Ines Di Loreto
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(https://doi.org/10.55612/s-5002-067-001)
Abstract
AI-powered educational technologies promise to enhance personalization, efficiency, and accessibility. However, this paper argues that modern AI-driven learning environments increasingly prioritize seamless automation over cognitive conflict, uncertainty, and disruption, key mechanisms for learning. Drawing on theories of cognitive disequilibrium, prediction error, and systems thinking, we examine how early AI learning systems embraced productive struggle, while contemporary adaptive platforms focus on minimizing errors and optimizing user experience. Finally, we explore the role of Human-Computer Interaction (HCI) in shaping AI’s educational future, advocating for intentional disruptions that foster engagement and conceptual change.
Keywords: Artificial Intelligence in Education (AIEd), Learning Theories, Human-Computer Interaction, Disruptive Learning, AI and Pedagogy
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