A Hybrid Machine Learning Approach to Predict Learning Styles in Adaptive E-Learning System

Ouafae El Aissaoui; Yasser El Madani El Alami; Lahcen Oughdir; Youssouf El Allioui

doi:10.1007/978-3-030-11928-7_70

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A Hybrid Machine Learning Approach to Predict Learning Styles in Adaptive E-Learning System

Ouafae El Aissaoui Yasser El Madani El Alami Lahcen Oughdir Youssouf El Allioui

Year: 2019 Advances in intelligent systems and computing Pages: 772-786 Publisher: Springer Nature

DOI: 10.1007/978-3-030-11928-7_70

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Keywords:

Machine learning Artificial intelligence Computer science Confusion matrix Instance-based learning Online machine learning Learning styles Unsupervised learning Active learning (machine learning) Semi-supervised learning Process (computing) Confusion Naive Bayes classifier Sequence learning Learning classifier system Support vector machine Mathematics Mathematics education Psychology

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Learning Styles and Cognitive Differences

Social Sciences → Psychology → Developmental and Educational Psychology

Online Learning and Analytics

Physical Sciences → Computer Science → Computer Science Applications

Artificial Immune Systems Applications

Physical Sciences → Engineering → Biomedical Engineering

A Hybrid Machine Learning Approach to Predict Learning Styles in Adaptive E-Learning System

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