Abstract
With the advancement of mobile device and wireless communication technologies, personalised ubiquitous learning support systems providing learning material corresponding student preference have been becoming an important research issue. This study focuses on developing such a learning support system based on learning styles and preferred technology types to recommend a proper digital learning material. A two-step experiment was conducted: the first study, involving 190 university students, explored a learning style-preferred technology type decision model for recommending digital learning material to individual students. The second study, involving 39 university students, empirically evaluated the effectiveness of the decision model-based personalised ubiquitous learning support system and the experiment was based on a pre-test and post-test design. The results of the two-part experiments showed that (a) the decision model is able to recommend proper learning material to individual students based on their learning style and preferred technology type, and (b) the learning support system demonstrated good performance concerning the gain of knowledge and learning motivations.
Published Version
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