Treinamento da Habilidade Metacognitiva de Monitoramento do Conhecimento em Sistemas Tutores

Tiago Roberto Kautzmann, Patricia Augustin Jaques

Resumo


Alunos que possuem habilidades metacognitivas estudam mais estrategicamente, buscam o conhecimento em áreas deficitárias e controlam sua aprendizagem. A habilidade fundamental para o desenvolvimento de outras habilidades metacognitivas é a de monitoramento do conhecimento. Apesar de diversos trabalhos encorajarem os estudantes a monitorarem o próprio conhecimento, não se conhece estudos que investigaram os efeitos de um treinamento específico desta habilidade. Além disso, sabe-se que uma característica fundamental para o sucesso do treinamento metacognitivo é a sua individualização. Porém, não se tem conhecimento de estudos envolvendo ambientes computacionais de aprendizagem que adaptem a etapa do treinamento de reflexão do conhecimento a características do aprendiz. O presente estudo propõe um treinamento adaptativo específico da habilidade de monitoramento do conhecimento em sistemas tutores inteligentes. Um agente pedagógico animado que realiza o treinamento proposto foi implementado e integrado a um sistema tutor algébrico. Os resultados de uma avaliação experimental sugerem que os alunos que receberam o treinamento proposto melhoraram a habilidade de monitoramento do conhecimento e o desempenho no domínio.

Palavras-chave


Habilidade de Monitoramento do Conhecimento; Metacognição; Agente Pedagógico Animado; Sistemas Tutores Inteligentes

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Referências


Aleven, V., Mclaren, B., Roll, I., & Koedinger, K. (2006). Toward meta-cognitive tutoring: A model of help seeking with a Cognitive Tutor. International Journal of Artificial Intelligence in Education, 16(2), 101-128. [Google Scholar]

Azevedo, R., & Aleven, V. A. (2013). International handbook of metacognition and learning technologies (Vol. 26). New York: Springer. [Google Scholar]

Azevedo, R., & Hadwin, A. F. (2005). Scaffolding self-regulated learning and metacognition–Implications for the design of computer-based scaffolds. Instructional Science, 33(5), 367-379. DOI:10.1007/s11251-005-1272-9 [Google Scholar]

Azevedo, R., Behnagh, R., Duffy, M., Harley, J., & Trevors, G. (2012). Metacognition and self-regulated learning in student-centered leaning environments. Theoretical foundations of student-centered learning environments, 171-197. [Google Scholar]

Azevedo, R., Harley, J., Trevors, G., Duffy, M., Feyzi-Behnagh, R., Bouchet, F., & Landis, R. (2013). Using trace data to examine the complex roles of cognitive, metacognitive, and emotional self-regulatory processes during learning with multi-agent systems. In International handbook of metacognition and learning technologies (pp. 427-449). Springer New York. DOI:10.1007/978-1-4419-5546-3_28 [Google Scholar]

Bannert, M. (2006). Effects of reflection prompts when learning with hypermedia. Journal of Educational Computing Research, 35(4), 359-375. DOI:10.2190/94V6-R58H-3367-G388 [Google Scholar]

Bielaczyk, K., Pirolli, P. L., & Brown, A. L. (1995). Training in Self-Explanation Strategies: Self-Regulation the Effects of Investigating Knowledge Acquisition Activities on Problem Solving. Cognition and Instruction. [Google Scholar]

Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational researcher, 13(6), 4-16. DOI:10.3102/0013189X013006004 [Google Scholar]

Bocca, E. W. (2003). Modelagem e implementação da interface para apresentação de comportamentos animados e emotivos de um agente pedagógico animado. (Master's thesis, Instituto de Informática, UFRGS). [Google Scholar]

Boud, D., & Falchikov, N. (1989). Quantitative studies of student self-assessment in higher education: A critical analysis of findings. Higher education, 18(5), 529-549. DOI:10.1007/BF00138746 [Google Scholar]

Burns, H. L., & Capps, C. G. (1988). Foundations of intelligent tutoring systems: An introduction. [Google Scholar]

Chi, M. T., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989). Self‐explanations: How students study and use examples in learning to solve problems. Cognitive science, 13(2), 145-182. DOI:10.1207/s15516709cog1302_1 [Google Scholar]

Chi, M. T., Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self‐explanations improves understanding. Cognitive science, 18(3), 439-477. DOI:10.1207/s15516709cog1803_3 [Google Scholar]

Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological bulletin, 52(4), 281. DOI:10.1037/h0040957 [Google Scholar]

Davis, E. A. (2003). Prompting middle school science students for productive reflection: Generic and directed prompts. The Journal of the Learning Sciences, 12(1), 91-142. DOI:10.1207/S15327809JLS1201_4 [Google Scholar]

Desoete, A., Roeyers, H., & De Clercq, A. (2003). Can offline metacognition enhance mathematical problem solving?. Journal of Educational Psychology, 95(1), 188. DOI:10.1037/0022-0663.95.1.188 [Google Scholar]

Dunlosky, J., & Metcalfe, J. (2009). Metacognition: A textbook of cognition, educational, life span, and applied psychology. Thousand Oaks, CA: Sage.

