Simulação de Aprendizagem em Estudantes como Ferramenta para Minimização de Custos na Avaliação de Novas Abordagens em Sistemas Adaptativos e Inteligentes para Educação a Distância: Uma Análise Experimental
Resumo
A modelagem automática de estilos de aprendizagem do estudante em sistemas adaptativos e inteligentes para educação é uma área de pesquisa em crescimento, e caracteriza um grande desafio em Informática na Educação. Uma dificuldade, neste caso, está em experimentar, avaliar e validar novas abordagens para modelagem automática do estudante antes destas serem efetivamente implantadas em sistemas adaptativos e inteligentes para educação. Desta forma, este trabalho apresenta uma abordagem para a avaliação desses sistemas, com foco na simulação da aprendizagem em estudantes com base em seus estilos de aprendizagem e de como o sistema educacional os atende ao longo do curso. Como resultado deste trabalho, obteve-se a experimentação e validação de uma nova abordagem para modelagem automática de estilos de aprendizagem num curto espaço de tempo e sem qualquer custo.
Palavras-chave:
simulação computacional, experimentação de modelos computacionais, sistemas adaptativos e inteligentes para educação, modelagem do estudante, estilos de aprendizagem
Referências
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Vanlehn, K., Ohlsson, S., e Nason, R. (1994). Applications of simulated students: An exploration. Journal of articial intelligence in education, 5:135–135.
Vasilyeva, E., Pechenizkiy, M., e Puuronen, S. (2006). The Challenge of Feedback Personalization to Learning Styles in a Web-Based Learning System. In Advanced Learning Technologies, 2006. Sixth International Conference on, pages 1143–1144. IEEE.
Virvou, M., Manos, K., e Katsionis, G. (2003). An evaluation agent that simulates students’ behaviour in intelligent tutoring systems. In IEEE International Conference on Systems, Man and Cybernetics, 2003, volume 5, pages 4872–4877. IEEE, IEEE.
Vizcaino, A. e du Boulay, B. (2002). Using a simulated student to repair difculties in collaborative learning. In ICCE ’02 Proceedings of the International Conference on Computers in Education. ACM, IEEE Computer Society Washington, DC, USA.
Al-Dujaily, A. e Ryu, H. (2006). A relationship between e-learning performance and personality. In Advanced Learning Technologies, 2006. Sixth International Conference on, pages 84–86. IEEE.
Alfonseca, E., Carro, R., Martín, E., Ortigosa, A., e Paredes, P. (2006). The impact of learning styles on student grouping for collaborative learning: a case study. User Modeling and User-Adapted Interaction, 16(3):377–401.
Bajraktarevic, N., Hall, W., e Fullick, P. (2003). Incorporating learning styles in hypermedia environment: Empirical evaluation. In Proceedings of the workshop on adaptive hypermedia and adaptive web-based systems, pages 41–52.
Bravo, J. e Ortigosa, A. (2006). Validating the evaluation of adaptive systems by user prole simulation. In Proceedings of Workshop held at the Fourth International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH2006), pages 479–483.
Castillo, G., Gama, J., e Breda, A. (2005). An Adaptive Predictive Model for Student Modeling. Advances in Web-based education: Personalized learning environments, pages 70–92.
Cofeld, F., Moseley, D., Hall, E., e Ecclestone, K. (2009). Learning styles and pedagogy in post-16 learning: A systematic and critical review. National Centre for Vocational Education Research (NCVER).
Dorça, F. A., Lima, L. V., Fernandes, M. A., e Lopes, C. R. (2013). Comparing strategies for modeling students learning styles through reinforcement learning in adaptive and intelligent educational systems: An experimental analysis. Expert Systems with Applications. http://dx.doi.org/10.1016/j.eswa.2012.10.014.
Dorça, F. A., Lima, L. V., Fernandes, M. A., e Lopes, C. R. (2011). A new approach to discover students learning styles in adaptive educational systems. In XXII Simpósio Brasileiro de Informática na Educação.
Felder, R. e Silverman, L. (1988). Learning and teaching styles in engineering education. Journal of Engineering education, 78(7):674–681.
Graf, S. e Kinshuk (2009). Advanced Adaptivity in Learning Management Systems by Considering Learning Styles. In Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology-Volume 03, pages 235–238. IEEE Computer Society.
Graf, S. e Kinshuk, C. (2010). A Flexible Mechanism for Providing Adaptivity Based In 10th IEEE International on Learning Styles in Learning Management Systems. Conference on Advanced Learning Technologies, pages 30–34. IEEE.
