Um modelo de treinamento adaptativo da habilidade metacognitiva de monitoramento do conhecimento
Resumo
Saber identificar o que se sabe e o que não se sabe em um determinado domínio de conhecimento é uma habilidade metacognitiva fundamental para o sucesso da aprendizagem. No entanto, poucos trabalhos se preocuparam em desenvolver um modelo de instrução específico para a melhora desta habilidade. Este artigo apresenta o modelo e a implementação de um agente que treina a habilidade de monitoramento do conhecimento através de uma instrução que se adapta a características do aprendiz e ao seu histórico de resolução de tarefas. O agente foi integrado a um Sistema Tutor Inteligente e uma avaliação experimental foi realizada com 63 alunos. A avaliação apresentou algumas evidências positivas em relação a benefícios do uso do agente metacognitivo.
Palavras-chave:
Aprendizagem, metacognição, monitoramento do conhecimento
Referências
Aleven, V., Mclaren, B., Koedinger, K. e Rool, I. (2006) Toward Meta-Cognitive Tutoring: A Model of Help-Seeking with a Cognitive Tutor. International Journal of Artificial Intelligence in Education, vol. 16, p. 101-130.
Azevedo, R., Feyzi-Behnagh, R. F., Duffy, M., Harley, J. M. e Trevors, G. (2012) Metacognition and self-regulated learning in student-centered leaning environments. In: D. Jonassen e S. Land (Eds.) Theoretical foundations of student-center learning environments, New York: Routledge, n. 2, pp. 171–197.
Azevedo, R. e Hadwin, A. F. (2005) Scaffolding Self-regulated Learning and Metacognition. Instructional Science, v. 33, n. 5-6, p. 367-379.
Blackwood, T. (2013) Business undergraduates’ knowledge monitoring accuracy: how much do they know about how much they know? Teaching in HE, NY,v.18,p. 65-77.
Brown, A. L. (1977) Knowing When, Where, and How to Remember: A Problem of Metacognition. Technical Report n. 47, Washington.
Desoete, A., Roeyers, H. e De Clercq, A. (2003) Can Offline Metacognition Enhance Mathematical Problem Solving? Journal of E.P., Washington, v.95, n. 1, p. 188-200.
Dunlosky, J. e Metcalfe, J. (2009) Metacognition. SAGE, Los Angeles.
Flavell, J. (1979) Metacognition and cognitive monitoring: A new area of cognitivedevelopmental inquiry. American Psychologist, v. 34, n. 10, p. 906–911.
Fogarty, R. (1994) How to Teach for Metacognitive Reflection. Pearson, Glenview.
Gama, C. A. (2004) Integrating Metacognition Instruction in Interactive Learning Environments. Thesis (PhD), University of Sussex, Brighton.
Jaques, P. A., Seffrin, H., Rubi, G., Morais, F. de, Ghilardi, C., Bittencourt, I. I. e Isotani, S. (2013) Rule-based expert systems to support step-by-step guidance in algebraic problem solving: the case of the tutor PAT2math. Expert Systems with Applications, v. 40, n. 14, p. 5456–5465.
Jaques, P. A. e Nunes, M. A. S. N. (2012) Ambientes Inteligentes de Aprendizagem que inferem, expressam e possuem emoções e personalidade. In: Isotani, S.; Campos, F. JAIE. Congresso Brasileiro de Informática na Educação. RJ: UFRJ, p. 31-82.
Kramarski, B. e Michalsky, T. (2013) Student and Teacher Perspectives on IMPROVE Self-Regulation Prompts in Web-Based Learning. In: R. Azevedo e V. Aleven (Eds.) International Handbook of Metacognition and Learning, Springer, NY.
Lester, J. C., Converse, S. A., Kahler, S. E., Barlow, S. T., Stone, B. A. e Bhogal, R. S. (1997) The persona effect: Affective impact of animated pedagogical agents. SIGCHI Conference on Human Factors in Computing Systems, Atlanta.
Lin, X. (2001) Designing Metacognitive Activities. Educational Technology Research and Development, v. 49, n. 2, p. 23-40.
Polya, G. (1957) How to Solve It. Princeton University Press, Garden City, NY.
Seffrin, H. e Jaques, P. (2014) Modelando o conhecimento algébrico do estudante através de Redes Bayesianas Dinâmicas. In: SBIE, Dourados, MT, SBC.
Stavrianopoulous, K. (2007) Adolescent’s Metacognitive Knowledge Monitoring and Academic Help Seeking. College Student Journal, v. 41, n. 2, p. 444-453.
Tobias, S. e Everson, H. (2002) Knowing What You Know and What You Don’t: Further Research on Metacognitive Knowledge Monitoring. Research Report, The College Board, New York, n. 2002-3, p. 1-25.
Tobias, S. e Everson, H. (2009) The Importance of Knowing What You Know: A Knowledge Monitoring Framework for Studying Metacognition. In: D. J. Hacker, J. Dunlosky e A. C. Graesser (Eds.) Handbook of Metacognition in Education, NY.
VanLehn, K. (2006) The Behavior of Tutoring Systems. International Journal of Artificial Intelligence in Education, v. 16, n. 3, p. 227–265.
Veenman, M. V. J., Hout-Wolters, B. H. A. M. Van e Afflerbach, P. (2006) Metacognition and learning: conceptual and methodological considerations. Metacognition Learning, v.1, n. 1, p. 3-14.
Verschaffel, L. (1999) Realistic mathematical modelling and problem solving in the upper elementary school: analysis and improvement. In: J. H. M. Hamers, J. E. H. Luit, B. Csapó (Eds.) Teaching and learning thinking skills, Lisse, The Netherlands.
