Abstract
This paper presents the pertinence of the use of the Answer Set Programming (ASP) formalism for developing a computational model of a software agent for Computer Supported Collaborative Learning (CSCL) environments. This analytic model is based on a representation of for agent’s beliefs about the learner and the domain, together with the corresponding inference system with the appropriate rules to derive new beliefs about the capabilities of the learner, and its use in order to support effective collaboration and maintain learning possibilities for the group members. The model provides a representation of the structural knowledge frontier and the social knowledge frontier of the learner, which are the components for the definition of the learner’s zone of proximal development (zpd). Based on the zpd of its learner the agent can propose her a learning task and maintain the zpd for the learner in the group. The complete code of the model is presented in the declarative language of DLV, a logic programming language for implementing ASP models.
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Ayala, G., Ortiz, M., Osorio, M. (2005). Application of ASP for Agent Modelling in CSCL Environments. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds) MICAI 2005: Advances in Artificial Intelligence. MICAI 2005. Lecture Notes in Computer Science(), vol 3789. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11579427_12
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DOI: https://doi.org/10.1007/11579427_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29896-0
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