Category: Types of Evidence

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Effective Teaching Approach Primary School Education

Support for self-regulated learning in immersive virtual reality – An experimental design for science learning

Immersive virtual reality (IVR) enables users to engage with virtual environments in a highly immersive way. Past studies have found that immersive virtual reality (IVR) may increase students’ cognitive load, distract them from learning tasks, and hinder their knowledge acquisition. To address these challenges, Hsu and Lee (2026) explored the integration of self-regulated learning (SRL) strategies into IVR, and examined their impact on students’ cognitive load. An experimental design was employed, involving 105 students randomly assigned to either an SRL group (n=52) or a non-SRL (NSRL) group (n = 53). A two-way mixed-design ANOVA was conducted to identify differences in the science learning outcomes of the two groups. In addition, partial least squares structural equation modeling (PLS-SEM) was applied to examine the structural relationships among affective factors in IVR environments, cognitive load, and students’ learning outcomes within both the SRL and NSRL conditions.

The findings confirm that, while learning with IVR, extraneous cognitive load exerted negative effects on both SRL gains and science knowledge, whereas germane cognitive load positively influenced these outcomes. First, interactive extraneous cognitive load predicted both lower- and higher-level science knowledge in the NSRL group. Second, environmental extraneous cognitive load negatively predicted SRL gains across both IVR conditions.  Third, a finding common to both the SRL and NSRL groups was that increased student control and active learning significantly enhanced perceived germane cognitive load.

As IVR technology becomes increasingly accessible and user-friendly, it is no longer confined to professional instructional designers; teachers now need the capacity to independently create VR-based learning materials. This shift highlights the importance of preparing teachers not only to use VR tools but also to design pedagogically meaningful IVR content, such as the incorporation of SRL strategies. Accordingly, teachers must recognize the benefits of presence and interaction while remaining cautious of their limitations and potential pitfalls. They should also be mindful that less optimal instructional designs may impose extraneous cognitive load, which can undermine learning outcomes. Most importantly, teachers should foster learners’ autonomy and agency, as these are critical for effective IVR-based learning.

Source (Open Access): Hsu, Y. T., & Lee, S. W. Y. (2026). Support for self-regulated learning in immersive virtual reality–An experimental design for science learning. Education and Information Technologies, 31(1), 269-300.

https://doi.org/10.1007/s10639-025-13807-y… Read the rest

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Achievement Higher Education Primary School Education Secondary School Education

The impact of test preparation on performance in large-scale educational tests: A meta-analysis of experimental studies

A recent meta-analysis examines whether test preparation improves performance in large-scale educational tests. Although schools, commercial institutions, and students invest heavily in preparation courses and materials, existing studies have reported inconsistent effects. Earlier reviews were also concentrated on US college admission and cognitive ability tests and often relied on evidence published before 2000. This study therefore estimates the overall effect of test preparation and examines how it varies across intervention, test, student, and research-design characteristics.

The authors synthesized 28 experimental and quasi-experimental studies, including 92 effect sizes and 16,741 participants across primary, secondary, and tertiary education. The studies covered college admission tests, English proficiency tests, and other large-scale assessments. A hierarchical random-effects model with robust variance estimation was used, while moderator analyses examined intervention breadth, strategy and material use, test characteristics, previous test experience, and study design.

Test preparation produced a significant positive overall effect on test performance (g=.26, 95% CI [.10,.42], p<.001), but heterogeneity was high (I^2=82.44%). Test-specific and narrowly focused interventions were more effective (g=.33) and (g=.32) than broad programs aimed at general knowledge or transferable skills (g=-.04). Interventions teaching test-taking strategies also showed stronger effects (g=.35) than those without such instruction (g=.05). Students with previous testing experience benefited substantially more (g=.69) than those without it (g=.06). However, preparation effects did not transfer significantly to other tests in the same domain (g=.06, p=.502).

Taken together, the findings suggest that test preparation can improve large-scale test scores, but its effectiveness mainly reflects alignment with the target test rather than broader learning gains. The limited transfer effect raises concerns about whether score improvement represents genuine development in the abilities being assessed. Future research should use stronger experimental designs, report intervention processes more clearly, and distinguish test-score gains from transferable learning.

