Abstract
SIAL is an Intelligent Tutoring System (ITS) for learning Computational Logic. It teaches classical refutation by resolution concepts using Robinson’s Binary Resolution Rule. Furthermore, SIAL can be considered a Model-Based System, as its Domain Model is an Automated Theorem Prover (ATP) for First Order Logic (FOL). This allows SIAL to accept several solutions to the proposed exercise, all of which are correct, providing a kind of open-ended feature to the ITS. The Domain Model is in charge of carrying out the error diagnosis, identifying, in many cases, the misunderstandings. The focus of this paper is to describe the Pedagogical Model of SIAL that takes advantage of the error diagnosis capabilities of the Domain Model to offer a learner-adaptive tutorial action, according to the user cognitive profile.
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Maestro-Prieto, J.A., Simon-Hurtado, A. (2015). Learner-Adaptive Pedagogical Model in SIAL, an Open-Ended Intelligent Tutoring System for First Order Logic. In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science(), vol 9112. Springer, Cham. https://doi.org/10.1007/978-3-319-19773-9_96
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DOI: https://doi.org/10.1007/978-3-319-19773-9_96
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