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Effective Teaching Approach Secondary School Education

Enhancing Middle School Science Learning with AR-Supported Intelligent Tutoring

Ateş (2025) examines whether combining augmented reality (AR) with an intelligent tutoring system (ITS) can improve middle school students’ science learning outcomes and learning experiences. The study focuses on the teaching of the periodic table, a topic that is often difficult for students because it involves abstract concepts and complex relationships among elements. By integrating AR-based visualizations with ITS-supported personalized feedback, adaptive learning paths, and individualized support, the research explores whether this technology-enhanced approach can outperform conventional science instruction.

Using a quasi-experimental pretest–posttest control group design, the study involved 58 eighth-grade students from a public middle school. The experimental group learned through the ITS-AR system, while the control group received traditional textbook-based instruction, lectures, demonstrations, practice exercises, and assessments. The intervention lasted eight weeks: students first received an introduction to the learning system, then completed pretests and questionnaires, participated in four weeks of instruction, and finally completed posttests and post-questionnaires. Measures included academic achievement, student engagement, science motivation, and self-efficacy.

Results indicate that students in the ITS-AR group significantly outperformed those in the control group across all measured outcomes. After controlling for pretest differences, the experimental group showed higher science learning outcomes, stronger engagement, greater motivation to learn science, and higher self-efficacy. The AR component helped students visualize and interact with periodic table content in more dynamic ways, while the ITS component provided feedback on students’ project ideas and supported more individualized learning. Together, these features appeared to make abstract scientific ideas more concrete, interactive, and accessible.

Overall, the findings suggest that AR-supported intelligent tutoring can be an effective instructional approach for improving science learning and supporting students’ motivational and affective development. The study highlights the value of integrating artificial intelligence and immersive visualization tools into science education, particularly when students need to understand abstract or visually demanding concepts. At the same time, because the study was conducted with a relatively small sample from one school, the findings should be interpreted as promising evidence that requires further validation across broader and more diverse educational contexts.

Source (Open Access): Ateş, H. (2025). Integrating augmented reality into intelligent tutoring systems to enhance science education outcomes. Education and Information Technologies, 30(4), 4435-4470.

https://doi.org/10.1007/s10639-024-12970-y… Read the rest

Categories
K-12 Education Social and Motivational Outcomes

The Relationship Between Teacher Burnout, Absenteeism, Teacher–Student Interactions, and Student Motivation and Achievement

Wartenberg and colleagues used meta-analysis and systematic review methods to comprehensively examine the relationship between teacher burnout, teachers’ professional functioning, and student outcomes. The study integrated 86 studies, 90 independent samples, and a total of 38,457 teachers, systematically analyzed the associations between three core burnout symptoms—emotional exhaustion, depersonalization, and reduced personal accomplishment—and teacher absenteeism, the quality of teacher–student interactions, and student motivation and academic achievement.

The results showed that teacher burnout was consistently related to multiple professional and student outcomes, although the strength of the associations varied. First, in terms of teacher absenteeism, emotional exhaustion was positively but weakly related to absenteeism (r = .18, 95% CI [.08, .29]), depersonalization was also weakly positively related to absenteeism (r = .14, 95% CI [.04, .24]), and reduced personal accomplishment showed an association close to zero but still significant (r = .08, 95% CI [.03, .12]). Second, regarding teacher–student interactions, all three burnout symptoms were negatively related to interaction quality, with depersonalization (r = −.21, 95% CI [−.33, −.09]) and reduced personal accomplishment (r = −.21, 95% CI [−.37, −.05]) showing stronger links than emotional exhaustion (r = −.12, 95% CI [−.17, −.07]). Third, regarding student outcomes, emotional exhaustion was weakly negatively associated with student motivation (r = –.23, 95% CI [–.28, –.17]), but its overall association with student academic achievement was close to zero (r = –.05, 95% CI [–.11, .01]). Although fewer studies examined depersonalization and reduced personal accomplishment in relation to student motivation and achievement, the overall pattern was also negative.

Further meta-regression analyses showed that the source of ratings was an important moderator, and teacher self-reports usually produced stronger negative associations than external ratings, with the association between reduced personal accomplishment and instructional support was r = –.41 in teacher self-reports, but no longer significant in external reports (r = –.03; β = –.35, p < .001). This suggests that relying only on teacher self-ratings may overestimate the relationship between teacher burnout and teaching performance.

Overall, this study shows that teacher burnout is related not only to teachers’ own risk of absenteeism, but also consistently to poorer teacher–student interaction quality and lower student motivation, while its direct association with student academic achievement is relatively weak. The study also highlights that the different dimensions of burnout do not operate in the same way, with depersonalization and reduced personal accomplishment often showing stronger links to teacher–student interactions than emotional exhaustion. Based on these findings, the authors suggest that future teacher support and intervention programs should not focus only on reducing stress or emotional exhaustion, but should also pay attention to maintaining the quality of teacher–student interactions and teachers’ sense of professional competence. Methodologically, future research should combine observations, student reports, and longitudinal designs to capture more accurately the actual effects of teacher burnout on teaching and student development.

Source (Open Access): Wartenberg, G., Aldrup, K., Grund, S., & Klusmann, U. (2026). How strongly is teachers’ burnout related to teacher absenteeism, teacher–student interactions, and student motivation and achievement: A meta-analysis and systematic review. Review of Educational Research, 00346543261455273.

https://doi.org/10.3102/00346543261455273… Read the rest

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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

Categories
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

Categories
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

Categories
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