Woolf, B. P. (2009) Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann, San Francisco, CA.
Woolf, B. P., Reid, J., Stillings, N., Bruno, M., Murray, D., Reese, P., Peterfreund, A. e Rath, K. (2002) A General Platform for Inquiry Learning. In: International Conference of Intelligent Tutoring Systems, Springer Berlin Heidelberg, NY.
Azevedo, R., Feyzi-Behnagh, R. F., Duffy, M., Harley, J. M. e Trevors, G. (2012) Metacognition and self-regulated learning in student-centered leaning environments. In: D. Jonassen e S. Land (Eds.) Theoretical foundations of student-center learning environments, New York: Routledge, n. 2, pp. 171–197.
Azevedo, R. e Hadwin, A. F. (2005) Scaffolding Self-regulated Learning and Metacognition. Instructional Science, v. 33, n. 5-6, p. 367-379.
Blackwood, T. (2013) Business undergraduates’ knowledge monitoring accuracy: how much do they know about how much they know? Teaching in HE, NY,v.18,p. 65-77.
Brown, A. L. (1977) Knowing When, Where, and How to Remember: A Problem of Metacognition. Technical Report n. 47, Washington.
Desoete, A., Roeyers, H. e De Clercq, A. (2003) Can Offline Metacognition Enhance Mathematical Problem Solving? Journal of E.P., Washington, v.95, n. 1, p. 188-200.
Dunlosky, J. e Metcalfe, J. (2009) Metacognition. SAGE, Los Angeles.
Flavell, J. (1979) Metacognition and cognitive monitoring: A new area of cognitivedevelopmental inquiry. American Psychologist, v. 34, n. 10, p. 906–911.
Fogarty, R. (1994) How to Teach for Metacognitive Reflection. Pearson, Glenview.
Gama, C. A. (2004) Integrating Metacognition Instruction in Interactive Learning Environments. Thesis (PhD), University of Sussex, Brighton.
Jaques, P. A., Seffrin, H., Rubi, G., Morais, F. de, Ghilardi, C., Bittencourt, I. I. e Isotani, S. (2013) Rule-based expert systems to support step-by-step guidance in algebraic problem solving: the case of the tutor PAT2math. Expert Systems with Applications, v. 40, n. 14, p. 5456–5465.
Jaques, P. A. e Nunes, M. A. S. N. (2012) Ambientes Inteligentes de Aprendizagem que inferem, expressam e possuem emoções e personalidade. In: Isotani, S.; Campos, F. JAIE. Congresso Brasileiro de Informática na Educação. RJ: UFRJ, p. 31-82.
Kramarski, B. e Michalsky, T. (2013) Student and Teacher Perspectives on IMPROVE Self-Regulation Prompts in Web-Based Learning. In: R. Azevedo e V. Aleven (Eds.) International Handbook of Metacognition and Learning, Springer, NY.
Lester, J. C., Converse, S. A., Kahler, S. E., Barlow, S. T., Stone, B. A. e Bhogal, R. S. (1997) The persona effect: Affective impact of animated pedagogical agents. SIGCHI Conference on Human Factors in Computing Systems, Atlanta.
Lin, X. (2001) Designing Metacognitive Activities. Educational Technology Research and Development, v. 49, n. 2, p. 23-40.
Polya, G. (1957) How to Solve It. Princeton University Press, Garden City, NY.
Seffrin, H. e Jaques, P. (2014) Modelando o conhecimento algébrico do estudante através de Redes Bayesianas Dinâmicas. In: SBIE, Dourados, MT, SBC.
Stavrianopoulous, K. (2007) Adolescent’s Metacognitive Knowledge Monitoring and Academic Help Seeking. College Student Journal, v. 41, n. 2, p. 444-453.
Tobias, S. e Everson, H. (2002) Knowing What You Know and What You Don’t: Further Research on Metacognitive Knowledge Monitoring. Research Report, The College Board, New York, n. 2002-3, p. 1-25.
Tobias, S. e Everson, H. (2009) The Importance of Knowing What You Know: A Knowledge Monitoring Framework for Studying Metacognition. In: D. J. Hacker, J. Dunlosky e A. C. Graesser (Eds.) Handbook of Metacognition in Education, NY.
VanLehn, K. (2006) The Behavior of Tutoring Systems. International Journal of Artificial Intelligence in Education, v. 16, n. 3, p. 227–265.
Veenman, M. V. J., Hout-Wolters, B. H. A. M. Van e Afflerbach, P. (2006) Metacognition and learning: conceptual and methodological considerations. Metacognition Learning, v.1, n. 1, p. 3-14.
Verschaffel, L. (1999) Realistic mathematical modelling and problem solving in the upper elementary school: analysis and improvement. In: J. H. M. Hamers, J. E. H. Luit, B. Csapó (Eds.) Teaching and learning thinking skills, Lisse, The Netherlands.
Woolf, B. P. (2009) Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann, San Francisco, CA.
Woolf, B. P., Reid, J., Stillings, N., Bruno, M., Murray, D., Reese, P., Peterfreund, A. e Rath, K. (2002) A General Platform for Inquiry Learning. In: International Conference of Intelligent Tutoring Systems, Springer Berlin Heidelberg, NY.
Publicado
26/10/2015
Como Citar
KAUTZMANN, Tiago Roberto; JAQUES, Patricia.
Um modelo de treinamento adaptativo da habilidade metacognitiva de monitoramento do conhecimento. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 26. , 2015, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2015
.
p. 1092-1101.
DOI: https://doi.org/10.5753/cbie.sbie.2015.1092.