Ferguson-Hessler, M. G., & de Jong, T. (1990). Studying Physics Texts: Differences in Study Process Between Good and Poor Performers. Cognition and Instruction, 7(1), 41-54. DOI:10.1207/s1532690xci0701_2 [Google Scholar]

Flavell, J. H. (1976). Metacognitive aspects of problem solving. The nature of intelligence, 12, 231-235. Hillsdale. [Google Scholar]

Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American psychologist, 34(10), 906. DOI:10.1037/0003-066X.34.10.906 [Google Scholar]

Fogarty, R. (1994). The Mindful School: How To Teach for Metacognitive Reflection. IRI/Skylight Publishing, Inc. [Google Scholar]

Gama, C. A. (2004). Integrating metacognition instruction in interactive learning environments. (Ph.D. Dissertation, University of Sussex). [Google Scholar]

Gürer, D. (1998). The use of distributed agents in intelligent tutoring. In Proceedings of 2nd ITS Workshop on Pedagogical Agents, San Antonio, Texas (pp. 20-25). [Google Scholar]

Hartman, H. J. (1998). Metacognition in teaching and learning: An introduction. Instructional Science, 26(1-2), 1-3. DOI:10.1023/A:1003023628307 [Google Scholar]

Hartman, H. J. (2001). Teaching metacognitively. In Metacognition in learning and instruction (pp. 149-172). Springer Netherlands. DOI:10.1007/978-94-017-2243-8_8 [Google Scholar]

Jaques, P. A., & Nunes, M. A. S. (2013). Ambientes Inteligentes de Aprendizagem que inferem, expressam e possuem emoções e personalidade. Jornada de Atualização em Informática na Educação, 1(1), 30-81. [JAIE] [Google Scholar]

Jaques, P. A., Seffrin, H., Rubi, G., de Morais, F., Ghilardi, C., Bittencourt, I. I., & 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, 40(14), 5456-5465. DOI:10.1016/j.eswa.2013.04.004 [Google Scholar]

Jennings, N. R., Sycara, K., & Wooldridge, M. (1998). A roadmap of agent research and development. Autonomous agents and multi-agent systems, 1(1), 7-38. DOI:10.1023/A:1010090405266 [Google Scholar]

Koedinger, K. R., & Aleven, V. (2007). Exploring the assistance dilemma in experiments with cognitive tutors. Educational Psychology Review, 19(3), 239-264. DOI:10.1007/s10648-007-9049-0 [Google Scholar]

Kramarski, B., & Michalsky, T. (2013). Student and teacher perspectives on IMPROVE self-regulation prompts in web-based learning. In International handbook of metacognition and learning technologies (pp. 35-51). Springer New York. DOI:10.1007/978-1-4419-5546-3_3 [Google Scholar]

Kramarski, B., Mevarech, Z. R., & Arami, M. (2002). The effects of metacognitive instruction on solving mathematical authentic tasks. Educational studies in mathematics, 49(2), 225-250. DOI:10.1023/A:1016282811724 [Google Scholar]

Lester, J. C., Converse, S. A., Kahler, S. E., Barlow, S. T., Stone, B. A., & Bhogal, R. S. (1997, March). The persona effect: affective impact of animated pedagogical agents. In Proceedings of the ACM SIGCHI Conference on Human factors in computing systems (pp. 359-366). ACM. DOI:10.1145/258549.258797 [Google Scholar]

Lin, X. (2001). Designing metacognitive activities. Educational Technology Research and Development, 49(2), 23-40. DOI:10.1007/BF02504926 [Google Scholar]

Ma, W., Adesope, O. O., Nesbit, J. C., & Liu, Q. (2014). Intelligent tutoring systems and learning outcomes: A meta-analysis. DOI:10.1037/a0037123 [Google Scholar]

Mark, M. A., & Greer, J. E. (1993). Evaluation methodologies for intelligent tutoring systems. Journal of Interactive Learning Research, 4(2), 129. [Google Scholar]

Mayer, R. E. (2011). Applying the science of learning. Boston: Pearson/Allyn & Bacon. [Google Scholar]

Norvig, P., & Russell, S. (2014). Inteligência Artificial, 3a Edição.

