EvoLogic: Intelligent Tutor System for Teaching Logic
Abstract
This article presents the cognitive model of the EvoLogic Intelligent Tutoring System, developed to assist in the teaching-learning process of Natural Deduction in Propositional Logic. EvoLogic consists of 3 agents, among which, the Pedagogical agent (treated here as the student model) and the Specialist agent (based on a Genetic Algorithm) compose the cognitive model. The purpose of the article, in addition to presenting the EvoLogic, is to analyze the efficiency of the ITS in a known exercise that has already been studied in the literature (applied to 57 students). The results show that the EvoLogic obtained all the solutions presented by the students, allowing it to follow the student's steps, providing real-time feedback, based on the steps that the students are taking, known as model tracing.
Keywords:
cognitive model, propositional logic, genetic algorithm
References
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Yacef, K. (2005) The Logic-ITA in the classroom: a medium scale experiment. International Journal of Artificial Intelligence in Education (IJAIED), vol. 15, p. 41- 62.
E-Prover (2020) The E Theorem Prover. https://wwwlehre.dhbw- stuttgart.de/~sschulz/E/E.html.
GALAFASSI, P. F. F.; GLUZ, J. C. ; GALAFASSI, C. (2013) Análise Crítica das Pesquisas Recentes sobre as Tecnologias de Objetos de Aprendizagem e Ambientes Virtuais de Aprendizagem. REVISTA BRASILEIRA DE INFORMÁTICA NA EDUCAÇÃO, v. 21, p. 85-99.
Galafassi, P. F. F.; Galafassi, C.; Vicari, R. M.; Gluz, J. C.; (2019a) Identifying Knowledge from the Application of Natural Deduction Rules in Propositional Logic. In: Demazeau Y., Matson E., Corchado J., De la Prieta F. (eds) Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection. p. 66-77.
Galafassi, P. F. F.; Galafassi, C.; Gluz, J. C.; Vicari, R. M. (2019b) LOGOS - Caderno de Estudos e Exercícios de Lógica do Ambiente de Ensino Heráclito. In: Karina Durau. (Org.). Demandas e Contextos da Educação no Século XXI. 1ed.Ponta Grossa: Atenas Editora, p. 1-8.
Gluz, J. C., Py, M. X. (2015) Introdução à Lógica Proposicional. Grupo TAOS3 - PIPCA – UNISINOS.
Hol (2020) Interactive Theorem Prover. https://hol-theorem-prover.org/
Holland, J. H. (1975) Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, Michigan.
Isabelle (2020) Isabelle proof assistant. https://isabelle.in.tum.de/.
JAPE. (2020) http://japeforall.org.uk/
Lesta L., Yacef K. (2002) An Intelligent Teaching Assistant System for Logic. In: Cerri S.A., Gouardères G., Paraguaçu F. (eds) Intelligent Tutoring Systems. ITS 2002. Lecture Notes in Computer Science, vol. 2363. p. 421-431.
Lukins, S.; Levicki, A. and Burg, J. (2002) A Tutorial Program for Propositional Logic with Human/Computer Interactive Learning. Proceedings of the 33rd SIGCSE Technical Symposium on Computer Science Education. p. 381-385.
Nwana, H. S. (1990) Intelligent Tutoring Systems: an overview. Artificial Intelligence Review. Springer,
Pandora (2020) Proof Assistant for Natural Deduction using Organised Rectangular Areas. http://www.doc.ic.ac.uk/pandora/newpandora/quick_start.html.
Prover9/Mace4 (2020) Prover9 and Mace4 https://www.cs.unm.edu/~mccune/prover9/
Resolução CNE/CES no 5, de 16 de novembro de 2016. http://portal.mec.gov.br/component/content/article?id=12991
Sieg, W. (2007) The AProS project: Strategic thinking & computational logic. Logic Journal of IGPL, 15(4): 359-368.
SPASS (2020) Classic SPASS: An Automated Theorem Prover for First-Order Logic with Equality. https://www.mpi-inf.mpg.de/departments/automation-of- logic/software/spass-workbench/classic-spass-theorem-prover/.
Yacef, K. (2005) The Logic-ITA in the classroom: a medium scale experiment. International Journal of Artificial Intelligence in Education (IJAIED), vol. 15, p. 41- 62.
Published
2020-06-30
How to Cite
GALAFASSI, Cristiano; GALAFASSI, Fabiane; REATEGUI, Eliseo ; VICARI, Rosa .
EvoLogic: Intelligent Tutor System for Teaching Logic. In: INTEGRATED SOFTWARE AND HARDWARE SEMINAR (SEMISH), 47. , 2020, Cuiabá.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 222-233.
ISSN 2595-6205.
DOI: https://doi.org/10.5753/semish.2020.11331.
