Helping students of introductory calculus classes: the Leibniz pedagogical agent
Resumo
This paper presents the architecture, structure of knowledge base, and the organization of the prototype of Leibniz pedagogical agent. This agent works as an educational assistant for Differential and Integral Calculus classes. Main innovative aspect present in this agent is the approach taken to model the interaction processes between students and teacher, which is based on Pedagogical Negotiation concepts. Another innovation is the inference mechanism used to detect divergences in the negotiation process. This mechanism allows probabilistic estimation of divergences in expected answers, combining a symbolic matcher of mathematical formulas with a bayesian networks inference engine. After an initial discussion about related work, the paper presents the theoretical foundations of Leibniz, shows the architecture of the agent, and the structure of its knowledge base. The organization of the prototype is also shown, including its inference process, interface facilities, and an example of use. The paper is finished with the presentation of some initial results.Referências
BAKER, M.J. 1994. A model for negotiation in teaching-learning dialogues. Journal of Artificial Intelligence in Education, 5 (2): 199-254.
BALDINO, R. R. 1995. Cálculo infinitesimal: passado ou futuro? Temas & Debates. Sociedade Brasileira de Educação Matemática, 6: 5-21.
BALDINO, R. R. 1997. Student Strategies in Solidarity Assimilation Groups. In Zack, V. Mousley, J. Breen, C. (Eds.) Developing Practice: Teacher's inquiry and educational change (pp. 123-134). Geelong, Australia: Deakin University.
BALDINO, R. R. 1998. Desenvolvimento de Essências de Cálculo Infinitesimal. Rio de Janeiro: MEM/US BALDINO, R. R. and SILVA, R. H. da 2001. Introdução ao processamento de imagens ou aplicação da álgebra linear? Revista de Matemática e Estatística, V. 19, p. 123-144. São Paulo: Editora da UNESP. (25/06/98)
BECK, J., STERN, M., and HAUGSJAA, E. 1996. Applications of AI in education. Crossroads 3, 1 (Sep. 1996), 11-15. [link]
BUNT A. and CONATI C. 2003. Probabilistic Student Modelling to Improve Exploratory Behaviour. Journal of User Modeling and User-Adapted Interaction, 13 (3): 269-309.
CABRAL, T. C. B. 2005. Ensino e Aprendizagem de Matemática na Engenharia e o Uso de Tecnologia. RENOTE – Revista Novas Tecnologias na Educação, 3(2), nov. Porto Alegre: UFRGS, CINTED.
CONATI, C., GERTNER, A., VANLEHN, K. 2002. Using Bayesian Networks to Manage Uncertainty in Student Modeling. Journal of User Modeling and User-Adapted Interaction, 12(4): 371-417.
COWEL, R., DAWID, P.R., LAURITZEN, S. L. and SPIEGELHALTER, D. J. 1999. Probabilistic Networks and Expert Systems. New York: Springer-Verlag.
CURY, H. N. 2004. Análise de Erros em Educação Matemática, In: Veritati, Salvador, 3(4): 95-107.
FERNANDEZ-MANJON, B., CIGARRAN, J. M., NAVARRO, A. and FERNANDEZ-VALMAYOR, A. 1998. Using Automatic Methods for Structuring Conceptual Knowledge in Intelligent Learning Environments. In: ITS98 Conference, San Antonio, Texas, 1998. Proceedings ..., p. 264 – 273.
FLORES, C.D., SEIXAS, L.J., GLUZ, J.C., PATRICIO, D., GIACOMEL, L., GONÇALVES, L. and VICARI, R.M. 2004. Amplia Learning Environment Architecture. Revista Tecnologia da Informação, 4(1): 27-36, nov.
FLORES, C.D., SEIXAS, L., GLUZ, J.C. and VICARI, R.M. 2005. A Model for Pedagogical Negotiation. In: EPIA 2005 Conference, Portugal, 2005. Lecture Notes in Computer Science, 3008(2005): 488-499.
GLUZ, J. C. A Biblioteca FACIL (FIPA-ACL Interface Library). 2002. 64p. Trabalho Individual de Pesquisa, Instituto de Informática, UFRGS, Porto Alegre.
GLUZ, J. C. and VICCARI, R. M. 2003. Linguagens de Comunicação entre Agentes: Fundamentos Padrões e Perspectivas. In: JORNADA DE MINI-CURSOS DE INTELIGÊNCIA ARTIFICIAL, 3. Campinas, 2003. Livro Texto. Campinas: SBC, p. 53-102.
