Computers & Education最新文献

{"title":"Navigating learning disruptions: The role of digital learning platforms in student motivation, feedback and emotion","authors":"Negar Monazam-Tabrizi ,&nbsp;Yusuf Kurt ,&nbsp;William il-Kuk Kang","doi":"10.1016/j.compedu.2025.105534","DOIUrl":"10.1016/j.compedu.2025.105534","url":null,"abstract":"<div><div>Crises such as pandemics disrupt the motivational, feedback, and emotional processes that sustain effective learning. Digital learning platforms (DLPs) are often positioned as tools to maintain educational continuity, yet their associations with effective learning in disrupted contexts remains insufficiently understood. This study examines whether DLP use moderates the relationships between low motivation, insufficient feedback, negative emotions, and students' effective learning during crisis-driven remote education. Using a mixed-methods design, quantitative data from 216 UK university students were analysed using partial least squares structural equation modelling (PLS-SEM), and qualitative insights derived from open-ended questionnaire responses were analysed using thematic analysis. Findings indicate that diminished motivation, inadequate feedback, and negative emotions are negatively associated with learning effectiveness during crises. While DLP use was positively associated with effective learning, it did not significantly moderate the relationships between low motivation, insufficient feedback, negative emotions, and students’ effective learning. Qualitative insights suggest that more favourable learner experiences occur when technological affordances are aligned with instructional design, instructor presence and emotional support. The study points to the value of incorporating motivation-enhancing strategies, personalised feedback and affective support within digital learning environments. It contributes to digital pedagogy by highlighting that DLPs relate more strongly to effective learning when their features are integrated with coherent pedagogical design, meaningful social interaction and emotionally supportive practices. These insights extend beyond crisis contexts and offer guidance for designing resilient, inclusive, and human-centred digital learning systems.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"246 ","pages":"Article 105534"},"PeriodicalIF":10.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comparative study of expert, AI, and no external feedback on mathematics teacher learning outcomes in reflective practice","authors":"Yimin Ning ,&nbsp;Wee Tiong Seah ,&nbsp;Jihe Chen ,&nbsp;Jinhai Liu ,&nbsp;Peifen Tan","doi":"10.1016/j.compedu.2026.105572","DOIUrl":"10.1016/j.compedu.2026.105572","url":null,"abstract":"<div><div>Feedback is crucial for teacher professional development, yet most studies focus on a single source (e.g., experts or peers). Longitudinal comparisons across sources and analyses of underlying mechanisms are rare. This study therefore investigates how different feedback sources influence teacher learning outcomes. A total of 522 teachers participated in a 13-week professional learning program, including three weeks of reflective practice. Participants were divided into three groups: NF (no external feedback), EF (expert feedback), and AF (AI feedback). Teaching videos, instructional design artifacts, and reflective journals were analyzed to assess outcomes. Teachers in the EF group achieved significantly higher learning outcomes than those in the AF group, who, in turn, outperformed the NF group. These findings underscore the distinctive value of expert feedback in providing depth of insight and contextual sensitivity, while also indicating that AI feedback, although timely and adaptive, cannot fully replace expert judgment. Cross-Lagged Panel Network (CLPN) analysis identified key behaviors and sequences across groups and revealed detailed temporal patterns within behavioral clusters. Qualitative interviews further demonstrated that feedback effectiveness is shaped by the interaction of three dimensions—Time, Object, and Level (TOL)—which form the basis of a framework with 16 elements. The study highlights the complementary strengths of AI adaptability and expert insight, suggesting that multi-source feedback enhances teacher professional development by integrating process support with higher-order regulation.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"246 ","pages":"Article 105572"},"PeriodicalIF":10.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145962558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal effects of learning analytics support for study planning and monitoring: Role of self-efficacy and data literacy","authors":"Anceli Kaveri ,&nbsp;Ismail Celik ,&nbsp;Egle Gedrimiene ,&nbsp;Anni Silvola ,&nbsp;Hanni Muukkonen","doi":"10.1016/j.compedu.2025.105532","DOIUrl":"10.1016/j.compedu.2025.105532","url":null,"abstract":"<div><div>Learning analytics (LA) can be an effective support for self-regulation of higher education students. Supporting different students on their academic paths requires considering students' self-efficacy beliefs and data-literacy skills as well as their varying uses and interpretations of LA. In this quasi-experimental study, we collected quantitative survey data on higher education students (N = 105) with and without access to a student-facing LA dashboard designed to support students on an academic path level. We collected data on students' perceived support for study planning and monitoring at three timepoints during one academic year. Utilizing latent growth curve modeling, the study investigated how students with different self-efficacy