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Title:
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BEHAVIORAL FEATURE EXTRACTION TO DETERMINE LEARNING STYLES IN E-LEARNING ENVIRONMENTS |
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Author(s):
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Somayeh Fatahi, Hadi Moradi, Elaheh Farmad |
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ISBN:
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978-989-8533-40-1 |
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Editors:
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Miguel Baptista Nunes and Maggie McPherson |
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Year:
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2015 |
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Edition:
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Single |
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Keywords:
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Learning style, e-learning, MBTI, learners behavior |
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Type:
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Full Paper |
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First Page:
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66 |
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Last Page:
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72 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Learning Style (LS) is an important parameter in the learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning environments. Consequently, an important capability of an e-learning system could be the automatic determination of a student's learning style. In this paper, a set of features which are important in extracting the learning style automatically from students behavior has been determined. These features, which are recognized based on Myers-Briggs Type Indicator's (MBTI), play a key role in predicting learning styles in an online course. The features are determined and ranked using pattern recognition techniques, such as K-means clustering algorithm, to show which features can be better to separate learning style dimensions. The results show several features can be used to predict learning styles with high precision. |
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