Towards Inferring Sequential-Global Dimension of Learning Styles from Mouse Movement Patterns
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
AH-questionnaire: An adaptive hierarchical questionnaire for learning styles
Computers & Education
End-user training methods: what we know, need to know
ACM SIGMIS Database
Tweets reveal more than you know: a learning style analysis on twitter
EC-TEL'12 Proceedings of the 7th European conference on Technology Enhanced Learning
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New client-based systems that filter Web pages, infer user learning styles, and recommend relevant pages are described. The systems provide easy, structured, focused, and controlled access to the Internet. A first system, called iLessons, is embedded within Microsoft Internet Explorer 6 and provides teachers with tools to create lesson Web pages, define zones of the Internet that can be accessed during a lesson, and enforce these settings in a set of computers. A second system enables students to investigate and collaborate using the Internet. The system filters Web pages based on the relevance of their contents and assists students by inferring their learning style (active or reflective) and by recommending pages found by fellow students based on page relevancy, student learning style, and state of mind measured by activity.