beliefs and data-literacy skills perceive receiving self-regulation support from LA throughout an academic year compared to peers with only regular digital tools. Our results showed that students with access to the LA dashboard reported a larger increase in perceived support compared to peers with access to only regular digital tools. Students with high data-literacy skills perceived receiving more support from LA compared to peers with low data-literacy. Students' self-efficacy beliefs did not significantly impact the extent of perceived support from LA. The results highlight the ethical risk of complex digital solutions, which, over time, put less technology-savvy students at a greater disadvantage and mainly benefit already higher-skilled students. The results strengthen current understanding on how LA supports higher education students on their academic paths but call for further investigation into ways of fostering students' data-literacy skills to maximize the support and overcome equity concerns.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"246 ","pages":"Article 105532"},"PeriodicalIF":10.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145730840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tracing scientific reasoning as process: A trait-behavior-performance model with learning analytics in simulated environments","authors":"Chia-Mei Lu","doi":"10.1016/j.compedu.2025.105556","DOIUrl":"10.1016/j.compedu.2025.105556","url":null,"abstract":"<div><div>Scientific reasoning in simulation-based learning environments (SBLEs) is a time-structured process, not a terminal outcome. We advance and test a trait → mechanism → behavior model explaining how self-regulated learning (SRL) and critical thinking disposition (CTD) become consequential via a translation layer: dispositions first shape a reasoning-aligned configuration mechanism (SIM; planned contrasts, disciplined retesting), which enables process-level behavior (SIB; semantic precision, revision cadence). Eleventh graders (N = 168) completed a closed-loop aquatic simulation under Guided→Open or Open→Open sequences. Consistent Partial Least Squares for Reflective Constructs(PLSc)estimated reflective blocks; SIB was formative (Mode B). Measurement quality and cross-condition invariance were established; Cluster-Robust Variance Estimator, Type 2 (CR2), and PLSpredict supported stability and utility. Process analytics (K-means profiles; three-state HMM) complemented the SEM. Findings: SRL and CTD had moderate positive effects on SIM; SIM had a vast, robust effect on SIB. Mediation showed trait effects reach behavior primarily through SIM. Format moderation was small/uncertain; temporally, lower-SRL learners dwelled longer in low-efficiency states, and editing cadence marked transitions to efficiency; early scaffolds modestly shortened dwell. Design principles: instrument platforms to monitor SIM/SIB as live control points; route support by profiles; and time-minimal, load-aware prompts to the revision window to restore Control of Variables Strategy (CVS) discipline and semantic alignment. The contribution is a validated, mechanism-aware account that yields diagnostic, feedback-ready, and scalable specifications for precision scaffolding and evaluation in SBLEs.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"246 ","pages":"Article 105556"},"PeriodicalIF":10.5,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145957053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The double-edged sword of technology: Investigating technostress and techno-eustress in academic burnout through digital literacy, internet self-efficacy, and cognitive flexibility","authors":"Mehmet Avcı","doi":"10.1016/j.compedu.2025.105540","DOIUrl":"10.1016/j.compedu.2025.105540","url":null,"abstract":"<div><div>The swift advancement of technology in educational contexts introduces a range of challenges alongside significant benefits. Technostress and techno-eustress have been identified as significant determinants of academic achievement in higher education, influencing students’ well-being, productivity, and levels of burnout. However, there is limited research on how psychological mechanisms play a mediating role in the relationship between technostress, techno-eustress, and academic burnout. To fill this gap, two serial mediation models with three mediators were proposed to explore the associations among technostress, techno-eustress, digital literacy, internet self-efficacy, cognitive flexibility, and academic burnout in a random sample of university students from different education faculties in Türkiye (<em>N</em> = 677). The total effect of technostress on academic burnout was significant. This first model, with an additional three mediators, accounted for 16 % of the explained variance in academic burnout, and then 5 % without mediators. In the second model, the total effect of techno-eustress on academic burnout was nonsignificant (p = 0.602), while the direct effect had a small impact (p = 0.029). However, the total indirect effect of techno-eustress on academic burnout was significant and serially mediated by digital literacy, internet self-efficacy, and cognitive flexibility, accounting for 13 % of the explained variance. Triple serial mediation analyses indicated that digital literacy enhances internet self-efficacy, which in turn improves cognitive flexibility. This sequence ultimately promotes techno-eustress and mitigates technostress, resulting in a reduction of academic burnout. Focusing on these mediators as protective resources against technostress may enhance psychological and behavioral outcomes in higher education students.