Author: cuspbeib

Categories
Primary School Education Social and Motivational Outcomes

The Effects of Interventions for Promoting Elementary School Students’ Engagement

Goulet and colleagues conducted a systematic review and three-level meta-analysis to examine the effects of different intervention strategies on elementary school students’ engagement and to compare which approaches were most effective in promoting behavioral, affective, and cognitive engagement. Following PRISMA guidelines, the study included 53 studies covering 46 interventions and a total of 38,225 students. Of these interventions, 39 used randomized controlled trials and 7 used quasi-experimental designs. The interventions were classified into three main categories: teacher support, mainly involving teacher professional development; student-directed interventions, which directly targeted students; and multimodal interventions, which simultaneously supported students and their family or school environments. The meta-analysis used a three-level random-effects model with robust variance estimation to account for dependencies among multiple effect sizes within the same study, and methodological bias was further examined as a moderator.

The results showed that interventions had the most consistent positive effect on elementary students’ behavioral engagement, with an overall effect size of g = .386. All three intervention types produced significant effects. Teacher support showed the largest effect (g = .503, 95% CI [.105, .901]), followed by multimodal interventions (g = .385, 95% CI [.202, .569]) and student-directed interventions (g = .370, 95% CI [.198, .542]), although there were no significant differences among the three approaches (F = 0.22, p = .808). Further comparisons among student-directed strategies showed that learning strategy development had the largest effect (g = .801, 95% CI [.318, 1.285]) and was significantly more effective than social-emotional learning (SEL; g = .171, 95% CI [.027, .314]; p = .003). Classroom physical activity also showed a relatively large effect (g = .478), but its confidence interval included zero (95% CI [–.100, 1.056]), indicating that the result was less stable.

Overall, the study indicates that elementary school students’ engagement is malleable, but different dimensions of engagement respond differently to intervention. The strongest evidence currently concerns behavioral engagement. In particular, improving teachers’ instructional and classroom management practices through workshops, coaching, feedback, and reflective activities, as well as directly developing students’ learning strategies such as planning, organization, self-monitoring, and reflection, appear especially promising. In comparison, interventions focusing only on students’ social-emotional skills have more limited effects, while the evidence for physical activity remains uncertain. The authors therefore suggest that schools prioritize investment in teacher professional development and student learning strategy training when designing engagement interventions, while avoiding the assumption that a single approach can improve behavioral, affective, and cognitive engagement equally. Future research should also include more measures of affective and cognitive engagement and adopt higher-quality research designs to build a stronger evidence base.

Source (Open Access): Goulet, J., Archambault, I., Maltais, C., Gilbert-Blanchard, O., & Janosz, M. (2026). Promoting engagement in elementary school: A systematic review and meta-analysis of intervention effects. Educational Psychology Review, 38(1), 107.

https://doi.org/10.1007/s10648-026-10204-w… Read the rest

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Educational Administration and Leadership Higher Education

International student mobility and retention: evidence from discrete choice experiments

A recent quantitative study by Peeters and De Witte investigates the determinants of international students’ university choices and their decisions to remain in the host country after graduation, focusing on the Flemish region of Belgium.

This study draws on 652 usable survey responses from international students at KU Leuven, collected between February 10 and March 19, 2025, after removing 96 Belgian respondents from an initial 748 completed surveys. Roughly 15% of respondents were reached through digital channels and 85% through lecturing moments. The authors conducted two discrete choice experiments (DCEs): Deck 1 on university choice (7,824 choice observations) and Deck 2 on the post-graduation stay decision (11,736 observations), plus an embedded information experiment on perceived English use in Brussels firms.

Variables were operationalized as choice attributes. Deck 1 comprised tuition fee, university ranking, proximity to home, labor prospects, and guaranteed accommodation; Deck 2 comprised gross salary, ease of obtaining a visa or work permit, ease of social integration, employment opportunities, and quality of life. Intention-to-stay was captured through a direct survey question and linked to a visa-requiring dummy and GDP per capita. Data were analyzed using conditional and mixed logit models, willingness-to-pay measures, latent class analysis, and subgroup analysis.

