Abstract
Novel pedagogical approaches supported by digital technologies such as blended learning and flipped classroom are prevalent in recent years. To implement such learning strategies, learning resources are often put online on learning management systems. The log data on those systems provide an excellent opportunity for getting more understanding about the students through data mining techniques. In this paper, we propose to use sequential pattern mining (SPM) to discover navigational patterns on a learning platform. We attempt to address the lack of literature support about conducting SPM on Moodle. We propose a method to apply SPM that is more appropriate for mining user navigational patterns. We further propose three sequence modeling strategies for mining patterns with educational implications. Results of a study on a statistics course show the effectiveness of the proposed method and the proposed sequence modeling strategies.
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Acknowledgment
The study was funded by Teaching Development Grant (HKIED7/T&L/12-15) under the Hong Kong University Grants Committee.
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Poon, L.K.M., Kong, SC., Wong, M.Y.W., Yau, T.S.H. (2017). Mining Sequential Patterns of Students’ Access on Learning Management System. In: Tan, Y., Takagi, H., Shi, Y. (eds) Data Mining and Big Data. DMBD 2017. Lecture Notes in Computer Science(), vol 10387. Springer, Cham. https://doi.org/10.1007/978-3-319-61845-6_20
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DOI: https://doi.org/10.1007/978-3-319-61845-6_20
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