Abstract
In this paper, a framework for individualizing the learning material structure in adaptive learning system is introduced. It aims to utilize the learning characteristics and provide a personalized learning environment that exploit pedagogical model and fuzzy logic techniques. The learning material consists of 4 structures; 1) theory, 2) examples 3) exercises and 4) activities. The pedagogical model and learning characteristics are based on the student’s personality factor (Myers-Briggs Type Indicator (MBTI)), whilst the fuzzy logic techniques are used to classify the structure of learning material which is based on student’s personality factors. This paper tend to illustrate the construction of fuzzy set and fuzzy rules to find the best rules based on combination of two approaches; learning style approach and fuzzy logic approach for adapting the content to the user, allowing a learning system to dynamically adapt the choice of possible learning structure through the learning material based on the user’s personality factor.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Brusilovsky, P.: Adaptive Hypermedia. User Modeling and User- Adapted Instruction, vol. 1-2, pp. 87–110. Kluwer academic Publishers, Dordrecht (2001)
Hashim, S., Yaakub, R.: Terbitan Pertama Psikologi Pembelajaran dan Personaliti. PTS Publications & Distributors Sdn. Bhd (Pelita) Malaysia (2003)
Stash, N., Cristeae, A., Bra, P.D.: Authoring of Learning Styles in Adaptive Hypermedia:Problems and Solutions International World Wide Web Conference. In: Proceedings of the 13th international World Wide Web conference on Alternate track papers & poster, pp. 114–123 (2004)
Carro, R.M., Pulido, E., Rodríguez, P.: Tangow: Task-Based Adaptive Learner Guidance on the WWW. In: Proc. Second Workshop on Adaptive Systems and User Modeling on the World Wide Web, Canada, pp. 49–57 (1999)
Triantafillou, E., Pomportsis, A., Georgiadou, E.: AES-CS: Adaptive Educational System base on cognitive styles. In: Proceedings of the AH 2002 Workshop, Malaga, Spain, pp. 10–20 (2002)
Bishop, C.C., Wheeler, D.: The Myers-Briggs Personality Type and Its Relationship to Computer Programming. Journal of Research on Computing in Education 26, 358–371 (1994)
Soles, C., Moller, L.: Myers Briggs Type Preferences in Distance Learning Education. International Journal of Educational Technology 2 (2001)
Honey, P., Mumford, A.: The Manual of Learning Styles. Maidenhead: PeterHoney (1992)
Schroeder, C.C.: New-Students-New LearningStyle (March 7, 2004), http://www.virtualschool.edu/mon/Academia/KierseyLearningStyles.html
Negnevitsky, M.: Artificial Intelligence. A Guide to Intelligent Systems, 1st edn. Pearson Education, London (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Salim, N., Haron, N. (2006). The Construction of Fuzzy Set and Fuzzy Rule for Mixed Approach in Adaptive Hypermedia Learning System. In: Pan, Z., Aylett, R., Diener, H., Jin, X., Göbel, S., Li, L. (eds) Technologies for E-Learning and Digital Entertainment. Edutainment 2006. Lecture Notes in Computer Science, vol 3942. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11736639_26
Download citation
DOI: https://doi.org/10.1007/11736639_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33423-1
Online ISBN: 978-3-540-33424-8
eBook Packages: Computer ScienceComputer Science (R0)