The findings show that tuition fees are the most influential determinant of university choice, with students willing to forgo up to €8,597 in annual fees for a higher-ranked institution (range €4,260 to €8,597, versus €2,989 for many employment opportunities). Easing immigration procedures raised stay probability by 11.62 to 23.99 percentage points, alongside substantial preference heterogeneity across student groups. Students would give up to €761 in gross monthly salary for an easier visa process and €754 for high quality of life. Visa-requiring students had a 9 to 10 percentage-point higher intention to stay, and each €10,000 of home-country GDP per capita lowered it by 1.92 percentage points. Master’s students were 9 to 10.2 percentage points more likely to intend to stay than Bachelor’s students, and students with a student or part-time job were 4.75 to 8.12 percentage points more likely. Latent class analysis found two groups for university choice (55% cost-conscious and 45% career-oriented) and two for staying (52% quality-of-life seekers and 33% instrumental optimizers). Fast-track visas for skilled graduates were estimated to yield €27.7 to €83.0 million a year for the Flemish economy, and better labour market conditions €40.4 to €172.7 million. This study offers actionable insights for policymakers seeking to attract and retain international talent.

Source: Peeters, E., & De Witte, K. (2026). International student mobility and retention: evidence from discrete choice experiments. Studies in Higher Education, 1-18.

https://doi.org/10.1080/03075079.2026.2692621… Read the rest

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Effective Teaching Approach Secondary School Education

When AR Makes Learning Enjoyable but Not Necessarily More Effective

Olea-Ibarra et al. (2025) examine how augmented reality (AR) affects middle school students’ enjoyment, epistemic emotions, and knowledge acquisition in science learning. Although AR is often promoted as an immersive tool that can make abstract content more engaging, the study addresses an important unresolved issue: whether greater enjoyment and emotional stimulation during AR learning actually translate into stronger learning outcomes, especially for younger learners. The study focuses on seventh-grade students learning about the solar system and compares AR-based learning with a non-immersive static multimedia condition.

Using a quasi-experimental field design, the study involved 47 seventh-grade students from an international middle school in Mexico. Students were assigned to either an AR condition or a control condition by class group. In the AR condition, students used the Jigspace app on tablets to spatially explore solar system content, including planets’ positions and characteristics. In the control condition, students learned the same content through an interactive PowerPoint presentation with static images and text on tablets. Knowledge was assessed through pre- and post-tests, while enjoyment and epistemic emotions were measured repeatedly before, during, and after the learning activity.

Results show a mixed and somewhat counterintuitive pattern. Students in the AR condition reported significantly higher enjoyment than those in the control condition. The averaged enjoyment scores during and after learning were higher in the AR group (M = 3.86, SD = 0.84) than in the control group (M = 2.84, SD = 0.66), with a large effect size (d = 1.37). AR also elicited stronger positive epistemic emotions, including surprise (d = 1.09), curiosity (d = 1.05), and excitement (d = 1.07). However, the control group achieved greater knowledge gains than the AR group. Knowledge gain was substantially higher in the control condition (M = 12.20%, SD = 6.90) than in the AR condition (M = 4.66%, SD = 6.41), with a large effect size (d = 1.13). A repeated measures ANOVA further showed a significant interaction between condition and measurement time, indicating that knowledge gain reached statistical significance only in the control condition, F (1,45) = 15.049, p < .001. The mediation analysis also indicated that enjoyment did not significantly mediate the relationship between AR use and learning gains (b = 1.857, SE = 1.356, p = .171). These findings suggest that while AR can make learning more emotionally engaging, this affective advantage does not automatically lead to better knowledge acquisition.

Overall, the study provides a valuable cautionary perspective on immersive technologies in school science learning. AR may enhance enjoyment and stimulate positive epistemic emotions, but it may also distract learners or create affective overload when emotional engagement competes with task-focused cognitive processing. The findings highlight the need to design AR learning environments that carefully balance immersion, emotion, and instructional focus. Rather than assuming that more engaging media will automatically improve learning, the study suggests that educators should use AR with clear pedagogical guidance, especially when working with younger learners.

