Educational Artificial Intelligence and Intelligent Tutoring Systems: Foundations, Evolution, and Contributions to Adaptive Learning

Abstract

This article provides an in-depth analysis of Artificial Intelligence in Education (AIED) and Intelligent Tutoring Systems (ITS), highlighting their theoretical foundations, historical evolution, and contributions to the design of adaptive learning environments. Through a critical review of the scientific literature, the study demonstrates the ability of these technologies to model learners, personalize learning pathways, and enhance the quality of pedagogical feedback. The analysis also reveals a growing convergence between AIED and ITS, particularly with the rise of generative artificial intelligence, which is transforming modes of interaction and opening new perspectives for individualized learning. However, the study also identifies major challenges related to algorithmic bias, data privacy, and the risk of dehumanizing educational practices. These findings call for a rethinking of the integration of these technologies from an ethical, inclusive, and human-centered perspective. Thus, AIED and ITS appear to be promising levers for the renewal of educational practices, provided that they are designed and implemented responsibly.