DocumentCode
2087791
Title
Identifying Learning Styles in Learning Management Systems by Using Indications from Students´ Behaviour
Author
Graf, Sabine ; Shuk, Kin ; Liu, Tzu-Chien
Author_Institution
Grad. Inst. of Learning & Instruction, Nat. Central Univ., Chungli
fYear
2008
fDate
1-5 July 2008
Firstpage
482
Lastpage
486
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 e-learning. 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, studentspsila learning styles can be identified automatically and be used for supporting students by considering their individual learning styles.
Keywords
computer aided instruction; educational courses; human factors; Felder-Silverman learning style model; e-learning management system; individual learning style identification; online course; student behaviour; Collaboration; Computer aided instruction; Conference management; Contracts; Councils; Electronic learning; Feedback; Information systems; Performance evaluation; Technology management; learning management systems; learning styles; student modelling;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Learning Technologies, 2008. ICALT '08. Eighth IEEE International Conference on
Conference_Location
Santander, Cantabria
Print_ISBN
978-0-7695-3167-0
Type
conf
DOI
10.1109/ICALT.2008.84
Filename
4561743
Link To Document