A robust classification to predict learning styles in adaptive E-learning systems

Ibtissam Azzi; Adil Jeghal; Abdelhay Radouane; Ali Yahyaouy; Hamid Tairi

doi:10.1007/s10639-019-09956-6

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A robust classification to predict learning styles in adaptive E-learning systems

Ibtissam Azzi Adil Jeghal Abdelhay Radouane Ali Yahyaouy Hamid Tairi

Year: 2019 Journal: Education and Information Technologies Vol: 25 (1)Pages: 437-448 Publisher: Springer Science+Business Media

DOI: 10.1007/s10639-019-09956-6

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Keywords:

Learning styles Artificial intelligence Machine learning Computer science Learning classifier system Classifier (UML) Robustness (evolution) Unsupervised learning Mathematics education

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Topics

Learning Styles and Cognitive Differences

Social Sciences → Psychology → Developmental and Educational Psychology

Online Learning and Analytics

Physical Sciences → Computer Science → Computer Science Applications

Educational Technology and Assessment

Physical Sciences → Computer Science → Information Systems

A robust classification to predict learning styles in adaptive E-learning systems

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