Supporting Reflective AI Use in Education: A Fuzzy-Explainable Model for Identifying Cognitive Risk Profiles

This record corresponds to the accepted manuscript (post-print) of the following journal article:

"Supporting Reflective AI Use in Education: A Fuzzy-Explainable Model for Identifying Cognitive Risk Profiles"

This article proposes an interpretable framework to analyze how users interact with generative AI tools in educational contexts, focusing on cognitive risk and reflective behavior. The approach integrates fuzzy clustering, the Analytic Hierarchy Process (AHP), and Explainable Artificial Intelligence (XAI) techniques to identify distinct user profiles based on AI usage patterns, decision-making strategies, and information verification. The model provides actionable insights to support responsible and critical AI use in education.

The final published version is available at the publisher’s website:
https://doi.org/10.3390/educsci15070923

This deposit is made for open access and dissemination purposes, in accordance with the publisher’s self-archiving policy.