Tallennettuna:
Bibliografiset tiedot
Päätekijä: Marín Díaz, Gabriel
Aineistotyyppi: Recurso digital
Kieli:englanti
Julkaistu: Zenodo 2025
Aiheet:
Linkit:https://doi.org/10.3390/educsci15070923
Tagit: Lisää tagi
Ei tageja, Lisää ensimmäinen tagi!
_version_ 1866901181832364032
author Marín Díaz, Gabriel
author_facet Marín Díaz, Gabriel
contents <p>This record corresponds to the accepted manuscript (post-print) of the following journal article:</p> <blockquote> <p><strong>"Supporting Reflective AI Use in Education: A Fuzzy-Explainable Model for Identifying Cognitive Risk Profiles"</strong></p> </blockquote> <p>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.</p> <p>The final published version is available at the publisher’s website:<br><a href="https://doi.org/10.3390/educsci15070923">https://doi.org/10.3390/educsci15070923</a></p> <p>This deposit is made for open access and dissemination purposes, in accordance with the publisher’s self-archiving policy.</p>
format Recurso digital
id zenodo_https___doi_org_10_3390_educsci15070923
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Supporting Reflective AI Use in Education: A Fuzzy-Explainable Model for Identifying Cognitive Risk Profiles
Marín Díaz, Gabriel
Generative AI
Machine Learning
Explainable AI
Critical Thinking
Fuzzy Logic
AHP
Educational Technology/education
Artificial Intelligence
<p>This record corresponds to the accepted manuscript (post-print) of the following journal article:</p> <blockquote> <p><strong>"Supporting Reflective AI Use in Education: A Fuzzy-Explainable Model for Identifying Cognitive Risk Profiles"</strong></p> </blockquote> <p>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.</p> <p>The final published version is available at the publisher’s website:<br><a href="https://doi.org/10.3390/educsci15070923">https://doi.org/10.3390/educsci15070923</a></p> <p>This deposit is made for open access and dissemination purposes, in accordance with the publisher’s self-archiving policy.</p>
title Supporting Reflective AI Use in Education: A Fuzzy-Explainable Model for Identifying Cognitive Risk Profiles
topic Generative AI
Machine Learning
Explainable AI
Critical Thinking
Fuzzy Logic
AHP
Educational Technology/education
Artificial Intelligence
url https://doi.org/10.3390/educsci15070923