Systematic review of adaptive learning research designs, context, strategies, and technologies from 2009 to 2018
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AI has showcased its ability to cater to individual student needs, offering tailored curricula and adaptive assessments.
“Through supporting personalised learning experiences, AI has showcased its ability to cater to individual student needs, offering tailored curricula and adaptive assessments (Brusilovsky, 1996;Hemmler & Ifenthaler, 2022;Jones & Winne, 1992;Martin et al., 2020).”
From Artificial Intelligence in Education: Implications for Policymakers, Researchers, and Practitioners (2024) · cites this paper as Martin et al., 2020
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- Authors
- Martin, F., Chen, Y., Moore, R. L., & Westine, C. D.
- Affiliations
- University of North Carolina at Charlotte (US)
- University of New Mexico (US)
- Old Dominion University (US)
- Corresponding author
- Westine, Carl D.
- Venue
- Educational Technology Research and Development
- Published
- 2020-06-15
- Volume
- 68
- Issue
- 4
- Pages
- 1903-1929
- ISSN
- 1042-1629 (ISSN-L)
- 1556-6501
- OpenAlex
- W3036177938
- Cited by
- 306
- References
- 63
- Citations by year
- 2026: 78 · 2025: 87 · 2024: 66 · 2023: 31 · 2022: 29 · 2021: 13 · 2020: 2
- FWCI
- 0.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Educational Technology Research and Development (publishedVersion)
- ODU Digital Commons (Old Dominion University) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Keywords
- adaptive learning, adaptive learning systems, adaptive learning strategies, student model, adaptive feedback, adaptive navigation, learning styles, personalized learning, higher education, instructional design, research gaps
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