JUCS - Journal of Universal Computer Science 29(10): 1161-1198, doi: 10.3897/jucs.90528
AI-Based Adaptive Learning: A Systematic Mapping of the Literature
expand article infoAymane Ezzaim‡, Aziz Dahbi‡, Abdelfatteh Haidine‡, Abdelhak Aqqal‡
‡ Chouaib Doukkali University, El Jadida, Morocco

Corresponding author: Aymane Ezzaim ( aymazzaim@gmail.com )

© Aymane Ezzaim, Aziz Dahbi, Abdelfatteh Haidine, Abdelhak Aqqal.
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Citation: Ezzaim A, Dahbi A, Haidine A, Aqqal A (2023) AI-Based Adaptive Learning: A Systematic Mapping of the Literature. JUCS - Journal of Universal Computer Science 29(10): 1161-1198. https://doi.org/10.3897/jucs.90528
Open Access
Abstract
With the aid of technology advancement, the field of education has seen a noticeable transformation. The teaching-learning process is now more interactive and is no longer restricted to students' physical presence in the classroom but instead makes use of specialized online platforms. In recent years, solutions that offer learning routes customized to learners' needs have become more necessary. In this regard, artificial intelligence has served as an excellent answer, allowing for the building of educational systems that can accommodate a wide range of student needs. Through this paper, a systematic mapping of the literature on AI-based adaptive learning is presented. The examination of 93 articles published between 2000 and 2022 made it possible to draw several conclusions, including the number of adaptive learning environments based on AI, the types of AI algorithms used, the objectives targeted by these systems as well as factors related to adaptation. This study may serve as a springboard for further investigation into how to address the problems raised by the current state. 
Keywords
Adaptive learning, Artificial intelligence, Education, AIED