User Modeling and User-Adapted Interaction
User Modeling and User-Adapted Interaction
An Approach for Detecting Learning Styles in Learning Management Systems
ICALT '06 Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies
The impact of learning styles on student grouping for collaborative learning: a case study
User Modeling and User-Adapted Interaction
Improved use of continuous attributes in C4.5
Journal of Artificial Intelligence Research
Studying the impact of personality and group formation on learner performance
CRIWG'07 Proceedings of the 13th international conference on Groupware: design implementation, and use
Intelligent browser-based systems to assist Internet users
IEEE Transactions on Education
Designer - supporting teachers experience in learning management systems
ICWL'12 Proceedings of the 11th international conference on Advances in Web-Based Learning
Computer-assisted assessment with item classification for programming skills
Proceedings of the First International Conference on Technological Ecosystem for Enhancing Multiculturality
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One of the main concerns when providing learning style adaptation in Adaptive Educational Hypermedia Systems is the number of questions the students have to answer. Most of the times, adaptive material available will discriminate among a few categories for each learning style dimension. Consequently, it is only needed to take into account the general tendency of the student and not the specific score obtained in each dimension. In this context, we present AH-questionnaire, a new approach to minimize the number of questions needed to classify student Learning Styles. Based on the Felder-Silverman's Learning Style Model, it aims at classifying students into categories in spite of providing precise scores. The results obtained in a case study with 330 students are very promising. It was possible to predict students' learning style preference with high accuracy and only a few questions.