Recomendação de Objetos de Aprendizagem utilizando Filtragem Colaborativa: Uma comparação entre abordagens de pré-processamento por meio de clusterização
Resumo
No contexto de e-learning a filtragem colaborativa pode servir para a recomendação de objetos de aprendizagem aos estudantes e professores envolvidos no processo de ensino-aprendizagem. Ainda que tal técnica apresente grande potencial no contexto educacional, os estudos existentes sobre sua utilização nesse domínio são bastante limitados, sobretudo pelas barreiras encontradas na disponibilização de conjuntos de dados para teste e avaliação. O presente trabalho avalia dois métodos de pré-processamento por meio de clusterização para a posterior utilização por um algoritmo de filtragem colaborativa utilizando uma base de dados de ratings de objetos de aprendizagem coletada do tradicional repositório MERLOT. Os resultados iniciais encontrados apontam que o agrupamento de objetos de aprendizagem melhora o desempenho do algoritmo de filtragem colaborativa.
Palavras-chave:
Filtragem Colaborativa, Objetos de Aprendizagem, E-Learning, Clusterização, Avaliação de Dados
Referências
Carvalho, V., Dorca, F., Cattelan, R., and Araujo, R. (2014). Uma abordagem para recomendação automática e dinâmica de objetos de aprendizagem baseada em estilos de aprendizagem. 25o Simpósio Brasileiro de Informática na Educação (SBIE) no 3o Congresso Brasileiro de Informática na Educação (CBIE 2014), Dourados:EaD-UFGD, 1.
Cechinel, C., Sánchez-Alonso, S., and García-Barriocanal, E. (2011). Statistical profiles of highly-rated learning objects. Computers & and Education, 57(1):1255 – 1269.
Cechinel, C., Sicilia, M.-Á., Sánchez-Alonso, S., and García-Barriocanal, E. (2013). Evaluating collaborative filtering recommendations inside large learning object repositories. Information Processing & Management, 49(1):34 – 50.
Drachsler, H., Bogers, T., Vuorikari, R., Verbert, K., Duval, E., Manouselis, N., Beham, G., Lindstaedt, S., Stern, H., Friedrich, M., and Wolpers, M. (2010). Issues and considerations regarding sharable data sets for recommender systems in technology enhanced learning. Procedia Computer Science, 1(2):2849 – 2858. Proceedings of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2010).
Drachsler, H., Hummel, H. G. K., and Koper, R. (2008). Personal recommender systems for learners in lifelong learning networks&58; the requirements, techniques and model. Int. J. Learn. Technol., 3(4):404–423.
Ghauth, K. and Abdullah, N. (2010). Learning materials recommendation using good learners’ ratings and content-based filtering. Educational Technology Research and Development, 58(6):711–727.
Gong, S. and Ye, H. (2009). Joining user clustering and item based collaborative filtering in personalized recommendation services. In Industrial and Information Systems, 2009. IIS ’09. International Conference on, pages 149–151.
Herlocker, J. L., Konstan, J. A., Terveen, L. G., and Riedl, J. T. (2004). Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst., 22(1):5–53.
Huang, Y. (2009). An item based collaborative filtering using item clustering prediction. In Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on, volume 4, pages 54–56.
Klas̃nja-Milićević, A., Vesin, B., Ivanović, M., and Budimac, Z. (2011). E-learning personalization based on hybrid recommendation strategy and learning style identification. Computers & Education, 56(3):885 – 899.
Manouselis, N., K. G. S. G. (2012). Revisiting the multi-criteria recommender system of a learning portal. In 2nd Workshop on Recommender Systems in Technology Enhanced Learning (RecSysTEL) - 7th European Conference on Technology Enhanced Learning (EC-TEL 2012), pages 35–48.
Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H., and Koper, R. (2011). Recommender systems in technology enhanced learning. In Ricci, F., Rokach, L., Shapira, B., and Kantor, P. B., editors, Recommender Systems Handbook, pages 387–415. Springer US.
Ochoa, X. and Carrillo, G. (2013). Recomendación de objetos de aprendizaje basado en el perfil del usuario y la información de atención contextualizada. Conferencias LACLO, 4(1).
Pontes, W., Franca, R., Costa, A. P. M., and Behar, P. A. (2014). Filtragens de recomendação de objetos de aprendizagem: uma revisão sistemática do cbie. 25o Simpósio Brasileiro de Informática na Educação (SBIE) no 3o Congresso Brasileiro de Informática na Educação (CBIE 2014), Dourados:EaD-UFGD, 1:76–86.
Sicilia, M.-Á., García-Barriocanal, E., Sánchez-Alonso, S., and Cechinel, C. (2010). Exploring user-based recommender results in large learning object repositories: the case of merlot. Procedia Computer Science, 1(2):2859 – 2864. Proceedings of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2010).
Tang, T. and McCalla, G. (2005). Smart recommendation for an evolving e-learning system: Architecture and experiment. International Journal on E-Learning, 4(1):105– 129.
