From Intelligent Tutoring to Generative AI: Rethinking Teaching and Learning in the Age of AI

Elena Adina Bîrsan

doi:10.63734/JNFDE.02.01.006

Authors

Elena Adina Bîrsan “Virgil Madgearu” Economic High School, Galați, Romania Author

DOI:

https://doi.org/10.63734/JNFDE.02.01.006

Keywords:

Artificial intelligence, Intelligent tutoring systems, Generative AI, Pedagogy, AI literacy

Abstract

Artificial intelligence (AI) has been used in education for several decades, but the public emergence of generative tools has prompted a reconsideration of how teaching and learning are organised. This paper traces the evolution of AI in education from early intelligent tutoring systems to contemporary generative models, and examines what this shift means for the roles of teachers and learners. The study is a narrative and critical review of peer-reviewed literature, foundational scholarship and policy guidance published mainly between 2011 and 2024, identified through academic databases and synthesised thematically around technological generations, capabilities and pedagogical implications. Three broad generations are identified: rule-based intelligent tutoring systems, which were narrow but reliable and pedagogically grounded; data-driven and adaptive systems, which scaled personalisation; and generative models, which are broad, open-ended and widely accessible but variable in accuracy. The transition expands what AI can do while shifting responsibility for judgement back towards teachers and learners. Recurring concerns include reliability, academic integrity, equity and the need for AI literacy. Rather than rendering teachers obsolete, the move from intelligent tutoring to generative AI makes their pedagogical role more important. The constructive path lies in combining the reach of generative tools with the rigour of earlier approaches, supported by AI literacy, redesigned assessment and a human-centred stance.

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