GLUZ, J. C., FLORES, C. D. and VICARI, R. M. 2006. Formal Aspects of Pedagogical Negotiation in AMPLIA System. To appear in: NEDJAH, N. and MOURELLE, L. M. (eds.) Intelligent Educational Machines. Series: Intelligent Systems Engineering Book Series. Springer-Verlag, 2006.
GÜRER, D. 1998. The Use of Distributed Agents in Intelligent Tutoring. In: 2nd ITS Workshop on Pedagogical Agents, San Antonio, Texas. Proceedings ... p. 20-25.
MARIANI, V. C. 2005. Análise de Erros em Cálculo Diferencial e Integral nos Cursos de Engenharia. In: COBENGE 2005, Campina Grande, 2005. Anais ...
MAXIMA. 2007. Maxima, a computer algebra system. [link]
MURRAY, C., VANLEHN, K. and MOSTOW, J. 2001. A Decision-Theoretic Architecture for Selecting Tutorial Discourse Actions. In: AIED-2001 Workshop on Tutorial Dialogue Systems, 2001. Proceedings ...
PEARL, J. Belief Networks Revisited. 1993. Artificial Intelligence, Amsterdan, 59: 49-56.
PIAGET, J., 1970. The book, L’Épistémologie Génétique, Paris.
SANDHOLM, T. W. 1999. Distributed Rational Decision Making. In: WEISS, G. (ed.). Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. Cambridge: The MIT Press, p.79-120.
SCHWARZ, B.B., NEUMAN, Y., GIL, J. and ILYA, M. 2001. Effects of argumentative activities on collective and individual arguments. In: European Conference on Computer-Supported Collaborative Learning – Euro-CSCL 2001, Maastricht, 22 - 24 March 2001. Proceedings ...
SEIXAS, L.J., VICARI, R.M. and FAGUNDES, L.C. 2006. Pedagogic Strategies Based on the Student Cognitive Model Using the Constructivist Approach. To appear in: NEDJAH, N. and MOURELLE, L. M. (eds.) Intelligent Educational Machines. Series: Intelligent Systems Engineering Book Series. Springer/Nova, 2006.
SELF, J. Computational Viewpoints. 1992. In: MOYSE, R. and ELSOM-COOK, M. (eds.) Knowledge Negotiation. Paul Chapman, London, p. 21-40.
SELF, J. A. 1998. Hanging by Two Threads: The Evolution of Intelligent Tutoring Systems Research. In: ITS98 Conference, San Antonio, Texas, 1998. Proceedings ...
VICARI, R.M., FLORES, C.D., SILVESTRE, A.M., SEIXAS, L.J., LADEIRA, M. and COELHO, H. 2003. A multi-agent intelligent environment for medical knowledge. Artificial Intelligence in Medicine, Elsevier, 27: 335-366.
BALDINO, R. R. 1995. Cálculo infinitesimal: passado ou futuro? Temas & Debates. Sociedade Brasileira de Educação Matemática, 6: 5-21.
BALDINO, R. R. 1997. Student Strategies in Solidarity Assimilation Groups. In Zack, V. Mousley, J. Breen, C. (Eds.) Developing Practice: Teacher's inquiry and educational change (pp. 123-134). Geelong, Australia: Deakin University.
BALDINO, R. R. 1998. Desenvolvimento de Essências de Cálculo Infinitesimal. Rio de Janeiro: MEM/US BALDINO, R. R. and SILVA, R. H. da 2001. Introdução ao processamento de imagens ou aplicação da álgebra linear? Revista de Matemática e Estatística, V. 19, p. 123-144. São Paulo: Editora da UNESP. (25/06/98)
BECK, J., STERN, M., and HAUGSJAA, E. 1996. Applications of AI in education. Crossroads 3, 1 (Sep. 1996), 11-15. [link]
BUNT A. and CONATI C. 2003. Probabilistic Student Modelling to Improve Exploratory Behaviour. Journal of User Modeling and User-Adapted Interaction, 13 (3): 269-309.
CABRAL, T. C. B. 2005. Ensino e Aprendizagem de Matemática na Engenharia e o Uso de Tecnologia. RENOTE – Revista Novas Tecnologias na Educação, 3(2), nov. Porto Alegre: UFRGS, CINTED.
CONATI, C., GERTNER, A., VANLEHN, K. 2002. Using Bayesian Networks to Manage Uncertainty in Student Modeling. Journal of User Modeling and User-Adapted Interaction, 12(4): 371-417.
COWEL, R., DAWID, P.R., LAURITZEN, S. L. and SPIEGELHALTER, D. J. 1999. Probabilistic Networks and Expert Systems. New York: Springer-Verlag.
CURY, H. N. 2004. Análise de Erros em Educação Matemática, In: Veritati, Salvador, 3(4): 95-107.
