AI self-efficacy as a predictor of satisfaction with studies: the mediating role of research motivation among Peruvian University students

A study conducted among Peruvian university students investigated the psychological mechanisms linking Artificial Intelligence (AI) self-efficacy to satisfaction with studies. It found that research motivation plays a mediating role in this relationship, suggesting that students' confidence in their AI abilities positively influences their motivation for research, which in turn contributes to their overall satisfaction with their academic pursuits.

Why it matters

This research provides insights into the psychological factors influencing student satisfaction in higher education, specifically highlighting the role of AI self-efficacy and research motivation. Understanding these dynamics can inform strategic initiatives aimed at enhancing educational outcomes and student engagement in an increasingly AI-driven academic landscape.

Key insights

• AI is increasingly impacting higher education, influencing learning experiences, motivation, and student satisfaction.
• Limited evidence exists on how AI-related competencies psychologically contribute to academic well-being, especially in Latin American universities.
• The study examined the mediating role of research motivation between AI self-efficacy and satisfaction with studies.
• A quantitative, cross-sectional, and explanatory design was used with 559 Peruvian university students.
• Participants completed validated instruments assessing AI self-efficacy, research motivation, and satisfaction with studies.
• The study indicates that AI self-efficacy predicts satisfaction with studies, with research motivation acting as a mediator.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1897704