Identifying learning styles in learning management systems by using indications from students' behaviour

Sabine Graf, Kinshuk, Tzu-Chien Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

109 Citations (Scopus)

Abstract

Making students aware of their learning styles and presenting them with learning material that incorporates their individual learning styles has potential to make learning easier for students and increase their learning progress. This paper proposes an automatic approach for identifying learning styles with respect to the Felder-Silverman learning style model by inferring their learning styles from their behaviour during they are learning in an online course. The approach was developed for learning management systems, which are commonly used in elearning. In order to evaluate the proposed approach, a study with 127 students was performed, comparing the results of the automatic approach with those of a learning style questionnaire. The evaluation yielded good results and demonstrated that the proposed approach is suitable for identifying learning styles. By using the proposed approach, students' learning styles can be identified automatically and be used for supporting students by considering their individual learning styles.

Original languageEnglish
Title of host publicationProceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008
Pages482-486
Number of pages5
DOIs
Publication statusPublished - 2008 Sep 22
Event8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008 - Santander, Spain
Duration: 2008 Jul 12008 Jul 5

Publication series

NameProceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008

Other

Other8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008
CountrySpain
CitySantander
Period08/7/108/7/5

Fingerprint

indication
Students
management
learning
student
learning success
questionnaire

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Information Systems
  • Electrical and Electronic Engineering
  • Education

Cite this

Graf, S., Kinshuk, & Liu, T-C. (2008). Identifying learning styles in learning management systems by using indications from students' behaviour. In Proceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008 (pp. 482-486). [4561743] (Proceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008). https://doi.org/10.1109/ICALT.2008.84

Identifying learning styles in learning management systems by using indications from students' behaviour. / Graf, Sabine; Kinshuk; Liu, Tzu-Chien.

Proceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008. 2008. p. 482-486 4561743 (Proceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Graf, S, Kinshuk & Liu, T-C 2008, Identifying learning styles in learning management systems by using indications from students' behaviour. in Proceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008., 4561743, Proceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008, pp. 482-486, 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008, Santander, Spain, 08/7/1. https://doi.org/10.1109/ICALT.2008.84
Graf S, Kinshuk, Liu T-C. Identifying learning styles in learning management systems by using indications from students' behaviour. In Proceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008. 2008. p. 482-486. 4561743. (Proceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008). https://doi.org/10.1109/ICALT.2008.84
Graf, Sabine ; Kinshuk ; Liu, Tzu-Chien. / Identifying learning styles in learning management systems by using indications from students' behaviour. Proceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008. 2008. pp. 482-486 (Proceedings - The 8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008).
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