Predicting perceived learning effectiveness from generative artificial intelligence in higher education: a hierarchical regression analysis of psychological, behavioral, and cognitive factors.
Aug 2026· Cognitive Processing· 0 citations· 43 references
Medicine
TL;DR
Overall, the findings suggest that students' perceived learning effectiveness from GenAI is associated with psychological readiness, behavioral usage patterns, and perceived cognitive engagement, while contextual control variables exhibit comparatively limited explanatory power.
The results suggest that students’ willingness to engage with GenAI is shaped not only by favorable perceptions but also by confidence in the system’s reliability, integrity, and ethical use, suggesting the need to foster trust and cultivate positive attitudes through transparent policies, ethical guidelines, and targe...
Enrico C. Mendoza, Jose Roberto Del Rosario· International Review of Mana...· 0 citations
The moderation findings demonstrated that coping self-efficacy significantly weakened the negative relationship between student anxiety and academic engagement, highlighting its potential protective role in students’ academic experiences.
Agha Fakhar Imam, Rimsha Arif, Farzana Saeed et al.· Journal of Global Social Tra...· 3 citations
Understanding of AI-supported learning systems is extended by emphasizing the alignment of technical functions with pedagogical processes and learners’ cognitive needs and practical guidance is provided for universities and developers seeking to better align the design and evaluation of AI-based e-learning systems with...
Jia-Yuan Guo, Jiu-Yang Ren, Zhao-Lin Lu et al.· Systems· 0 citations
The findings indicate that teachers' adoption decisions are jointly driven by instrumental value and institutional provisioning, and that generalized technology anxiety is not, in itself, a barrier among teachers who already have practical exposure to GenAI.
The findings suggest that epistemic awareness is associated with students’ perceptions of task functionality, and that task functionality is associated with the reported frequency of artificial intelligence use in higher education.
Ángel Ramón Sabando-García, Darwin Maccoll Primero Llacsaguache-Calle, W. R. Villota-Oyarvide et al.· Frontiers in Education· 0 citations
Examination of education students’ self-efficacy and attitudes influence their trust in AI highlights that students’ trust in AI is shaped by their attitudes and reinforced by their confidence in using it, and is most effective as a supportive tool when paired with critical thinking and responsible use.