Source (Open Access): Olea‐Ibarra, D., Hartmann, C., & Bannert, M. (2025). The role of enjoyment and epistemic emotions in middle school AR learning: A quasi‐experimental field study. Journal of Computer Assisted Learning, 41(2), e70016.

https://doi.org/10.1111/jcal.70016… Read the rest

Categories
Higher Education Social and Motivational Outcomes

Unveiling the hidden key: can help-seeking behaviors bridge the gap between doctoral supervision relationship and research self-efficacy of PhD candidates?

A recent cross-sectional study by Jeanne Boisselier examines the relationship between the Doctoral Supervision Relationship (DSR) and Research Self-Efficacy (RSE) among PhD candidates, with a particular focus on the mediating role of Help-seeking behaviors. Specifically, the study investigates whether adaptive and non-adaptive help-seeking act as mechanisms that bridge the gap between supervisory support and students’ confidence in their research abilities. The sample comprised 178 PhD candidates enrolled in French universities and research institutes.

The authors employed ANOVAs, linear regressions, and mediation analyses to examine the associations among the study variables. Key constructs were measured using multi-dimensional 5-point Likert scales. The DSR was assessed across five dimensions: Autonomy Support, Competence Support, Relatedness Support, Communication Quality, and Supervisor Involvement. Help-seeking behaviors were categorized as Adaptive Help-seeking, reflecting proactive strategies to gain mastery, and Non-adaptive Help-seeking, reflecting avoidance of support due to perceived threats to self-esteem. Research Self-Efficacy was operationalized as students’ subjective belief in their ability to perform research-related tasks and processes successfully.

Results indicate that all five dimensions of the DSR significantly and positively predict RSE: autonomy support (β = .20, p < .01), competence support (β = .27, p < .01), relatedness support (β = .29, p < .01), communication quality (β = .31, p < .01), and supervisor involvement (β = .28, p < .01). Mediation analyses reveal that Adaptive Help-seeking partially mediates the relationship between DSR and RSE and fully mediates the effect of Autonomy Support. In contrast, Non-adaptive Help-seeking functions as a negative mediator: effective supervision reduces avoidant behaviors, thereby preventing a decline in research confidence. Despite the significance of these behavioral pathways, the direct influence of supervisory support on RSE remains stronger, emphasizing the primary importance of the quality of the supervision relationship itself.

The findings highlight the need for supervisors and institutions to attend to the multifaceted nature of doctoral guidance, particularly by enhancing communication quality and autonomy support to encourage adaptive help-seeking among students.

Source (Open Access): Boisselier, J. (2026). Unveiling the hidden key: can help-seeking behaviors bridge the gap between doctoral supervision relationship and research self-efficacy of PhD candidates? Higher Education Research & Development, 45(1), 33-48.

https://doi.org/10.1080/07294360.2025.2526816… Read the rest

Categories
Effective Teaching Approach Higher Education

Supporting self-regulated learning through generative AI feedback in online higher education

A recent mixed-methods study by Yilmaz and colleagues examined whether feedback generated by artificial intelligence can help university students develop self-regulated learning skills (SRLs) in an online course, and how students’ perceptions of the feedback source shape their attitudes. The study was conducted within a nine-week distance-learning “Basic Statistics” module and involved 46 higher education students who were randomly and blindly assigned to either a GenAI feedback group (n = 23) or a tutor feedback group (n = 23), with participants unaware of which type of feedback they were receiving during the intervention itself.

The researchers drew on Nazaretsky and colleagues’ (2024) four-dimension feedback perception framework, covering objectivity, usefulness, genuineness, and provider credibility, together with Barnard and colleagues’ (2009) six-dimension SRL model, comprising goal setting, task strategies, environment structuring, time management, help-seeking, and self-evaluation. SRL was measured using trace-based indicators adapted from Ye and Pennisi’s (2022) framework, derived from roughly 48,000 MOODLE log records that were mined, standardised, and mapped onto SRL proxy scores before and after two feedback interventions. GenAI feedback was produced using GPT-4 through structured prompts fed with each student’s individual proxy z-scores, while tutor feedback was generated using a purpose-built support tool named RefleXED, based on the same underlying data.