Source (Open Access): Hao, Z., Baird, J. A., Masri, Y. E., & Double, K. (2025). The impact of test preparation on performance of large-scale educational tests: A meta-analysis of experimental studies. Review of Educational Research, 00346543251360775.

https://doi.org/10.3102/00346543251360775… Read the rest

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Effective Teaching Approach Programme Evaluation Secondary School Education

Linking Classrooms and Museums for Self-Regulated STEM Learning

Lewalter et al. (2025) examine how school-based factors shape students’ self-regulated STEM learning during and after a museum visit. The study addresses an important challenge in STEM education: how to connect classroom learning with meaningful real-world contexts beyond school. Focusing on a museum exhibition about mobility and traffic, the authors investigate whether students’ learning strategy knowledge, prior knowledge, prior interest, and classroom preparation or follow-up activities predict their learning processes during the visit and their learning outcomes three months later.

The study used a pretest–posttest–follow-up design with 409 Grade 10 students from 21 classes in 12 German high schools. Students visited the Deutsches Museum München and explored a tablet-supported exhibition programme titled Mobility Transition—What Moves Us in the Future? Traffic and Mobility Challenges of the 21st Century. During the 90-minute visit, students worked in small groups and engaged in self-guided exploration of selected exhibits. Questionnaire data were collected one week before the visit, immediately after the visit, and approximately three months later to measure learning strategy knowledge, preparation and follow-up activities, situational interest, basic psychological needs, perceived content relevance, engagement, knowledge, and individual interest.

Results show that most students did not experience systematic classroom integration of the museum visit: 75% reported no classroom preparation, and 60.4% reported no follow-up activities after the visit. Students’ metacognitive and motivational learning strategy knowledge positively predicted several aspects of the learning process, including perceived content relevance, basic need satisfaction, situational interest, and engagement. However, when prior individual interest was included in the model, it became the strongest predictor of learning process variables, suggesting that students’ existing interest plays a central role in shaping museum-based STEM learning.

For medium-term learning outcomes, follow-up activities in the classroom were especially important. Three months after the museum visit, students who experienced classroom follow-up showed higher self-perceived and objective knowledge. Knowledge of learning strategies also contributed to self-perceived knowledge, whereas students’ later individual interest was mainly predicted by their prior individual interest. Overall, the findings highlight that museum visits should not be treated as isolated field trips. Instead, their educational value depends on stronger links between classroom teaching and out-of-school learning, particularly through helping students develop self-regulated learning strategies and providing meaningful follow-up activities after the visit.

Source (Open Access): Lewalter, D., Neubauer, K., & Moser, S. (2025). Self-regulated STEM learning in museums—the role of learner characteristics and visit-related activities in school. International Journal of STEM Education, 12(1), 56.

https://doi.org/10.1186/s40594-025-00577-9… Read the rest

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Educational Administration and Leadership Higher Education K-12 Education

The impact of generative artificial intelligence on students’ higher order thinking: Evidence from a three-level meta-analysis

Given the current trends in AIEd, it is crucial to synthesize the overall impact of Gen-AI on HOT, as Gen-AI has been creatively applied by researchers to assist in teaching and learning. Concerns exist in current discourse that Gen-AI may harm HOT. However, empirical research on the specific effects of Gen-AI on HOT remains scattered, and no consensus has been reached. Nie et al.’s (2025) study synthesized 19 experimental and quasi-experimental studies conducted in different contexts (k=68), involving 2,347 participants. A three-level meta-analysis was employed to account for within- and between-study variability, assessing the impact of Gen-AI on HOT and exploring the effects of moderators.

The results revealed that Gen-AI had a significant positive effect on enhancing students’ HOT (Hedges’s g=0.851, p<0.001). Moderator analyses were conducted based on impact target, Gen-AI elements, study contexts, and methodological characteristics. When the sample size was less than 80, the promotion effect was more significant. Both short-term interventions (less than 4 weeks) and long-term interventions (more than 8 weeks) have the potential to produce significant positive effects.

These findings offer vital policy implications for integrating Gen-AI into education. First, educational authorities should mandate smaller class sizes or optimized student-to-teacher ratios in AI-driven curricula, as large groups dilute Gen-AI’s efficacy in fostering HOT. Second, curriculum frameworks must transition from short-term pilots to extended, long-term intervention timelines, given that 4-8 weeks is insufficient for deep cognitive development. Lastly, policymakers should fund targeted, granular research into AI’s specific impacts on different dimensions of HOT to guide the scaling of intelligent, personalized, and adaptive educational ecosystems.

Source (Open Access): Nie, X., Tian, Y., Liu, M., Wu, D., & Guo, Y. (2025). The impact of generative artificial intelligence on students’ higher order thinking: Evidence from a three-level meta-analysis. Education and Information Technologies, 30(17), 25359-25390.https://doi.org/10.1007/s10639-025-13735-x… Read the rest

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Higher Education Language Development

Task Offloading to GenAI in the Writing Feedback Process and Its Effects on Writing Development

Lai and colleagues used a quasi-experimental design to investigate whether offloading different tasks to GenAI in the “draft–assess–revise” workflow affects English-as-a-foreign-language (EFL) students’ writing development. Conducted over seven weeks, the study involved 101 Chinese university students and compared three conditions: (1) GenAI drafting, student assessment, student revision; (2) student drafting, GenAI assessment, student revision; and (3) student drafting, student self-assessment, student revision.

