A Model for Semi-Automatic Composition of Educational Content from Open Repositories of Learning Objects
Keywords:
Learning Object Repositories, Open Educational Resources, Educational Technology, Educational Theory.Abstract
Learning objects (LOs) repositories are important in building educational content and should allow search, retrieval and composition processes to be successfully developed to reach educational goals. However, such processes require so much time-consuming and not always provide the desired results. Thus, the aim of this paper is to propose a model for the semiautomatic composition of LOs, which are automatically recovered from open repositories. For the development of model, various text similarity measures are discussed, while for calibration and validation some comparison experiments were performed using the results obtained by teachers. Experimental results show that when using a value of k (number of LOs selected) of at least 3, the percentage of similarities between the model and such made by experts exceeds 75%. To conclude, it can be established that the model proposed allows teachers to save time and effort for LOs selection by performing a pre-filter process.Downloads
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References
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Li, J. Z. (2010). Quality, evaluation and recommendation for learning object. International Conference on Educational and Information Technology, 533-537.
Mavrommatis, G. (2008). Learning objects and objectives towards automatic learning construction. European Journal of Operational Research, 187(3), 1449-1458. doi:10.1016/j.ejor.2006.09.024
Ouyang, Y. y Zhu, M. (2008). eLORM: learning object relationship mining-based repository. Online Information Review, 32(2), 254-265. doi:10.1108/ 14684520810879863
Peña, C. I., Marzo, J., De la Rosa, J. L. y Fabregat, R. (2002). Un sistema de tutoría inteligente adaptativo considerando estilos de aprendizaje. Universidad de Girona, España.
Pithamber, R. P. (2003). Use and abuse of reusable learning objects. Journal of Digital Information, 3(4).
Real, R. y Vargas, J. M. (1996). The probabilistic basis of Jaccard’s Index of similarity. Systematic Biology, 45(3), 380. doi:10.2307/2413572
Salton, G., Wong, A. y Yang, C. S. (1975). A vector space model for automatic indexing. Communications of the ACM, 18(11), 613-620.
Tabares, V., Duque, N., Moreno, J., Ovalle, D. y Vicari R. (2013) Evaluación de la calidad de metadatos en repositorios digitales de objetos de aprendizaje. Revista interamericana de bibliotecología (En dictamen).
Tseng, S. S., Su, J. M., Hwang, G. J., Hwang, G. H., Tsai, C. y Tsai, C. J. (2008). An object-oriented course framework for developing adaptive learning systems. Educational Technology & Society, 11(2), 171-191.
Van de Sompel, H. y Chute, R. (2008). The aDORe federation architecture?: digital repositories at scale. International Journal, 9, 83-100. doi:10.1007/s00799-008-0048-7
Verbert, K., Ochoa, X., Derntl, M., Wolpers, M., Pardo, A. y Duval, E. (2012). Semi-automatic assembly of learning resources. Computers & Education, 59(4), 1257-1272. doi:10.1016/j.compedu.2012.06.005
Baldiris, S. y Duque Méndez, N. (2012). Searching and positioning of contextualized. Learning Objects, 5(3), 1-11.
Betancur, D., Moreno, J. y Ovalle, D. (2009). Modelo para la recomendación y recuperación de objetos de aprendizaje en entornos virtuales de enseñanza/aprendizaje. Revista Avances en Sistemas e Informática, 6(1), 45-56.
Bonny, J. y Renou, J. (2002). Euclidian distance-weighted smoothing for quantitative MRI: application to intervoxel anisotropy index mapping with DTI. Journal of magnetic resonance, 159(2), 183-9.
Dice, L. R. (1945). Measures of the amount of ecologic association between species. Ecology, 26(3), 297-302.
Duque, N. D. (2005). Modelo de cursos virtuales adaptativos en un ambiente de planificacion inteligente. Universidad Nacional de Colombia.
Grossman, D. y Frieder, O. (2004). Information retrieval: algorithms and heuristics. Berlín: Springer.
Haibo, G., Wenxue, H., Jianxin, C., Yong, Z. y Hui, M. (2008). Pattern recognition of multivariate information based on non-statistical techniques. International Conference on Information and Automation, 697-702. doi:10.1109/ICINFA.2008.4608088
Hamming, W. (1950). Error detecting and error correcting codes. Bell System Technical Journal, 29(2), 147-160.
Huang, Y.-M., Chen, J.-N., Huang, T.-C., Jeng, Y.-L. y Kuo, Y.-H. (2008). Standardized course generation process using Dynamic Fuzzy Petri Nets. Expert Systems with Applications, 34(1), 72-86. doi:10.1016/j.eswa.2006.08.030
Jaccard, P. 1908. Nouvelles recherches sur la distribution florale. Bulletin de la Société Vaudoise des Sciences Naturelles, 44, 223-270.
Kim, M. y Choi, K. (1999). A comparison of collocation-based similarity measures in query expansion. Information processing & management, 35(1), 19-30.
Learning Technology Standards Committee. (2002). IEEE Standard for learning object metadata. Nueva York: Institute of Electrical and Electronics Engineers.
Li, J. Z. (2010). Quality, evaluation and recommendation for learning object. International Conference on Educational and Information Technology, 533-537.
Mavrommatis, G. (2008). Learning objects and objectives towards automatic learning construction. European Journal of Operational Research, 187(3), 1449-1458. doi:10.1016/j.ejor.2006.09.024
Ouyang, Y. y Zhu, M. (2008). eLORM: learning object relationship mining-based repository. Online Information Review, 32(2), 254-265. doi:10.1108/ 14684520810879863
Peña, C. I., Marzo, J., De la Rosa, J. L. y Fabregat, R. (2002). Un sistema de tutoría inteligente adaptativo considerando estilos de aprendizaje. Universidad de Girona, España.
Pithamber, R. P. (2003). Use and abuse of reusable learning objects. Journal of Digital Information, 3(4).
Real, R. y Vargas, J. M. (1996). The probabilistic basis of Jaccard’s Index of similarity. Systematic Biology, 45(3), 380. doi:10.2307/2413572
Salton, G., Wong, A. y Yang, C. S. (1975). A vector space model for automatic indexing. Communications of the ACM, 18(11), 613-620.
Tabares, V., Duque, N., Moreno, J., Ovalle, D. y Vicari R. (2013) Evaluación de la calidad de metadatos en repositorios digitales de objetos de aprendizaje. Revista interamericana de bibliotecología (En dictamen).
Tseng, S. S., Su, J. M., Hwang, G. J., Hwang, G. H., Tsai, C. y Tsai, C. J. (2008). An object-oriented course framework for developing adaptive learning systems. Educational Technology & Society, 11(2), 171-191.
Van de Sompel, H. y Chute, R. (2008). The aDORe federation architecture?: digital repositories at scale. International Journal, 9, 83-100. doi:10.1007/s00799-008-0048-7
Verbert, K., Ochoa, X., Derntl, M., Wolpers, M., Pardo, A. y Duval, E. (2012). Semi-automatic assembly of learning resources. Computers & Education, 59(4), 1257-1272. doi:10.1016/j.compedu.2012.06.005
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Published
2014-04-30
