Abstract
Several initiatives concerning the learner model has been proposed in the context of technology-enhanced learning systems. In fact, there are two main challenges encountered in this regard: Firstly, which information will serve to represent and reflect better the learner? Secondly, which formalism chooses for representing and managing the learner model? To overcome those challenges, we propose a new ontological approach for learner modeling enriched from the existing models.
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References
Chrysafiadi, K., Virvou, M.: Student modeling approaches: a literature review for the last decade. Expert Syst. Appl. 40(11), 4715–4729 (2013)
Self, J.: The role of student models in learning environments. IEICE Trans. Inf. Syst. 77, 3–8 (1994). No. 94
Jameson, A., Paris, C., Tasso, C.: User Modeling: Proceedings of the Sixth International Conference, UM97. SpringerWein, New York (1997)
VanLehn, K.: Toward a theory of impasse-driven learning. In: Learning Issues for Intelligent Tutoring Systems, pp. 19–41. Springer, New York (1988)
Brusilovsky, P., Peylo, C.: Adaptive and intelligent web-based educational systems (IJAIED). Int. J. Artif. Intell. Educ. 13, 159–172 (2003)
Mccalla, G., Vassileva, J., Greer, J., Bull, S.: Active learner modelling (2000)
Kay, J.: Stereotypes, student models and scrutability. In: International Conference on Intelligent Tutoring Systems, pp. 19–30 (2000)
Carr, B., Goldstein, I.P.: Overlays: a theory of modelling for computer aided instruction (1977)
Greer, J.E., McCalla, G.I.: Student Modelling: The Key to Individualized Knowledge-Based Instruction, vol. 125. Springer, Heidelberg (2013)
Brown, J.S., VanLehn, K.: Repair theory: a generative theory of bugs in procedural skills. Cognit. Sci. 4(4), 379–426 (1980)
Ohlsson, S.: Constraint-based student modelling. J. Interact. Learn. Res. 3(4), 429 (1992)
Zhouand, X., Conati, C.: Inferring user goals from personality and behavior in a causal model of user affect, pp. 1–8 (2003)
Panagiotopoulos, I., Kalou, A.: An ontology-based model for student representation in intelligent tutoring systems for distance learning. In: Artificial Intelligence Tutoring Systems for Distance Learning, pp. 296–305 (2012)
Rezgui, K., Mhiri, H., Ghédira, K.: An ontology-based profile for learner representation in learning networks. Int. J. Emerg. Technol. Learn. 9(3), 16–25 (2014)
Kikiras, P., Tsetsos, V., Hadjiefthymiades, S.: Ontology-based user modeling for pedestrian navigation systems. In: ECAI 2006 Workshop on Ubiquitous User Modeling (UbiqUM), Riva del Garda, Italy, pp. 1–6, January 2006
Clemente, J., Ramírez, J., De Antonio, A.: A proposal for student modeling based on ontologies and diagnosis rules. Expert Syst. Appl. 38(7), 8066–8078 (2011)
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Akharraz, L., El Mezouary, A., Mahani, Z. (2019). LMOnto: An Ontology-Based Learner Model for Technology Enhanced Learning Systems. In: Khoukhi, F., Bahaj, M., Ezziyyani, M. (eds) Smart Data and Computational Intelligence. AIT2S 2018. Lecture Notes in Networks and Systems, vol 66. Springer, Cham. https://doi.org/10.1007/978-3-030-11914-0_15
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