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

Artificial intelligence-enabled adaptive learning platforms: A review

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

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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Crossref · 10.1016/j.caeai.2025.100429

Cites

123 of 124 references verified0 citation errors · 0 not checkable

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  • This automation significantly reduces instructor workload while maintaining consistency across learning resources and supports scalable adoption in institutional settings.

    “This automation significantly reduces instructor workload while maintaining consistency across learning resources and supports scalable adoption in institutional settings [3].”
  • Integrating adaptivity directly into widely used LMS platforms has been repeatedly identified as a key challenge and opportunity for scalable personalization.

    “Integrating adaptivity directly into widely used LMS platforms has been repeatedly identified as a key challenge and opportunity for scalable personalization [3].”

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2 of the 126 references couldn’t be matched to a known paper.

Research works printed but not linked: 2

  1. Aggarwal, 2023, Integration of innovative technological developments and AI with education for an adaptive learning pedagogy, China Petroleum Processing and Petrochemical Technology, 23, 709
  2. Muñoz, 2022, Systematic review of adaptive learning technology for learning in higher education, Eurasian Journal of Educational Research, 98, 221

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Authors
Tan, L. Y., Hu, S., Yeo, D. J., & Cheong, K. H.
Affiliations
Nanyang Technological University (SG)
Corresponding author
Cheong, Kang Hao
Venue
Computers and Education: Artificial Intelligence
Publisher
Elsevier BV
Published
2025-12
Volume
9
Pages
100429
ISSN
2666-920X (ISSN-L)
OpenAlex
W4410882319
Cited by
207
References
126
Citations by year
2026: 151 · 2025: 56
FWCI
15.42
Type
journal article
Language
en
Open access
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
  • Physical Sciences › Computer Science › Information Systems › 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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