Cited by 207Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in EducationOnline Learning and Analytics

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Artificial intelligence-enabled adaptive learning platforms: A review

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Tan, Le Ying, Hu, Shiyu, Yeo, Darren J., Cheong, Kang Hao·2025·Computers and Education: Artificial Intelligence

DOI 10.1016/j.caeai.2025.100429

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Abstract

This review provides a comprehensive analysis of adaptive learning platforms (ALPs) in education, focusing on their pedagogical foundations, AI-driven implementations, and the challenges and successes of real-world applications. By collecting and analyzing learner data, ALPs dynamically adjust instructional content and pathways to offer personalized learning experiences, enhancing learning outcomes. The paper explores ALP design frameworks, core algorithms, and evaluation metrics, and assesses their performance across diverse educational contexts through case studies. Lastly, the review highlights key challenges ALPs face, such as privacy concerns and faculty support for implementation, and offers insights into future trends in developing adaptive technologies. This review provides educators and researchers with valuable insights into how ALPs can be effectively applied in various educational settings.

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See all 207

Authors: Tan, L. Y., Hu, S., Yeo, D. J., & Cheong, K. H.
Affiliations: Nanyang Technological University (SG)
Corresponding author: Cheong, Kang Hao
ORCID: Hu, Shiyu
Yeo, Darren J.
Cheong, Kang Hao
Venue: Computers and Education: Artificial Intelligence
Publisher: Elsevier BV
Published: 2025-12
Volume: 9
Pages: 100429
ISSN: 2666-920X (ISSN-L)
DOI: 10.1016/j.caeai.2025.100429
OpenAlex: W4410882319
Semantic Scholar: dde418c0ff78aea0c101f3a7c2c86ab90dd98fac
Cited by: 207
References: 126
Citations by year: 2026: 151 · 2025: 56
FWCI: 15.42
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by-nc-nd
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
creativecommons.org/licenses/by/4.0/ (vor)
Locations: Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
Funders: Government of Singapore Ministry of Education (MOE2022-TRF-029)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Social Sciences › Education › Artificial Intelligence in Education
Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
Keywords: adaptive learning systems, artificial intelligence in education, personalized learning, adaptive learning algorithms, learner data, student privacy, faculty support

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Artificial intelligence-enabled adaptive learning platforms: A review

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