Pimentel, E. P., Omar, N., & França, V. F. (2005). Um modelo para Incorporação de Automonitoramento da Aprendizagem em STI. RBIE - Brazilian Journal of Computers in Education / Revista Brasileira de Informática na Educação, 13(1). [RBIE] [Google Scholar]

Pintrich, P. R., Wolters, C. A., & Baxter, G. P. (2000). 2. Assessing Metacognition and Self-Regulated Learning. In Issues in the measurement of metacognition. Lincoln, NE. [Google Scholar]

Polya, G. (2014). How to solve it: A new aspect of mathematical method. Princeton university press. [Google Scholar]

Psotka, J., Massey, L. D., & Mutter, S. A. (Eds.). (1988). Intelligent tutoring systems: Lessons learned. Psychology Press. [Google Scholar]

Reiser, B. J. (2002, January). Why scaffolding should sometimes make tasks more difficult for learners. In Proceedings of the Conference on Computer Support for Collaborative Learning: Foundations for a CSCL Community (pp. 255-264). International Society of the Learning Sciences. [Google Scholar]

Schoenfeld, A. H. (1987). What’s all the fuss about metacognition. Cognitive science and mathematics education, 189.

Seffrin, H. M., Rubi, G., Carlotto, T., Mello, G., & Jaques, P. A. (2009, July). Um resolvedor de equações algébricas como ferramenta de apoio à sala de aula no ensino de equações algébricas. In Anais do Workshop de Informática na Escola (Vol. 1, No. 1, pp. 1791-1800). [Anais do WIE] [Google Scholar]

Seffrin, H., & Jaques, P. (2015, October). Avaliando o conhecimento algébrico dos estudantes através de Redes Bayesianas Dinâmicas. In Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação-SBIE) (Vol. 26, No. 1, p. 987). DOI:10.5753/cbie.sbie.2015.987 [Google Scholar]

Stavrianopoulos, K. (2007). Adolescents' metacognitive knowledge monitoring and academic help seeking: the role of motivation orientation. College Student Journal, 41(2), 444-454. [Google Scholar]

Steenbergen-Hu, S., & Cooper, H. (2013). A meta-analysis of the effectiveness of intelligent tutoring systems on K–12 students’ mathematical learning. [Google Scholar]

Steenbergen-Hu, S., & Cooper, H. (2014). A meta-analysis of the effectiveness of intelligent tutoring systems on college students’ academic learning. DOI:10.1037/a0034752 [Google Scholar]

Tobias, S., & Everson, H. (2009). The Importance of Knowing What You Know: A Knowledge Monitoring Framework for Studying Metacognition. Handbook of Metacognition in Education, NY. [Google Scholar]

Tobias, S., & Everson, H. T. (2000). Assessing metacognitive knowledge monitoring. In Issues in the measurement of metacognition. Lincoln, NE.

Tobias, S., & Everson, H. T. (2002). Knowing what you know and what you don’t: Further research on metacognitive knowledge monitoring. Technical Report 3, The College Board Research Report. [Google Scholar]

Tobias, S., Everson, H. T., Hacker, D. L., Dunlosky, J., & Graesser, A. (2009). The importance of knowing what you know: A knowledge monitoring framework for studying metacognition in education. Handbook of metacognition in education, 107-127. [Google Scholar]

Ullman, M. T. (2004). Contributions of memory circuits to language: The declarative/procedural model. Cognition, 92(1), 231-270. DOI:10.1016/j.cognition.2003.10.008 [Google Scholar]

Vanlehn, K. (2006). The Behavior of Tutoring Systems. International Journal of Artificial Intelligence in Education, 16(3), 227-265. [Google Scholar]

VanLehn, K. (2011). The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems, and Other Tutoring Systems. Educational Psychologist, 46(4), 197-221. DOI:10.1080/00461520.2011.611369 [Google Scholar]

Veenman, M. V., Van Hout-Wolters, B. H., & Afflerbach, P. (2006). Metacognition and learning: Conceptual and methodological considerations. Metacognition and learning, 1(1), 3-14. DOI:10.1007/s11409-006-6893-0 [Google Scholar]

Verschaffel, L. (1999). Realistic mathematical modelling and problem solving in the upper elementary school: Analysis and improvement. [Google Scholar]

Vygotsky, L. (1978). Interaction between learning and development. Readings on the development of children, 23(3), 34-41. [Google Scholar]

Woolf, B. P. (2010). Building intelligent interactive tutors: Student-centered strategies for revolutionizing e-learning. Morgan Kaufmann. [Google Scholar]

Woolf, B. P., Reid, J., Stillings, N., Bruno, M., Murray, D., Reese, P., ... & Rath, K. (2002, June). A general platform for inquiry learning. In International Conference on Intelligent Tutoring Systems (pp. 681-697). Springer Berlin Heidelberg. DOI:10.1007/3-540-47987-2_69 [Google Scholar]

Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of educational psychology, 81(3), 329-339. [Google Scholar]

Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American educational research journal, 45(1), 166-183. DOI:10.3102/0002831207312909 [Google Scholar]




DOI: https://doi.org/10.5753/rbie.2016.24.02.22

DOI (PDF): https://doi.org/10.5753/rbie.2016.24.02.22

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Revista Brasileira de Informática na Educação (RBIE) (ISSN: 1414-5685; online: 2317-6121)
Brazilian Journal of Computers in Education (RBIE) (ISSN: 1414-5685; online: 2317-6121)