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صفحه اصلی
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International Conference on Artificial Intelligence; City, Industry and Health
Explainability as a Learning Tool: Leveraging Transparent AI to Foster Self-Regulated Learning in Smart Education Environments
نویسندگان :
Maryam Nooraei Abadeh
1
Shohreh Ajoudanian
2
1- Department of Computer Engineering, Arvand International Branch, Islamic Azad University, Abadan, Iran.
2- Department of Computer Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
کلمات کلیدی :
Artificial Intelligence،Explainability،Self-Regulated Learning،Smart Education،Transparency
چکیده :
In the evolving landscape of AI-driven education, Explainable Artificial Intelligence (XAI) offers not only transparency and accountability but also untapped potential as a educational resource. The new function of explainability as a learning aid to improve students' self-regulated learning (SRL) inside smart educational settings is investigated in this work. Inspired by ideas of self-directed learning, we provide a conceptual model in which AI-generated explanations help students in designing, monitoring, and assessing their own learning paths. Comprising core standards, system-wide analytics, and personalized explanations, this model enhances learners’ metacognitive skills while addressing ethical challenges like bias and privacy. Empirical data from several learning environments shows better SRL results; students show more autonomy and performance. This model redefines smart education by making artificial intelligence a transparent collaborator, therefore bridging the gap between technological innovation and learner agency and providing a scalable solution for fair, efficient learning environments.
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