Aquisição Automática de Competências num Ambiente Educacional Ubíquo
Resumo
Este artigo apresenta uma proposta que tem como objetivo dotar um ambiente de computação ubíqua de ferramenta que possibilite prover ao usuário um mecanismo para reforço ou alcance de um conjunto de competências. A abordagem faz uso de objetos de aprendizagem adequados ao seu estilo de aprendizagem, que pode ser determinado automaticamente pelo sistema. Para alcançar um conjunto de competências, faz-se necessário um sequenciamento de objetos de aprendizagem a serem apresentados, o que foi obtido por meio de estratégias evolucionárias e algoritmos de busca. Nos experimentos realizados, mostra-se que melhores resultados podem ser obtidos com algoritmos evolucionários.
Palavras-chave:
Objeto de Aprendizagem, Computação Ubíqua, Estratégias Evolucionárias
Referências
Araújo, R., Brant-Ribeiro, T., Cattelan, R., De Amo, S., and Ferreira, H. (2013). Personalization of interactive digital media in ubiquitous educational environments. In IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 3955–3960.
Butz, C., Hua, S., and Maguire, R. (2004). A web-based intelligent tutoring system for computer programming. In IEEE/WIC/ACM Conference on Web Intelligence (WI04).
De Bra, P. and Calvi, L. (1998). AHA! An open adaptive hypermedia architecture. New Review of Hypermedia and Multimedia, 4(1):115–139.
de Marcos, L., Pages, C., Martinez, J., and Gutierrez, J. (2007). Competency-based learning object sequencing using particle swarms. In 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI).
Dorça, F., Lima, L., Fernandes, M., and Lopes, C. (2012). Avaliação de políticas de aprendizagem por reforço para modelagem automática e dinâmica de estilos de aprendizagem: Uma análise experimental. In Simpósio Brasileiro de Informática na Educação (SBIE).
Felder, R. and Silverman, L. (1988). Learning and teaching styles in engineering education. Journal of Engineering education, 78(7):674–681.
Felder, R. and Spurlin, J. (2005). Applications, reliability and validity of the index of learning styles. International Journal of Engineering Education, 21(1):103–112.
García, A., de Marcos, L., García, E., and Gutiérrez, J. A. (2010). Courseware sequencing using heuristic and local search. In Arabnia, H. R., Bahrami, A., and Solo, A. M. G., editors, CSREA EEE, pages 70–75. CSREA Press.
Graf, S., Kinshuk, and Liu, T. (2009). Supporting teachers in identifying students’ learning styles in learning management systems: An automatic student modelling approach. Journal of Educational Technology & Society, 12(4):3–14.
Graf, S., Liu, T.-C., and Kinshuk (2008). Interactions Between Students Learning Styles, Achievement and Behaviour in Mismatched Courses. In Proceedings of the International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2008), pages 223–230. IADIS International Conference.
Graf, S. and Viola, S. (2009). Automatic student modelling for detecting learning style preferences in learning management systems. Citeseer.
IEEE (2010). LOM (Learning Object Metadata). IEEE Learning Technology Standards Committee, [link].
Kinshuk, Liu, T., and 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.
Limongelli, C., Sciarrone, F., Temperini, M., and Vaste, G. (2009). Adaptive learning with the LS-plan system: a field evaluation. IEEE Transactions on Learning Technologies, pages 203–215.
Limongelli, C., Sciarrone, F., Temperini, M., and Vaste, G. (2010). Comparing curriculum sequencing algorithms for intelligent adaptive (e)-learning. In Proceedings of the Conference ICL.
Luke, S. (2013). Essentials of Metaheuristics. Lulu, 2 edition.
Marzano, R. and Kendall, J. (2007). The new taxonomy of educational objectives. Corwin Pr.
Messick, S. (1976). Personal styles and educational options. Individuality in learning, pages 327–368.
Roberts, M. and Erdos, G. (1993). Strategy selection and metacognition. Educational Psychology, 13(3):259–266.
S., A.-M. and Menai, M. (2011). Evolutionary computation approaches to the curriculum sequencing problem. Natural Computing, 10(2):891–920.
