Learning style estimation using bayesian networks

Webist 2007 - 3rd International Conference on Web Information Systems and Technologies, Proceedings

Volumn SEBEG, Issue EL/-, 2007, Pages 415-418

  Botsios, S ^a   Georgiou, D A ^a   Safouris, N F ^a  

^a DEMOCRITUS UNIVERSITY OF THRACE   (Greece)

Author keywords

Adaptive educational hypermedia systems; Bayesian networks; Expert systems; Learning style estimation

Indexed keywords

ADAPTIVE EDUCATIONAL HYPERMEDIA SYSTEMS; CULTURAL ENVIRONMENT; LEARNING STYLE; LEARNING STYLE ESTIMATION; WEB BASED;

DISTRIBUTED PARAMETER NETWORKS; EDUCATION; ESTIMATION; INFERENCE ENGINES; INFORMATION SYSTEMS; INTELLIGENT NETWORKS; PROBLEM SOLVING; SPEECH ANALYSIS; WORLD WIDE WEB;

BAYESIAN NETWORKS;

EID: 67649984894     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. Barros, B., Verdejo, M.F., Read, T., Mizoguchi, R., 2002. Lecture Notes in Computer Science; vol 2313. Proceedings of the Second Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence. Springer-Verlag. London.
2. Bunt, A., Conati, C, 2003. Probabilistic Student Modeling to Improve Exploratory Behavior. In User Modeling and User-Adapted Interaction, vol 13(3).
3. Dunn, R., Dunn K., Price, G. 1985. Learning Style Inventory Research Manual, Price Systems
4. Dunn, R., Dunn, K., 1992. Teaching elementary students through their individual learning styles: Practical approaches for grades 3-6, Boston, MA: AUyn & Bacon.
5. Felder, R., Silverman, L., 1988. Learning and Teaching Styles in Engineering Education. In Engineering Education, vol. 78(7), pp. 674-681.
6. Garcia, P., Amandi, A., Schiaffino, S., Campo, M., 2005. Evaluating Bayesian network's precision for detecting students' learning styles. In Computers and Education (in press)
7. Georgiou, D., Makry, D., 2004. A Learner's Style and Profile Recognition via Fuzzy Cognitive Map. In. Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT04). IEEE.
8. Kaltz, L., Rezaei, R., 2004. Evaluation of the reliability and validity of the cognitive style analysis. In Personality and Individual Differences, vol 36.
9. Kolb, D., 1984. Experiential Learning: Experience as the Source of Learning and Development. Prentice Hall, Englewood Cliffs.
10. Kolb, D., 1999. Learning Style Inventory-version 3: Technical Specifications, TRG Hay/McBer, Training Resources Group.
11. Millán, E., Perez-de-la-Cruz J., Suárez, E., 2000. Adaptive Bayesian Networks for Multilevel Student Modelling, Intelligent Tutoring Systems. In Proceedings of the Fifth International Conference. Montreal, Canada.
12. Murray, W., 1999. An Easily Implemented Linear-time Algorithm for Bayesian Student Modelling in Multilevel Trees, Artificial Intelligence in Education: Open Learning Environments: New Conceptual Technologies to Support Learning, Exploration and Collaboration, Frontiers in Artificial Intelligence and Applications, vol. 50, pp. 413-420.
13. Pearl, J., 1988. Probabilistic Inference in Intelligent Systems, Morgan Kaufmann, San Mateo, California.
14. Reye, J., 1996. Lecture Notes In Computer Science; vol 1086. Proceeding of the Third International Conference on Intelligent Tutoring Systems. Springer-Verlag. London.
15. Reye, J., 2004. Student Modelling based on Belief Networks. In International Journal of Artificial Intelligence in Education, vol 14.
16. Smith, SE., 2001. The relationship between learning style and cognitive style. In Personality and Individual Differences, vol 30.
17. Van Lehn, K., Martin, J., 1995. Student assessment using Bayesian Nets. In International Journal of Human Computer Studies, vol 42.
18. Zapata-Rivera, JD., Greer, J., 2004. Inspect able Bayesian student modeling servers in multi-agent tutoring systems. In International Journal of Human-Computer Studies, vol 61.