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Personalisation methods in e‐learning‐A literature review

  • Published:2022-09-19 Issue:6 Volume:30 Page:1931-1958
  • ISSN:1061-3773
  • Container-title:Computer Applications in Engineering Education
  • language:en
  • Short-container-title:Comp Applic In Engineering

Author:

Mikić Vladimir1ORCID,Ilić Miloš1,Kopanja Lazar1,Vesin Boban23

Affiliation:

1. Faculty of Information Technologies Alfa BK University Belgrade Serbia

2. Department of Business, History and Social Sciences University of South‐Eastern Norway Vesfold Norway

3. Department of Computer Science Norwegian University of Science and Technology Trondheim Norway

Publisher

Wiley

Subject

General Engineering,Education,General Computer Science

Reference292 articles.

1. Developing an Intelligent Tutoring System For Students Learning To Program in C++

2. Human computer interaction design of the lp‐its: Linear programming intelligent tutoring systems;Abu‐Naser S. S.;Int. J. Artif. Intell. Appl,2011

3. Learner modelling: systematic review of the literature from the last 5 years

4. Data mining classification techniques on the analysis of student's performance;Adebayo A. O.;GSJ,2019

5. Genetic algorithm‐based curriculum sequencing model for personalised e‐learning system;Agbonifo O. C.;Int. J. Educ. Manag. Eng,2018

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2. What Factors Contribute to Effective Online Higher Education? A Meta-Review;Technology, Knowledge and Learning;2024-06-13

3. Self‐regulation and shared regulation in collaborative learning in adaptive digital learning environments: A systematic review of empirical studies;British Journal of Educational Technology;2024-04-09

4. Recommendations for Personalised Learning Paths;2024 13th International Conference on Educational and Information Technology (ICEIT);2024-03-22

5. Predicting Student Performance in a Programming Tutoring System Using AI and Filtering Techniques;IEEE Transactions on Learning Technologies;2024
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