The results showed that students rated GenAI-generated feedback more favourably than tutor-generated feedback across every perception dimension, with a statistically significant advantage found specifically for Genuineness (p = .036, r = .36). In terms of SRL development, the GenAI feedback group demonstrated a significant improvement in the Task Strategies dimension (p = .044, r = .35), and a near-significant trend emerged for Time Management (p = .057, r = .33), while no significant between-group differences were found for the remaining SRL dimensions. Qualitative analysis of open-ended responses from 17 treatment-group students revealed considerable variation in awareness of the feedback source: students who recognised the feedback as AI-generated generally reported no change in attitude, prioritising content quality over provenance, whereas a smaller number of unaware students indicated their views might have shifted had they known the source in advance.

The findings suggest that carefully designed, learning-analytics-informed GenAI feedback holds real potential to scale personalised support for self-regulation in online higher education, but the researchers caution against viewing GenAI as a replacement for tutors. Instead, they argue for a complementary model in which GenAI’s scalability and adaptability work alongside tutors’ pedagogical judgement, while institutions remain attentive to how students’ awareness and perceptions of the feedback source can influence its ultimate impact. The authors note that the modest sample size (n = 46) drawn from a single course limits generalisability, and they call for future research involving larger, more diverse cohorts, no-feedback control conditions, and longer-term tracking of SRL outcomes.

Source (Open Access): Yilmaz, M., Temur, H. B., Emmungil, L., Çelik, E., Gauthier, A., & Cukurova, M. (2026). Supporting self-regulated learning through generative AI feedback in online higher education: the importance of student perceptions of the source of feedback. International Journal of Educational Technology in Higher Education, 23(1), 16.

https://doi.org/10.1186/s41239-026-00592-y… Read the rest

Categories
Higher Education Programme Evaluation

Unequal Access, Equal Outcomes? Gender Differences in University-Led STEM Programs

Guo et al. (2025) investigate whether university-led STEM programs function as gender equalizers in shaping undergraduates’ career commitment in STEM. Grounded in Social Cognitive Career Theory, the study examines how four program factors (i.e., course resources, research opportunities, mentoring quality, and peer interactions) relate to students’ STEM career commitment, and whether these relationships differ by gender through the mediating roles of STEM professional self-efficacy and perceptions of STEM professionals. Data were drawn from a nationwide survey of 19,108 undergraduates from 39 leading Chinese universities participating in the Strong Foundation Program, a large-scale initiative designed to cultivate elite STEM talent.

Using t-tests, regression analyses, and multi-group structural equation modeling, the authors compared gender differences among both program participants and non-participants. Results show that although men reported higher overall STEM career commitment in the full sample, this gender gap disappeared among students enrolled in the university-led STEM program. Women participants even reported more favorable experiences in course resources, research opportunities, and mentoring quality, whereas men reported stronger peer interactions. These findings suggest that structured university programs may substantially reduce gender disparities in STEM career commitment.

Regression results further indicate that all four program factors positively predicted STEM career commitment. Course resources and research opportunities were particularly influential for women students, while peer interactions exerted a stronger effect for men students. Mentoring quality showed comparable effects across genders. These patterns highlight gender-differentiated sensitivities to specific institutional supports within STEM programs.

Multi-group mediation analyses revealed distinct gender-specific pathways. For women students, course resources and research opportunities enhanced STEM career commitment primarily through STEM professional self-efficacy and positive perceptions of STEM professionals. In contrast, men students’ career commitment was shaped more strongly by peer interactions via perceptions of STEM professionals. Mentoring quality demonstrated similar indirect effects for both groups. Together, these findings underscore that equal access does not imply identical developmental mechanisms.

Overall, the study demonstrates that thoughtfully structured university-led STEM programs can act as effective gender equalizers in career commitment outcomes, even when women remain numerically under-represented in participation. By revealing gender-specific psychological and contextual pathways, the research extends Social Cognitive Career Theory and provides important implications for designing targeted STEM policies and support systems in higher education.

Source (Open Access): Guo, C., Wu, W., Hu, T., & Gao, T. (2025). Unequal access, equal outcomes? Gender differences in the relationship between university-led STEM program factors and undergraduates’ career commitment in STEM. International Journal of STEM Education, 12(1), 46.

https://doi.org/10.1186/s40594-025-00569-9… Read the rest