Sangineto, E., Capuano, N., Gaeta, M., and Micarelli, A. (2008). Adaptive course generation through learning styles representation. Universal Access in the Information Society, 7(1):1–23.
Weiser, M. (1991). The Computer for the 21st Century. Scient. American, 265(3):66–75.
Butz, C., Hua, S., and Maguire, R. (2004). A web-based intelligent tutoring system for computer programming. In IEEE/WIC/ACM Conference on Web Intelligence (WI04).
De Bra, P. and Calvi, L. (1998). AHA! An open adaptive hypermedia architecture. New Review of Hypermedia and Multimedia, 4(1):115–139.
de Marcos, L., Pages, C., Martinez, J., and Gutierrez, J. (2007). Competency-based learning object sequencing using particle swarms. In 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI).
Dorça, F., Lima, L., Fernandes, M., and Lopes, C. (2012). Avaliação de políticas de aprendizagem por reforço para modelagem automática e dinâmica de estilos de aprendizagem: Uma análise experimental. In Simpósio Brasileiro de Informática na Educação (SBIE).
Felder, R. and Silverman, L. (1988). Learning and teaching styles in engineering education. Journal of Engineering education, 78(7):674–681.
Felder, R. and Spurlin, J. (2005). Applications, reliability and validity of the index of learning styles. International Journal of Engineering Education, 21(1):103–112.
García, A., de Marcos, L., García, E., and Gutiérrez, J. A. (2010). Courseware sequencing using heuristic and local search. In Arabnia, H. R., Bahrami, A., and Solo, A. M. G., editors, CSREA EEE, pages 70–75. CSREA Press.
Graf, S., Kinshuk, and Liu, T. (2009). Supporting teachers in identifying students’ learning styles in learning management systems: An automatic student modelling approach. Journal of Educational Technology & Society, 12(4):3–14.
Graf, S., Liu, T.-C., and Kinshuk (2008). Interactions Between Students Learning Styles, Achievement and Behaviour in Mismatched Courses. In Proceedings of the International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2008), pages 223–230. IADIS International Conference.
Graf, S. and Viola, S. (2009). Automatic student modelling for detecting learning style preferences in learning management systems. Citeseer.
IEEE (2010). LOM (Learning Object Metadata). IEEE Learning Technology Standards Committee, [link].
Kinshuk, Liu, T., and 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.
Limongelli, C., Sciarrone, F., Temperini, M., and Vaste, G. (2009). Adaptive learning with the LS-plan system: a field evaluation. IEEE Transactions on Learning Technologies, pages 203–215.
Limongelli, C., Sciarrone, F., Temperini, M., and Vaste, G. (2010). Comparing curriculum sequencing algorithms for intelligent adaptive (e)-learning. In Proceedings of the Conference ICL.
Luke, S. (2013). Essentials of Metaheuristics. Lulu, 2 edition.
Marzano, R. and Kendall, J. (2007). The new taxonomy of educational objectives. Corwin Pr.
Messick, S. (1976). Personal styles and educational options. Individuality in learning, pages 327–368.
Roberts, M. and Erdos, G. (1993). Strategy selection and metacognition. Educational Psychology, 13(3):259–266.
S., A.-M. and Menai, M. (2011). Evolutionary computation approaches to the curriculum sequencing problem. Natural Computing, 10(2):891–920.
Sangineto, E., Capuano, N., Gaeta, M., and Micarelli, A. (2008). Adaptive course generation through learning styles representation. Universal Access in the Information Society, 7(1):1–23.
Weiser, M. (1991). The Computer for the 21st Century. Scient. American, 265(3):66–75.
Publicado
26/10/2015
Como Citar
BRANQUINHO, Augusto B.; LOPES, Carlos R.; DORÇA, Fabiano A.; FERNANDES, Márcia A.; CATTELAN, Renan G..
Aquisição Automática de Competências num Ambiente Educacional Ubíquo. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 26. , 2015, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2015
.
p. 1207-1216.
DOI: https://doi.org/10.5753/cbie.sbie.2015.1207.
