With the proliferation of generative artificial intelligence (AI) tools, a growing body of research reports negative associations between the use of these technologies and students’ critical thinking. However, the psychological pathways that may account for this association remain insufficiently understood. This study examines the relationship between university students’ generative AI use and their critical thinking in AI-usage contexts, and tests whether the perception of automation bias and cognitive offloading statistically mediate this relationship. A cross-sectional survey was administered to 526 undergraduate students recruited from three universities in western Türkiye. Generative AI usage intensity and critical thinking in AI usage were measured with previously published instruments; the automation bias perception and cognitive offloading measures were developed for this study across two independent pilot samples, and their psychometric properties are reported in detail. Structural equation modeling indicated that generative AI usage intensity was negatively associated with critical thinking in AI contexts, with a total effect (β = − 0.40, p < .001) and a substantially smaller direct effect (β = − 0.12, p = .014). Indirect paths accounted for a considerable portion of the total association through automation bias perception (β = − 0.15, p < .01) and cognitive offloading (β = − 0.13, p < .01). The model accounted for 50
In this study, we examine rich clubs—tightly connected groups of highly active participants—in online discussion boards. Using a combination of social network and discourse analysis, we analyzed social and cognitive engagement patterns in five undergraduate courses. Based on the analysis of approximately 3000 posts, we found that rich clubs form even in small-scale networks, with rich club members exhibiting high levels of interaction. However, discourse analyses revealed only marginal differences in the quality of discourse between rich club and non-rich club members. Based on our findings, we suggest that rich clubs may indicate bottlenecks to information flow, and we suggest ways to foster participatory discussion boards by integrating designed prompts that encourage early posting and scaffolded participation. We also suggest further exploration of rich club discourse using a connected, interactive stance.
The expansion of online higher education has generated increasing demand for effective strategies to support faculty professional development. Among these, peer mentoring mediated through structured class observation and rubric-based evaluation has emerged as a promising practice to enhance teaching quality in virtual learning environments. This study examines the impact of a formative peer mentoring program with assigned roles implemented at an online university in Spain. A pre-experimental pretest-posttest design was applied with a sample of 90 faculty members from the School of Education. Each participant was observed by an expert mentor through the analysis of recorded synchronous online classes, using a sequential rubric designed to evaluate five key dimensions of online teaching: pedagogical design, communication, on-screen presence, instructional design and facilitation. Descriptive statistics, Wilcoxon signed-rank tests, and qualitative coding of observations were conducted. Results showed statistically significant improvements across all evaluated dimensions, with particularly strong effects in Learning Facilitation (r = 0.891) and Communication (r = 0.820). The qualitative analysis revealed a notable reduction in corrections associated with pedagogical weaknesses, as well as increased pedagogical awareness and the adoption of more effective teaching strategies. Structured mentoring supported by professional feedback demonstrates high potential to enhance pedagogical practice in virtual environments. This study provides empirical evidence of its positive impact on faculty development and offers an institutionally feasible approach to fostering a culture of continuous improvement, engagement, and evidence-informed reflection.
Generative AI is increasingly positioned not only as a tool for accelerating production but also as a collaborator that reshapes how individuals regulate cognition, enact innovation, and negotiate creative integrity. This study developed a dual-mediation framework to explain how AI-assisted tool use, hereafter referred to as AI engagement, is associated with higher-order competencies. Drawing on Social Cognitive Theory, we conceptualized self-regulated learning (SRL) and innovative behavior (IB) as behavioral pathways linking AI-assisted tool use to critical thinking (CT) and creative integrity (CI). Survey data from undergraduate students in design-related higher education were analyzed using partial least squares structural equation modeling (PLS-SEM). The results showed that AI-assisted tool use was positively associated with SRL and IB, which were in turn associated with CT and CI. Significant indirect effects further indicated that reflective regulation and purposeful innovation served as important mechanisms through which AI-assisted engagement was linked to higher-order growth. A complementary qualitative phase illustrated how learners framed AI as a “cognitive partner” for idea clarification, iteratively repurposed AI-generated outputs for innovation, and grappled with questions of authorship and attribution. By integrating quantitative modeling with qualitative insights, the study reframes AI not merely as a productivity booster but as a catalyst for reflective, innovative, and ethically attuned practices in AI-mediated design contexts. These findings provide context-specific evidence for understanding human–AI collaboration and offer practical directions for embedding responsibility and criticality in AI-mediated learning environments, while advancing a process-oriented account of how learners translate AI-assisted engagement into cognitive and ethical development.
Gamification is a design strategy that can support higher education students’ autonomous motivation by targeting the basic psychological needs. Yet, to date, the field lacks a comprehensive overview of how this can be achieved. The present scoping review aimed to uncover gamification design strategies that influence higher education students’ basic psychological need support. Following a hybrid search strategy, 20 studies were identified based on 897 entries in Scopus and subsequent backward and forward snowballing. The studies had designed gamification to support higher education students’ basic psychological needs and provided a rationale for how the needs were affected by the intervention. By conducting a basic content analysis, we identified four educational gamification design strategies to support autonomy, three to support competence, and two to support relatedness. The overall results highlight the importance of considering how individual game elements are designed and integrated into learning contexts and understanding how gamification design strategies concurrently affect different students and basic psychological needs.
