E-Learning personalization based on hybrid recommendation strategy and learning style identification
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Learning styles have been among the broadly chosen components in previous studies as a reference for adapting learning.
“Learning styles (Çakıroğlu, 2014;Klašnja-Milićević et al., 2011;Latham, Crockett and McLean, 2014) have been among the broadly chosen components in previous studies as a reference for adapting learning.”
From A systematic literature review of personalized learning terms (2020) · cites this paper as Klašnja-Milićević et al., 2011
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- Authors
- Klašnja-Milićević, A., Vesin, B., Ivanović, M., & Budimac, Z.
- Affiliations
- University of Novi Sad (RS)
- Corresponding author
- Vesin, Boban
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2011-04
- Volume
- 56
- Issue
- 3
- Pages
- 885-899
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W1994510396
- Cited by
- 580
- References
- 46
- Citations by year
- 2026: 11 · 2025: 23 · 2024: 25 · 2023: 27 · 2022: 41 · 2021: 47 · 2020: 53 · 2019: 56 · 2018: 41 · 2017: 50 · 2016: 52 · 2015: 54 · 2014: 37 · 2013: 29 · 2012: 19
- FWCI
- 56.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers & Education (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- personalized e-learning, learning style identification, hybrid recommendation, frequent sequence mining, learner preferences
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