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"245 ","pages":"Article 105540"},"PeriodicalIF":10.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitigating cognitive biases in higher education contexts through a brief video-based intervention: A randomized controlled trial","authors":"Lemi Baruh ,&nbsp;Zeynep Cemalcilar ,&nbsp;Andy Stoycheff","doi":"10.1016/j.compedu.2025.105535","DOIUrl":"10.1016/j.compedu.2025.105535","url":null,"abstract":"<div><div>Cognitive biases present significant challenges in higher education, yet existing mitigation strategies are often resource-intensive or lack scalability. This study introduces and evaluates a novel, scalable intervention using brief, scenario-based videos to reduce cognitive biases that may influence self-perceptions, relationships, and decision-making in higher education contexts. We conducted a cross-national experiment (N = 1038) with teachers and learners, targeting 21 distinct biases. Participants were randomly assigned to a control or experimental condition. Both groups viewed a video depicting a bias-eliciting scenario; the experimental group was then shown an additional \"debiasing\" segment containing supplemental, context-altering information. Results showed the debiasing videos significantly reduced biased decisions. This effect was substantially stronger for teachers (Cohen's d = 0.51) than for learners (d = 0.11). For students, the intervention was effective only when participants viewed the videos with subtitles in their native language. Teachers, but not learners, also demonstrated a \"transfer\" effect, showing reduced bias in subsequent, unrelated tasks, after receiving the debiasing intervention. These findings indicate that brief, narrative-based micro-interventions are a promising and scalable tool for cognitive bias mitigation. However, their effectiveness is moderated by audience characteristics, like role as a teacher or a student, and the language of delivery, underscoring the need for context-sensitive design and implementation.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"245 ","pages":"Article 105535"},"PeriodicalIF":10.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145784989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differential effects of student and parental mobile phone use on academic procrastination trajectories: Machine learning evidence","authors":"Jiabin Liu ,&nbsp;Ru-De Liu ,&nbsp;Wei Hong ,&nbsp;Jingmin Lin","doi":"10.1016/j.compedu.2025.105551","DOIUrl":"10.1016/j.compedu.2025.105551","url":null,"abstract":"<div><div>Academic procrastination is a prevalent and varies considerably among adolescents. However, little is known about the specific patterns of academic procrastination development and how the family's digital environment influences these developmental patterns. We conducted a three-wave longitudinal survey with 1130 Chinese adolescents (47.10 % males, <em>M</em>_age = 13.59 years, <em>SD</em> = 2.14 at T1) to identify distinct procrastination trajectories and examine how student and parental mobile phone use (MPU) predicts trajectories. The latent class growth analysis revealed four distinct trajectories: high-stable (47.40 %), low-increasing (14.10 %), moderate-stable (22.20 %), and low-stable groups (16.30 %). Machine learning analysis demonstrated that students' mobile phone dependency and escape motivation predicted membership in less adaptive trajectories (i.e., high-stable, moderate-stable, and low-increasing groups). For the specific purposes of MPU, using for seeking life info, online courses learning, and playing games predicted membership in the low-stable group; while chatting with net friends predicted membership in the low-increasing group. Notably, parental phubbing also predicted membership in these less adaptive groups, whereas active parental mediation predicted membership in the low-stable group. These findings provide the first empirical evidence for the heterogeneous development of academic procrastination and highlight the important role of the family digital ecosystem in shaping these trajectories. Practically, the study supports the development of targeted and family-based interventions tailored to specific procrastination patterns.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"245 ","pages":"Article 105551"},"PeriodicalIF":10.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The indirect role of children’s screen time and the moderating role of problematic parental screen use on the relationships between different parental mediation strategies and preschoolers’ developmental outcomes","authors":"Siyu Wu ,&nbsp;Xiaodan Yu ,&nbsp;Wei Wei","doi":"10.1016/j.compedu.2025.105552","DOIUrl":"10.1016/j.compedu.2025.105552","url":null,"abstract":"<div><div>Parents can mitigate screens’ negative effects on school-aged children and adolescents by monitoring their screen use and improving their screen use skills. However, many preschoolers spend more time on screens than recommended. It remains unclear whether parental mediation is associated with preschoolers’ development through children’s screen time, and whether the first part of this pathway is moderated by problematic parental screen use. This analysis utilized parent-reported data collected in June 2019 about 57,827 children aged 4–5 years. Data included children’s developmental outcomes, children’s screen time, parental mediation (restrictive mediation, instructive mediation, and co-use) frequency, problematic parental screen use level, family income, and parental education. A significant negative correlation was found between children’s screen time and developmental