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Teaching-Learning by Means of a Fuzzy-Causal User Model

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MICAI 2009: Advances in Artificial Intelligence (MICAI 2009)

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Abstract

In this research the teaching-learning phenomenon that occurs during an E-learning experience is tackled from a fuzzy-causal perspective. The approach is suitable for dealing with intangible objects of a domain, such as personality, that are stated as linguistic variables. In addition, the bias that teaching content exerts on the user’s mind is sketched through causal relationships. Moreover, by means of fuzzy-causal inference, the user’s apprenticeship is estimated prior to delivering a lecture. This supposition is taken into account to adapt the behavior of a Web-based education system (WBES). As a result of an experimental trial, volunteers that took options of lectures chosen by this user model (UM) achieved higher learning than participants who received lectures’ options that were randomly selected. Such empirical evidence contributes to encourage researchers of the added value that a UM offers to adapt a WBES.

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Peña Ayala, A. (2009). Teaching-Learning by Means of a Fuzzy-Causal User Model. In: Aguirre, A.H., Borja, R.M., Garciá, C.A.R. (eds) MICAI 2009: Advances in Artificial Intelligence. MICAI 2009. Lecture Notes in Computer Science(), vol 5845. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05258-3_46

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  • DOI: https://doi.org/10.1007/978-3-642-05258-3_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05257-6

  • Online ISBN: 978-3-642-05258-3

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