FERNANDEZ-MANJON, B., CIGARRAN, J. M., NAVARRO, A. and FERNANDEZ-VALMAYOR, A. 1998. Using Automatic Methods for Structuring Conceptual Knowledge in Intelligent Learning Environments. In: ITS98 Conference, San Antonio, Texas, 1998. Proceedings ..., p. 264 – 273.
FLORES, C.D., SEIXAS, L.J., GLUZ, J.C., PATRICIO, D., GIACOMEL, L., GONÇALVES, L. and VICARI, R.M. 2004. Amplia Learning Environment Architecture. Revista Tecnologia da Informação, 4(1): 27-36, nov.
FLORES, C.D., SEIXAS, L., GLUZ, J.C. and VICARI, R.M. 2005. A Model for Pedagogical Negotiation. In: EPIA 2005 Conference, Portugal, 2005. Lecture Notes in Computer Science, 3008(2005): 488-499.
GLUZ, J. C. A Biblioteca FACIL (FIPA-ACL Interface Library). 2002. 64p. Trabalho Individual de Pesquisa, Instituto de Informática, UFRGS, Porto Alegre.
GLUZ, J. C. and VICCARI, R. M. 2003. Linguagens de Comunicação entre Agentes: Fundamentos Padrões e Perspectivas. In: JORNADA DE MINI-CURSOS DE INTELIGÊNCIA ARTIFICIAL, 3. Campinas, 2003. Livro Texto. Campinas: SBC, p. 53-102.
GLUZ, J. C., FLORES, C. D. and VICARI, R. M. 2006. Formal Aspects of Pedagogical Negotiation in AMPLIA System. To appear in: NEDJAH, N. and MOURELLE, L. M. (eds.) Intelligent Educational Machines. Series: Intelligent Systems Engineering Book Series. Springer-Verlag, 2006.
GÜRER, D. 1998. The Use of Distributed Agents in Intelligent Tutoring. In: 2nd ITS Workshop on Pedagogical Agents, San Antonio, Texas. Proceedings ... p. 20-25.
MARIANI, V. C. 2005. Análise de Erros em Cálculo Diferencial e Integral nos Cursos de Engenharia. In: COBENGE 2005, Campina Grande, 2005. Anais ...
MAXIMA. 2007. Maxima, a computer algebra system. [link]
MURRAY, C., VANLEHN, K. and MOSTOW, J. 2001. A Decision-Theoretic Architecture for Selecting Tutorial Discourse Actions. In: AIED-2001 Workshop on Tutorial Dialogue Systems, 2001. Proceedings ...
PEARL, J. Belief Networks Revisited. 1993. Artificial Intelligence, Amsterdan, 59: 49-56.
PIAGET, J., 1970. The book, L’Épistémologie Génétique, Paris.
SANDHOLM, T. W. 1999. Distributed Rational Decision Making. In: WEISS, G. (ed.). Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence. Cambridge: The MIT Press, p.79-120.
SCHWARZ, B.B., NEUMAN, Y., GIL, J. and ILYA, M. 2001. Effects of argumentative activities on collective and individual arguments. In: European Conference on Computer-Supported Collaborative Learning – Euro-CSCL 2001, Maastricht, 22 - 24 March 2001. Proceedings ...
SEIXAS, L.J., VICARI, R.M. and FAGUNDES, L.C. 2006. Pedagogic Strategies Based on the Student Cognitive Model Using the Constructivist Approach. To appear in: NEDJAH, N. and MOURELLE, L. M. (eds.) Intelligent Educational Machines. Series: Intelligent Systems Engineering Book Series. Springer/Nova, 2006.
SELF, J. Computational Viewpoints. 1992. In: MOYSE, R. and ELSOM-COOK, M. (eds.) Knowledge Negotiation. Paul Chapman, London, p. 21-40.
SELF, J. A. 1998. Hanging by Two Threads: The Evolution of Intelligent Tutoring Systems Research. In: ITS98 Conference, San Antonio, Texas, 1998. Proceedings ...
VICARI, R.M., FLORES, C.D., SILVESTRE, A.M., SEIXAS, L.J., LADEIRA, M. and COELHO, H. 2003. A multi-agent intelligent environment for medical knowledge. Artificial Intelligence in Medicine, Elsevier, 27: 335-366.
Publicado
16/04/2007
Como Citar
GLUZ, João Carlos; CABRAL, Tânia; BAGGIO, Paulo; LIVI, Paulo.
Helping students of introductory calculus classes: the Leibniz pedagogical agent. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 1. , 2007, Pelotas/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2007
.
p. 51-64.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2007.33034.