outcomes (<em>r</em> = −0.07, 95 % confidence interval (CI) = [−0.08, −0.06]). Children’s screen time mediated the relations between parental mediation strategies and developmental outcomes. Restrictive mediation frequency was positively associated with developmental outcomes through children’s screen time (β = 0.016, 95 % CI = [0.013, 0.018]). Instructive mediation (β = −0.005, 95 % CI = [−0.006, −0.005]) and co-use (β = −0.004, 95 % CI = [−0.005, −0.003]) were indirectly, negatively associated with developmental outcomes through children’s screen time. Problematic parental screen use moderated the relations between parental mediation and children’s screen time. Higher problematic parental screen use strengthened restrictive mediation’s negative (β = −0.023, 95 % CI = [−0.032, −0.011]) and instructive mediation’s positive (β = 0.047, 95 % CI = [0.037, 0.057]) effects. Despite the modest effect sizes, the statistically robust results suggest that population-level adoption of combined parental strategies—reducing problematic parental screen use alongside implementing restrictive mediation—could translate into public health benefits for early childhood development.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"245 ","pages":"Article 105552"},"PeriodicalIF":10.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145845117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing mindset states of Hong Kong secondary students using machine learning in real-world online learning environment","authors":"Elly Cheng Wang,&nbsp;Xin Guan,&nbsp;Xiaolong Chen,&nbsp;Tai Kai Ng","doi":"10.1016/j.compedu.2025.105554","DOIUrl":"10.1016/j.compedu.2025.105554","url":null,"abstract":"<div><div>This study investigates the use of machine learning to detect mindset states — concentration, motivation, perseverance, engagement, and self-initiative among secondary school students in Hong Kong during two real-life online courses. Prior research has explored AI for mindset detection in controlled settings. Addressing real-life challenges such as low data quality, lighting variability, movement, and privacy concerns, this study explores the feasibility of detecting mindset states in a real-life environment with a combination of inputs, including quiz scores, facial expression, and categorized learning behavior logs. Using a Recurrent Neural Network (RNN), we achieved a modest yet significant prediction accuracy, even with a small dataset of approximately one hundred students. In particular, our results demonstrate the potential of logging data as a scalable and privacy-preserving approach for understanding students’ psychological states. We caution that while our results are encouraging, the modest accuracy highlights the need for further optimization before the approach can be reliably applied in real-world educational settings.</div><div>From a pedagogical perspective, our findings suggest that real-time feedback from well-trained AI tool may provide useful information about students’ mindset states which educators can use to create better student-centered adaptive teaching practices that promote personalized learning while addressing ethical considerations such as data privacy and accessibility.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"245 ","pages":"Article 105554"},"PeriodicalIF":10.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145839428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The effects of GAI-enhanced pedagogical agents in the metaverse (GPAiM) on elementary school students’ conceptual understanding and cognitive engagement patterns","authors":"Tinghui Wu ,&nbsp;Xuesong Zhai ,&nbsp;Yanjie Song","doi":"10.1016/j.compedu.2025.105555","DOIUrl":"10.1016/j.compedu.2025.105555","url":null,"abstract":"<div><div>This study examines the effects of generative artificial intelligence (GAI)-enhanced pedagogical agents in the metaverse (GPAiM) on elementary school students' conceptual understanding of traditional festival customs and on the students' cognitive engagement patterns. The participants included 116 students from three intact classes. These classes were randomly assigned to two experimental groups (with 2D-GPAiM and 3D-GPAiM, respectively) and one control group (without GPAiM but with a real-person teacher). All the participants learned in the metaverse, and students in different groups were allowed to interact with 2D-GPAiM, 3D-GPAiM, and the real-person teacher during their learning, respectively. This study was conducted under a three-week AI literacy project with the learning topic of traditional festival customs. The results showed that the experimental groups (both 2D-GPAiM and 3D-GPAiM) had a positive impact on the students' conceptual understanding of traditional festivals, while the control group did not. More importantly, the 2D-GPAiM group showed a significantly positive difference in the participants’ conceptual understanding compared with the control group. In addition, regarding cognitive engagement, the 2D-GPAiM group showed a <em>highly interactive, low-fluctuating, and high-level cognitive engagement</em> pattern; The 3D-GPAiM group demonstrated a <em>highly interactive, highly fluctuating, medium-level cognitive engagement</em> pattern, while the control group exhibited a <em>low-interactive, low-fluctuating, low-level cognitive engagement pattern</em>. These findings provide valuable insights into future GAI-assisted pedagogical designs.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"245 ","pages":"Article 105555"},"PeriodicalIF":10.5,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145882238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}