Automatic prediction of learning styles in learning management systems: a literature review

The Web-based learning environment promises to have a profound impact on learning processes. One way in which this field of research is bringing about beneficial effects for learners is through learner modelling that offers the content and learning resources to learners depending on their learning needs and personal traits, often in an interactive manner. A number of studies have focused on the integration of learner's learning styles and other personal traits in adaptive Web-based learning environments utilizing computer-based techniques. An important factor in these studies is to automatically predict the learning style. This paper provides a review of recent studies in learning styles modeling and prediction in e-learning systems. We identified three research questions and employed a systematic literature review technique to select and critically analyze the most relevant and important papers in automatic prediction of learning styles. An overview of learning style theories and learner modeling is provided followed by a discussion on learning styles theory selection, predictors and dimensions, and prediction and integration techniques.