Application of adaptive artificial intelligence for personalizing learning paths in e-learning

Mohammed Salihoun, Abdelali Elmounadi

Abstract


The field of education and online education in particular, has undergone radical change thanks to digital transformation. The integration of adaptive artificial intelligence (AI) into the latter has given a further significant evolution, enabling the online personalization of learning paths. The result is clearly effective, engaging and specific education for every student. This article analyzes how adaptive AI can improve e-learning, with a specific accentuation on algorithms and tools—such as machine learning and deep learning that enable this level of customization. Technical and ethical challenges will be discussed, as we go over their benefits, precisely with regard to improving learning outcomes and promoting student involvement and engagement. Additionally, the paper examines the potential applications of adaptive AI in online learning, stressing the anticipated advancements and the significance of a thoughtful strategy that considers moral and legal concerns. The paper highlights the ways in which adaptive AI can revolutionize distance learning and stimulates critical thought about the implications of its broad implementation.

Keywords


Adaptive e-learning; Artificial intelligence in education; Deep learning; Intelligent tutoring systems; Learning personalization; Machine learning

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DOI: http://doi.org/10.11591/ijai.v15.i5.pp4992-5000

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Copyright (c) 2026 Mohammed Salihoun, Abdelali Elmounadi

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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES).

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