Verbert, K., Manouselis, N., Ochoa, X., Wolpers, M., Drachsler, H., Bosnic, I., and Duval, E. (2012). Context-aware recommender systems for learning: A survey and future challenges. Learning Technologies, IEEE Transactions on, 5(4):318–335.
Wang, P.-Y. and Yang, H.-C. (2012). Using collaborative filtering to support college students’ use of online forum for english learning. Computers & Education, 59(2):628 – 637.
Cechinel, C., Sánchez-Alonso, S., and García-Barriocanal, E. (2011). Statistical profiles of highly-rated learning objects. Computers & and Education, 57(1):1255 – 1269.
Cechinel, C., Sicilia, M.-Á., Sánchez-Alonso, S., and García-Barriocanal, E. (2013). Evaluating collaborative filtering recommendations inside large learning object repositories. Information Processing & Management, 49(1):34 – 50.
Drachsler, H., Bogers, T., Vuorikari, R., Verbert, K., Duval, E., Manouselis, N., Beham, G., Lindstaedt, S., Stern, H., Friedrich, M., and Wolpers, M. (2010). Issues and considerations regarding sharable data sets for recommender systems in technology enhanced learning. Procedia Computer Science, 1(2):2849 – 2858. Proceedings of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2010).
Drachsler, H., Hummel, H. G. K., and Koper, R. (2008). Personal recommender systems for learners in lifelong learning networks&58; the requirements, techniques and model. Int. J. Learn. Technol., 3(4):404–423.
Ghauth, K. and Abdullah, N. (2010). Learning materials recommendation using good learners’ ratings and content-based filtering. Educational Technology Research and Development, 58(6):711–727.
Gong, S. and Ye, H. (2009). Joining user clustering and item based collaborative filtering in personalized recommendation services. In Industrial and Information Systems, 2009. IIS ’09. International Conference on, pages 149–151.
Herlocker, J. L., Konstan, J. A., Terveen, L. G., and Riedl, J. T. (2004). Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst., 22(1):5–53.
Huang, Y. (2009). An item based collaborative filtering using item clustering prediction. In Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on, volume 4, pages 54–56.
Klas̃nja-Milićević, A., Vesin, B., Ivanović, M., and Budimac, Z. (2011). E-learning personalization based on hybrid recommendation strategy and learning style identification. Computers & Education, 56(3):885 – 899.
Manouselis, N., K. G. S. G. (2012). Revisiting the multi-criteria recommender system of a learning portal. In 2nd Workshop on Recommender Systems in Technology Enhanced Learning (RecSysTEL) - 7th European Conference on Technology Enhanced Learning (EC-TEL 2012), pages 35–48.
Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H., and Koper, R. (2011). Recommender systems in technology enhanced learning. In Ricci, F., Rokach, L., Shapira, B., and Kantor, P. B., editors, Recommender Systems Handbook, pages 387–415. Springer US.
Ochoa, X. and Carrillo, G. (2013). Recomendación de objetos de aprendizaje basado en el perfil del usuario y la información de atención contextualizada. Conferencias LACLO, 4(1).
Pontes, W., Franca, R., Costa, A. P. M., and Behar, P. A. (2014). Filtragens de recomendação de objetos de aprendizagem: uma revisão sistemática do cbie. 25o Simpósio Brasileiro de Informática na Educação (SBIE) no 3o Congresso Brasileiro de Informática na Educação (CBIE 2014), Dourados:EaD-UFGD, 1:76–86.
Sicilia, M.-Á., García-Barriocanal, E., Sánchez-Alonso, S., and Cechinel, C. (2010). Exploring user-based recommender results in large learning object repositories: the case of merlot. Procedia Computer Science, 1(2):2859 – 2864. Proceedings of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2010).
Tang, T. and McCalla, G. (2005). Smart recommendation for an evolving e-learning system: Architecture and experiment. International Journal on E-Learning, 4(1):105– 129.
Verbert, K., Manouselis, N., Ochoa, X., Wolpers, M., Drachsler, H., Bosnic, I., and Duval, E. (2012). Context-aware recommender systems for learning: A survey and future challenges. Learning Technologies, IEEE Transactions on, 5(4):318–335.
Wang, P.-Y. and Yang, H.-C. (2012). Using collaborative filtering to support college students’ use of online forum for english learning. Computers & Education, 59(2):628 – 637.
Publicado
26/10/2015
Como Citar
SANTOS, Henrique L. dos; CECHINEL, Cristian; ARAÚJO, Ricardo M.; BRAUNER, Daniela.
Recomendação de Objetos de Aprendizagem utilizando Filtragem Colaborativa: Uma comparação entre abordagens de pré-processamento por meio de clusterização. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 26. , 2015, Maceió/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2015
.
p. 1127-1136.
DOI: https://doi.org/10.5753/cbie.sbie.2015.1127.
