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A Process for Exploring Employees’ Relationships via Social Network and Sentiment Analysis Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Mining Sequential Patterns of Students’ Access on Learning Management System

Authors : Leonard K. M. Poon, Siu-Cheung Kong, Michael Y. W. Wong, Thomas S. H. Yau

Published in: Data Mining and Big Data

Publisher: Springer International Publishing

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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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Footnotes
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Metadata
Title
Mining Sequential Patterns of Students’ Access on Learning Management System
Authors
Leonard K. M. Poon
Siu-Cheung Kong
Michael Y. W. Wong
Thomas S. H. Yau
Copyright Year
2017
Book
Data Mining and Big Data

Print ISBN: 978-3-319-61844-9

Electronic ISBN: 978-3-319-61845-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-61845-6_20

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