Title
Mining Sequential Patterns Of Students' Access On Learning Management System
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.
Year
DOI
Venue
2017
10.1007/978-3-319-61845-6_20
DATA MINING AND BIG DATA, DMBD 2017
Keywords
Field
DocType
Sequential pattern mining, Educational data mining, Learning management systems, Moodle, Navigational patterns
Data science,Data mining,Virtual learning environment,Flipped classroom,Learning Management,Computer science,Sequence modeling,Blended learning,Multimedia,Sequential Pattern Mining,Educational data mining
Conference
Volume
ISSN
Citations 
10387
0302-9743
1
PageRank 
References 
Authors
0.43
8
4
Name
Order
Citations
PageRank
Leonard K. M. Poon19410.96
Siu Cheung Kong215626.41
Michael Y. W. Wong320.82
Thomas S. H. Yau420.82