to guided play, intentionally introducing targeted writing tools, books, and printables into popular areas like the playdough, block, dramatic play, and Lego centers. By carefully observing and interacting with the children, Sanchez (2025) seamlessly integrated early writing prompts into their natural play routines.

By thoughtfully curating materials and engaging in collaborative dialogue, Sanchez (2025) successfully motivated students to independently incorporate writing into their spontaneous play. Children naturally began authoring authentic texts, including “how-to” guides for playdough snowmen, labels for complex block mazes, dramatic play pie recipes, and step-by-step Lego instructions. This playful approach transformed writing from a stressful, mandated chore into a joyful, self-directed activity that empowered even the most reluctant students.

Sanchez (2025) concludes that guided play effectively dismantles the false dichotomy between structured academic learning and early childhood play. The research highlights that successful implementation requires dedicating adequate classroom time, encouraging storytelling with an audience, and fostering a supportive community among educators. Ultimately, intentional scaffolding allows writing to evolve from an isolated academic skill into an authentic, meaningful communication tool that honors young children’s agency.

 

Source (Open Access): Sanchez, A. (2025). Guided play in the kindergarten classroom: One teacher’s inquiry into scaffolding play-based writing instruction. Early Childhood Education Journal, 53(6), 2089-2098.

https://doi.org/10.1007/s10643-025-01931-w… Read the rest

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Primary School Education Secondary School Education Social and Motivational Outcomes

Teachers’ Teaching Emotions, Teaching Mindset, and AI Readiness

Ti and colleagues employed a cross-sectional survey design with hierarchical regression and moderation analyses to examine how in-service teachers’ teaching emotions and teaching ability mindset predict their AI readiness, and whether mindset moderates the relationship between emotions and AI readiness. The study included 424 in-service teachers in China (mean age = 38.76 years) from both primary and secondary schools. AI readiness was measured using Wang et al.’s (2023) four-dimensional framework, including cognition, ability, vision, and ethics. Teaching emotions were categorized into positive and negative emotions, and teaching mindset was classified as growth or fixed. Gender and social desirability bias were controlled in the analyses, and interaction effects were tested using the PROCESS macro.

The results showed that positive teaching emotions significantly and positively predicted all four dimensions of AI readiness (B ≥ .48, p < .001), whereas negative emotions did not significantly predict any dimension (|B| ≤ .06, p ≥ .309). Regarding mindset, a growth teaching mindset had significant positive effects on cognition, ability, vision, and ethics (B ≥ .18, p < .01), indicating that teachers who view teaching ability as developable are better prepared to respond to AI-related educational change. Interestingly, a fixed teaching mindset did not uniformly produce negative effects; instead, it positively predicted the cognition and ability dimensions (B ≥ .17, p < .01), although it was not significant for vision and ethics. Overall, the inclusion of emotions and mindset in the models yielded medium to large effect sizes (.28 ≤ f² ≤ .36), suggesting substantial explanatory power.

Moderation analyses further revealed that a growth teaching mindset strengthened the positive relationship between positive emotions and AI cognitive readiness (B = .11, p < .05). In other words, teachers with both high positive emotions and a strong growth mindset demonstrated higher levels of understanding regarding AI roles and functions. In contrast, a fixed teaching mindset moderated the relationship between negative emotions and the cognitive dimension (B = .10, p < .05). When fixed mindset was low, negative emotions significantly reduced cognitive readiness (B = –.18, p < .05), whereas this effect was not significant when fixed mindset was high. Notably, moderation effects were observed only for the cognition dimension, suggesting that the cognitive aspect of AI readiness is particularly sensitive to the interaction between emotional and mindset resources.

Overall, this study indicates that teachers’ readiness for AI integration in education is influenced not only by technical training or institutional support but also by their emotional experiences and beliefs about the malleability of teaching ability. Positive emotions and a growth teaching mindset serve as important psychological resources that enhance AI readiness, especially in shaping teachers’ cognitive understanding of AI. The authors recommend that AI-related professional development initiatives incorporate emotional regulation support and mindset cultivation to foster more comprehensive and sustainable AI readiness among teachers.

Source (Open Access): Ti, Y., Sun, Y., & Li, X. (2026). Predicting in-service teachers’ AI readiness from emotions in teaching and mindsets about teaching ability: Testing the direct and moderating effects. Teaching and Teacher Education, 175, 105433.

https://doi.org/10.1016/j.tate.2026.105433… Read the rest

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Higher Education Language Development

Comparing the effects of ChatGPT and automated writing evaluation on students’ writing and ideal L2 writing self

Using a randomized controlled experimental design, Shi et al. (2025) compared the effects of ChatGPT-based feedback and traditional automated writing evaluation (AWE) systems on English-as-a-foreign-language (EFL) students’ writing performance and their ideal L2 writing self. One hundred and fifty second-year university students from three writing classes in a Chinese public university were recruited and randomly divided into a ChatGPT group, an AWE group, and a control group.

After an eleven-week intervention, results showed that ChatGPT helped students perform better in their writing compared to the control group and the AWE group, but compared to the AWE group, ChatGPT significantly lowered students’ ideal L2 writing self. Qualitative results shed light on possible causes: while participants were fully aware of the affordances of ChatGPT feedback, they were also concerned with their (over) reliance on the tool and the accompanying loss of creativity and agency and expressed their reserved attitude toward future intention to use ChatGPT.

Educators should refine learning objectives based on students’ ZPD and design prompts accordingly, so that ChatGPT supports learning rather than completing tasks, while also teaching prompt-engineering skills. For lower-intermediate to intermediate learners, AWE’s systematic and rule-based feedback can provide stronger scaffolding and better preserve authorship. However, ChatGPT’s richer affordances may lead to over-reliance, weakening learner agency and diminishing the ideal L2 writing self. Therefore, language-education goals should be redefined to incorporate AI literacy and critical thinking, safeguarding teacher and learner agency and promoting responsible use.

 

Source (Open Access): Shi, H., Chai, C. S., Zhou, S., & Aubrey, S. (2025). Comparing the effects of ChatGPT and automated writing evaluation on students’ writing and ideal L2 writing self. Computer Assisted Language Learning, 1-28.

https://doi.org/10.1080/09588221.2025.2454541… 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