Advanced knowledge sharing strategies based on learning style similarity for smart education

Abstract

The spread of the smart device has led collaborative technologies to valuable applications in developing educational content. Many electronic textbooks provide basic annotation features like sharable bookmarks, notes, highlighting and underlining. These user activities contain important information in the view of education such as user knowledge and students' learning style. In this paper, we proposed annotation-content learning model to analyze learner's annotating behavior on electronic textbooks. Based on the model, we also developed similarity algorithms to find other notes created by students who have similar learning style. The purpose of the proposed system is to encourage students to have their own online communities using smart tablets to pool their knowledge and share ideas and experiences. We also presented the evaluation indicating that the system improved students' knowledge significantly. © 2012 Springer-Verlag.