Between perceived competence and artificial intelligence: academic self-efficacy profiles in university students with motor disabilities

Abstract

Academic self-efficacy is a key factor in understanding how students manage university demands. From the perspective of social sustainability and educational inclusion, analyzing its relationship with artificial intelligence (AI) can clarify differences in the adoption and use of technologies capable of supporting student autonomy and academic participation among groups facing higher education barriers. The objective of this study was to identify academic self-efficacy profiles based on the dimensions of Attention, Communication, and Excellence, as well as to examine their relationship with the use of AI as an educational, informational, and emotional support system among university students with motor disabilities. A quantitative, cross-sectional study was conducted using convenience sampling and an institutional online questionnaire between January and March 2026 at universities in Alicante, Spain. The sample consisted of 102 higher education students with motor disabilities, aged between 18 and 33 years. An online questionnaire was administered to evaluate academic self-efficacy and the use of AI tools. Latent Profile Analysis (LPA) was used to identify distinct academic self-efficacy profiles, and Structural Equation Modeling (SEM) was conducted to examine the associations between self-efficacy dimensions and AI use. Three academic self-efficacy profiles were identified: low, moderate, and high. The dimensions of academic self-efficacy showed positive associations with AI use, with Excellence showing the strongest association, followed by Communication and Attention. The findings indicate that higher levels of academic self-efficacy were associated with greater use of AI tools. Academic self-efficacy and AI use were positively associated among university students with motor disabilities. These findings highlight the relevance of considering academic self-efficacy and the responsible and accessible integration of AI when developing inclusive academic support strategies aimed at fostering student autonomy and participation.