Abstract
Group learning plays an important role in Web based educational process. Groups of students who are to learn together should be characterized by similar features. However course needs may differ depending on the context of the system usage. Each new student, who intends to join the community, should obtain context-aware recommendation of the group of colleagues matching his preferences. In the paper, using fuzzy logic for modeling students and groups is considered. We propose to describe student characteristics by means of fuzzy sets and to use the possibility-based representation of each group. We assume that context is represented by a vector of weights. Then recommendations for new students are determined by applying pattern matching technique including respective context vector. We examine the presented approach by taking into account learning style dimensions as attributes which characterize student preferences. The method is evaluated on the basis of experimental results obtained for real student data.
Keywords
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References
Schmidt, A., Winterhalter, C.: User Context Aware Delivery of E-learning Material: Approach and Architecture. J. Univers. Comput. Sci. 10, 38–46 (2004)
Shakouri, H.G., Tavassoli, Y.N.: Implementation of a Hybrid Fuzzy System as a Decision Support Process: A FAHP-FMCDM-FIS Composition. Expert Syst. Appl. 39, 3682–3691 (2012)
Zadeh, L.A.: Fuzzy Sets. Inform. Control 8, 338–353 (1965)
Myszkorowski, K., Zakrzewska, D.: Using fuzzy logic for recommending groups in E-learning systems. In: Bǎdicǎ, C., Nguyen, N.T., Brezovan, M. (eds.) ICCCI 2013. LNCS, vol. 8083, pp. 671–680. Springer, Heidelberg (2013)
Myszkorowski, K., Zakrzewska, D.: Building contextual student group recommendations with fuzzy logic. In: Cornelis, C., Kryszkiewicz, M., Ślȩzak, D., Ruiz, E.M., Bello, R., Shang, L. (eds.) RSCTC 2014. LNCS, vol. 8536, pp. 358–365. Springer, Heidelberg (2014)
Dubois, D., Prade, H., Testemale, C.: Weighted Fuzzy Pattern Matching. Fuzzy Set Syst. 28, 313–331 (1988)
Bobadilla, J., Serradilla, F., Hernando, A.: Collaborative Filtering Adapted to Recommender Systems of E-learning. Knowl-Based Syst. 22, 261–265 (2009)
Severac, Z., Devedzic, V., Jovanovic, J.: Adaptive Neuro-Fuzzy Pedagogical Recommender. Expert Syst. Appl. 39, 9797–9806 (2012)
Jovanowic, J., Gasewic, D., Knight, C., Richards, G.: Ontologies for Effective Use of Context in E-learning Settings. Educ. Technol. Soc. 10, 47–59 (2007)
Yang, S.J.H.: Context Aware Ubiquitous Learning Environments for Peer-to-Peer Collaborative Learning. Educ. Technol. Soc. 9, 188–201 (2006)
Das, M.M., Chithralekha, T., SivaSathya, S.: Static Context Model for Context Aware E-learning. Int. J. Eng. Sci. Technol. 2, 2337–2346 (2010)
Adomavicius, G., Tuzhilin, A.: Context-aware recommender systems. In: Ricci, F., et al. (eds.) Recommender Systems Handbook, pp. 217–253. Springer Science+Business Media (2011)
Muehlenbrock, M.: Formation of learning groups by using learner profiles and context information. In: 12th International Conference AIED 2005, pp. 507–514 (2005)
Christodoulopoulos, C.E., Papanikolaou, K.A.: A group formation tool in an E-learning context. In: 19th IEEE ICTAI 2007, vol. 2, pp. 117–123 (2007)
Wang, J., Li, H., Zhao, H.: The Contextual group recommendation. In: 5th International Conference on Intelligent Networking and Collaborative Systems, pp. 127–131 (2013)
Masthoff, J.: Group recommender systems: combining individual models. In: Ricci, F., et al. (eds.) Recommender Systems Handbook, pp. 677–702. Springer Science+Business Media (2011)
Zheng, Y., Burke, R., Mobasher, B.: Recommendation with differential context weighting. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds.) UMAP 2013. LNCS, vol. 7899, pp. 152–164. Springer, Heidelberg (2013)
de Arriaga, F., El Alami, M., Arriaga, A.: Evaluation of fuzzy intelligent learning systems. In: Mendez-Vilas, A., et al. (eds.) Recent Research Developments in Learning Technologies. Formatex, Badajoz (2005)
Hogo, M.: Evaluation of E-Learners Behavior Using Different Fuzzy Clustering Models: A Comparative Study. International Journal of Computer Science and Information Security 7, 131–140 (2010)
Essalmi, F., Ayed, L., Jemni, M., Kinshuk, Graf, S.: Evaluation of personalization strategies based on fuzzy logic. In: 11th IEEE International Conference on Advanced Learning Technologies, pp. 254–256 (2011)
Lu, J.: A personalized e-learning material recommender system. In: the 2nd International Conference on Information Technology for Application, pp. 374–379 (2004)
Vrettaros, J., Vouros, G.A., Drigas, A.S.: Development of an intelligent assessment system for solo taxonomies using fuzzy logic. In: Mellouli, K. (ed.) ECSQARU 2007. LNCS (LNAI), vol. 4724, pp. 901–911. Springer, Heidelberg (2007)
Almohammadi, K., Hagras H.: An adaptive fuzzy logic based system for improved knowledge delivery within intelligent E-learning platforms. In: 2013 IEEE International Conference on Fuzzy Systems (2013)
Chrysafiadi, K., Virvou, M.: Fuzzy Logic for Adaptive Instruction in an E-learning Environment for Computer Programming. IEEE T. Fuzzy Syst. 23, 164–177 (2015)
Zadeh, L.A.: Fuzzy Sets as a Basis for a Theory of Possibility. Fuzzy Set Syst. 1, 3–28 (1978)
Dubois, D., Prade, H.: The Three Semantics of Fuzzy Sets. Fuzzy Set Syst. 90, 141–150 (1997)
Felder, R.M., Silverman, L.K.: Learning and Teaching Styles in Engineering Education. Eng. Educ. 78, 674–681 (1988)
Index of Learning Style Questionnaire. http://www.engr.ncsu.edu/learningstyles/ilsweb.html
Witten, I.H., Frank, E.: Data Mining: Practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann Publishers, San Francisco (2005)
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Myszkorowski, K., Zakrzewska, D. (2015). Fuzzy Logic Based Modeling for Building Contextual Student Group Recommendations. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9330. Springer, Cham. https://doi.org/10.1007/978-3-319-24306-1_43
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DOI: https://doi.org/10.1007/978-3-319-24306-1_43
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