This study examines how ChatGPT-generated writing feedback relates to Saudi EFL learners’ perceived assessment performance among those who already use ChatGPT, and how this relationship is associated with indirect statistical pathways involving evaluative and motivational factors. Drawing on the Feedback Engagement Framework and Self-Regulated Learning Theory, a structural model was specified to account for relationships among ChatGPT use, perceived feedback quality, writing confidence and motivation, perceived improvement in writing skills, and perceived assessment performance. Data were collected from 662 undergraduate learners who reported prior use of ChatGPT and analysed using structural equation modelling. The results indicate that ChatGPT use does not directly predict perceived assessment performance. Instead, its association with perceived assessment performance was indirect, through statistical pathways involving perceived feedback quality, confidence and motivation, and perceived improvement in writing skills. Perceived feedback quality was strongly associated with both motivational responses and perceived improvement in writing skills. Academic level moderated the relationship between feedback quality and perceived improvement in writing skills, whereas gender did not. The findings indicate that learners’ evaluations of AI-generated feedback are associated with their perceptions of improvements in writing skills and assessment performance, rather than with objectively measured learning outcomes.
Team-Based Learning (TBL) is widely used in medical and health-professions education, but post-COVID Hybrid-Flexible (HyFlex) delivery can challenge features on which TBL depends. This critical narrative review synthesized 289 publications from 2019 to 2026 across four domains: educational outcomes; learner experience and equity; feasibility and implementation fidelity; and the comparative or complementary roles of TBL, case-based learning (CBL), and flipped learning. TBL was generally associated with favorable or equivalent immediate knowledge outcomes, while evidence for delayed retention, clinical reasoning, communication, transfer, equity, and resource use was less consistent. Learner satisfaction and engagement were often positive but varied with preparation burden, team dynamics, facilitation, and delivery format. Single-mode synchronous online TBL can preserve key processes when learners share one digital environment, but direct evidence for concurrent HyFlex TBL remains sparse. HyFlex delivery introduces dual-audience facilitation, audiovisual barriers, unequal visibility, coordination delays, and additional workload that may weaken team stability, 4S fidelity, feedback, and debriefing. Conceptually, TBL and CBL are active-learning approaches, flipped learning is an instructional architecture, and HyFlex is a delivery format. TBL remains valuable when fidelity and participation equity can be protected.
Reading-to-write tasks require EFL learners to comprehend and integrate academic source material into original texts. This longitudinal mixed-methods study examined whether AI-generated, level-aligned input during preparation supported performance among 134 undergraduates in two intact academic writing sections at a Jordanian university. Sections received either AI-mediated input or instructor-scaffolded preparation; AI was prohibited during assessed writing. Performance at three time points was analyzed using repeated-measures ANOVA, alongside reflections, think-aloud protocols, and interviews. Both groups improved, but the AI group gained more, especially in content integration (Group × Time: partial η² = .177; posttest d = 1.58). Learners described benefits for comprehension, synthesis, and planning. However, section-level allocation and potentially unequal synthesis support limit causal inference. The findings position AI as a constrained pre-writing input mediator rather than a drafting tool.
Performance-based assessment is central to engineering education, but fairness may be threatened by rater subjectivity and task variability. This study examined a multi-task assessment using the Many-Faceted Rasch Model (MFRM). Eight faculty raters scored 468 performances from 156 undergraduate engineering students across three tasks, generating 3,744 ratings using a five-criterion rubric. MFRM jointly estimated student ability, task difficulty, rater severity, and criterion difficulty on a common logit scale. Global and facet-level fit were acceptable. Student ability showed good separation (3.45) and reliability (0.92). Male–female differences were small and non-significant (0.21 logits; t(154) = 1.18, p = .240; d = 0.19), although the 95% confidence interval (−0.14 to 0.56) was too wide to establish practical equivalence. Laboratory Experiment was the most difficult task, while Technical Presentation was the least difficult. Rater severity varied by 2.14 logits (separation = 5.82; reliability = 0.97), indicating systematic differences in scoring stringency. Bias also emerged in Rater × Task and Rater × Criterion interactions. The five-category scale functioned adequately, with ordered thresholds. Despite acceptable measurement quality, rater severity and interaction effects remain potential fairness risks. MFRM offers a framework for auditing and strengthening the transparency, equity, and defensibility of engineering performance assessment.
While gamification has been associated with increased engagement in technology-enhanced learning, limited evidence exists regarding its relationship with students’ psychological safety, confidence, and inclusion in face-to-face, language-rich classrooms. This study examined Grade 9 students’ perceptions of ClassPoint-supported gamification in Arabic and Islamic Studies classrooms in the United Arab Emirates. Using a quantitative, cross-sectional survey design, data were collected from 575 students across three domains: engagement and motivation, confidence and psychological safety, and inclusion and equitable participation. Descriptive statistics, Spearman’s rank-order correlations, and the Friedman test were employed. Findings revealed predominantly positive perceptions of engagement and motivation, followed by confidence and psychological safety, while inclusion and equitable participation received comparatively less favorable ratings. Strong positive associations emerged between engagement and confidence, alongside moderate to strong associations involving inclusion. The Friedman test identified statistically significant differences across the three domains. These findings suggest that gamified classroom interaction may support student participation and confidence, although positive engagement does not necessarily ensure equitable inclusion. The study highlights the importance of teacher-mediated gamification design in creating supportive, participatory learning environments and emphasizes the need to examine psychological safety and student voice alongside engagement.