Graf, S. e Kinshuk, K. (2007). Providing Adaptive Courses in Learning Management Systems with Respect to Learning Styles. In Proceedings of World Conference on ELearning in Corporate, Government, Healthcare, and Higher Education 2007, pages 2576–2583.
Graf, S., Lan, C., Liu, T., et al. (2009). Investigations about the Effects and Effectiveness of Adaptivity for Students with Different Learning Styles. In 2009 Ninth IEEE International Conference on Advanced Learning Technologies, pages 415–419. IEEE.
Graf, S. e Lin, T. (2007). Analysing the Relationship between Learning Styles and Cognitive Traits. In Advanced Learning Technologies, 2007. ICALT 2007. Seventh IEEE International Conference on, pages 235–239. IEEE.
Graf, S. e Liu, T. (2008). Identifying Learning Styles in Learning Management Systems by Using Indications from Students’ Behaviour. In Advanced Learning Technologies, 2008. ICALT’08. Eighth IEEE International Conference on, pages 482–486. IEEE.
Graf, S., Liu, T.-C., e Kinshuk (2008). Interactions Between Students Learning Styles, Achievement and Behaviour in Mismatched Courses. In Proceedings of the Internatio1328 nal Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2008), pages 223–230. IADIS International Conference.
Haider, M., Sinha, A., e Chaudhary, B. (2010). An Investigation of relationship between International Journal of Engineering learning styles and performance of learners. Science and Technology, 2(7):2813–2819.
Kinshuk, Liu, T., e Graf, S. (2009). Coping with Mismatched Courses: Students’ behaviour and performance in courses mismatched to their learning styles. Educational Technology Research and Development, 57(6):739–752.
Lim, H., Lee, S., e Nam, K. (2007). Validating e-learning factors affecting training effectiveness. International Journal of Information Management, 27(1):22–35.
Mertz, J. (1997). Using a simulated student for instructional design. International Journal of Articial Intelligence in Education (IJAIED), 8:116–141.
Moodle (2010). http://www.moodle.org/.
Mosakhani, M. e Jamporazmey, M. (2010). Introduce critical success factors (CSFs) In Educational and of elearning for evaluating e-learning implementation success. Information Technology (ICEIT), 2010 International Conference on, volume 1, pages V1–224. IEEE.
Price, L. (2004). Individual differences in learning: Cognitive control, cognitive style, and learning style. Educational Psychology, 24(5):681–698.
Sangineto, E., Capuano, N., Gaeta, M., e Micarelli, A. (2008). Adaptive course generation through learning styles representation. Universal Access in the Information Society, 7(1):1–23.
Santos, O. e Boticario, J. (2008). Recommendation strategies for promoting eLearning performance factors for all. In 6th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems in conjunction with The 23nd AAAI Conference on Articial Intelligence-2008.
Starr, C., Manaris, B., e Stalvey, R. (2008). Bloom’s taxonomy revisited: specifying assessable learning objectives in computer science. ACM SIGCSE Bulletin, 40(1):261– 265.
Vanlehn, K., Ohlsson, S., e Nason, R. (1994). Applications of simulated students: An exploration. Journal of articial intelligence in education, 5:135–135.
Vasilyeva, E., Pechenizkiy, M., e Puuronen, S. (2006). The Challenge of Feedback Personalization to Learning Styles in a Web-Based Learning System. In Advanced Learning Technologies, 2006. Sixth International Conference on, pages 1143–1144. IEEE.
Virvou, M., Manos, K., e Katsionis, G. (2003). An evaluation agent that simulates students’ behaviour in intelligent tutoring systems. In IEEE International Conference on Systems, Man and Cybernetics, 2003, volume 5, pages 4872–4877. IEEE, IEEE.
Vizcaino, A. e du Boulay, B. (2002). Using a simulated student to repair difculties in collaborative learning. In ICCE ’02 Proceedings of the International Conference on Computers in Education. ACM, IEEE Computer Society Washington, DC, USA.
Publicado
23/07/2013
Como Citar
DORÇA, Fabiano A.; LIMA, Luciano V.; FERNANDES, Márcia A.; LOPES, Carlos R..
Simulação de Aprendizagem em Estudantes como Ferramenta para Minimização de Custos na Avaliação de Novas Abordagens em Sistemas Adaptativos e Inteligentes para Educação a Distância: Uma Análise Experimental. In: WORKSHOP DE DESAFIOS DA COMPUTAÇÃO APLICADA À EDUCAÇÃO (DESAFIE!), 2. , 2013, Maceió.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2013
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p. 1320-1329.