Results showed that the GenAI drafting group performed best in writing ability (M = 18.21, SD = 2.21), significantly higher than both the GenAI assessment group (M = 16.30, SD = 1.70) and the no GenAI group (M = 15.15, SD = 1.79). This indicates that including GenAI in the feedback workflow generally benefits writing, but offloading the drafting task rather than the assessment task produces the strongest effects.

Regarding cognitive processes, the GenAI drafting group showed significantly higher cognitive engagement, utilizing more total prompts (median 20.50 vs. 9.00, U = 195, p < .001) and more learning-oriented prompts (median 10.50 vs. 8.00, U = 398.50, p < .05) than the assessment group. They also outperformed the other two groups in metacognition in problem identification (M = 4.41), argumentation (M = 2.82), and providing constructive feedback (M = 4.97) during peer review.

In writing self-efficacy, the GenAI drafting group demonstrated the largest improvement (M = 4.74, SD = .55), significantly higher than the other groups, whereas the GenAI assessment group (M = 4.42, SD = .53) and no GenAI group (M = 4.45, SD = .78) did not differ significantly. Interviews revealed these students experienced a stronger sense of control and competence because they could critically evaluate and revise AI-generated drafts. In contrast, some students in the GenAI assessment group worried about overreliance on AI feedback, leading to “false confidence.”

Overall, the study highlights that the educational value of GenAI in writing feedback depends on which tasks are offloaded to AI. Offloading the drafting task to GenAI while having students handle assessment and revision promotes deeper cognitive engagement, stronger metacognitive understanding, and higher self-efficacy. The authors recommend that writing instruction should prioritize AI-generated drafts paired with student evaluation and revision, serving as a catalyst for critique and reflection rather than replacing student thinking.

Source (Open Access): Lai, C., Pan, M., Guo, K., & Cui, Y. (2026). What task to offload to GenAI in the writing feedback process? – Effects of task-offloading approaches on EFL learners’ writing skill development. Computers & Education, 252, 105675.

https://doi.org/10.1016/j.compedu.2026.105675… Read the rest

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Achievement Higher Education

Student agency in Colombian higher education: a dual-pathway model of mediation and moderation between student engagement and academic achievement

A recent quantitative study by Torres Castro and Pineda-Baéz examines the relationship between student engagement and academic achievement, with particular attention to how student agency functions as both a mediating and a moderating mechanism in this relationship.

The study surveyed 1,713 final-year students from six accredited private universities across five regions in Colombia. Grounded in social cognitive theory and the ecological model of student engagement, the study conceptualizes student engagement as a multidimensional construct. It encompasses ten indicators across four domains: academic challenge, learning with peers, experiences with faculty, and campus environment. Student engagement is assessed through the National Survey of Student Engagement, with scores standardized on a 0 to 60 scale. Student agency is operationalized as agentic engagement through the five-item Agentic Engagement Scale. This scale captures proactive behaviors such as expressing preferences, asking questions, and suggesting adjustments to instruction. Academic achievement was measured by self-reported cumulative grade point average on Colombia’s standardized 0.0 to 5.0 scale. The study employed hierarchical regression with robust standard errors, structural equation modeling, and bootstrap-based mediation analysis using R version 4.3.1.

The findings reveal that among the ten engagement indicators, only collaborative learning and student-faculty interaction are positively and independently associated with academic achievement. Among the five agentic engagement behaviors, only expressive voice emerged as a significant mediator, channeling approximately six percent of the total effect of collaborative learning on grade point average. Expressive voice also moderated the relationship between student-faculty interaction and grade point average in a compensatory pattern. The association between faculty interaction and achievement was stronger among students with lower levels of expressive voice, whereas it was attenuated yet remained positive among those with higher levels. Although effect sizes were modest, the findings demonstrate that student agency operates as a context-dependent dual mechanism.

The study further suggests that instructional practices should combine structured guidance with opportunities for student-initiated contribution, and that support systems should prioritize students with lower levels of agentic engagement.

Source (Open Access): Torres Castro, U. E., & Pineda-Baéz, C. (2026). Student agency in Colombian higher education: a dual-pathway model of mediation and moderation between student engagement and academic achievement. Higher Education, 1-20.

https://doi.org/10.1007/s10734-026-01669-3… Read the rest