Sequential-global learning style detection based on users’ navigation patterns in the prerequisite structure

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages283-293
Volume9167
ISBN (Print)9783319206202
Publication statusPublished - 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9167
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Title8th International Conference on Hybrid Learning, ICHL 2015
LocationCentral China Normal University
PlaceChina
CityWuhan
Period27 - 29 July 2015

Abstract

The preferred way people apply in learning is known as learning style. Adapting different learning strategies to different learning styles yields a better learning outcome. In this paper, we describe a novel rule- based approach to detect the students’ learning styles (sequential/global) by analyzing their navigation patterns in the prerequisite structure. In order to evaluate the accuracy of the proposed approach, a case study in dance education was conducted, 32 students were asked to learn 10 dances by browsing the prerequisite structure in a dance education system. Students’ browsing histories are recorded and analyzed so that their learning styles are extracted. The result shows that our approach is optimistic.

Research Area(s)

  • Dance education, Learning style, Navigation pattern, Prerequisite structure

Citation Format(s)

Sequential-global learning style detection based on users’ navigation patterns in the prerequisite structure. / Yang, Yang; Leung, Howard; Liu, Zhanzhan; Zhan, Yongzhao; Zeng, Lanling.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9167 Springer Verlag, 2015. p. 283-293 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9167).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review