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Smart University Taxonomy: Features, Components, Systems Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Sequencing Educational Contents Using Clustering and Ant Colony Algorithms

Authors : María José Franco Lugo, Christian von Lücken, Esteban Ramírez Espinoza

Published in: Smart Education and e-Learning 2016

Publisher: Springer International Publishing

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Abstract

This work presents a model to optimize the presentation order of educational contents in the Moodle e-Learning platform. The objective here is to infer those learning paths for which it is expected the students may achieve the best performance. The foundations of the proposed model are (i) a clustering of similar students according to a student model, and (ii) a metaheuristic to obtain an improved educational content sequence for each group. The clustering of similar students is achieved by a modified k-prototypes algorithm. Then, for each group of students, an Ant Colony Optimization algorithm is used for self-organize the sequencing of the educational content that better adapts to its learning characteristics. Finally, to evaluate the proposal, synthetic and real data were used for testing purposes. Experimental results show the viability of the proposed approach.

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Literature
1.
Ros, M.Z.: Secuenciación de contenidos y objetos de aprendizaje. Revista de Educación a Distancia (2005)
2.
Bianchi, L., Dorigo, M., Gambardella, L.M., Gutjahr, W.J.: A survey on metaheuristics for stochastic combinatorial optimization. Nat. Comput. 8(2), 239–287 (2009)MathSciNetCrossRefMATH
3.
Semet, Y., Lutton, E., Collet, P.: Ant colony optimization for e-learning: Observing the emergence of pedagogic suggestions. In: Swarm Intelligence Symposium, 2003. SIS’03. Proceedings of the 2003 IEEE, pp. 46–52. IEEE (2003)
4.
Van den Berg, B., Van Es, R., Tattersall, C., Janssen, J., Manderveld, J., Brouns, F., Koper, R.: Swarm-based sequencing recommendations in E-learning. In: 5th International Conference on Intelligent Systems Design and Applications, 2005. ISDA’05. Proceedings, pp. 488–493. IEEE (2005)
5.
Gutiérrez, S., Pardo, A., Kloos, C.D.: Finding a learning path: toward a swarm intelligence approach. In: Proceedings of the 5th IASTED International Conference on Web-Based Education, pp. 94–99. ACTA Press (2006)
6.
Wang, T.I., Wang, K.T., Huang, Y.M.: Using a style-based ant colony system for adaptive learning. Expert Syst. Appl. 34(4), 2449–2464 (2008)CrossRef
7.
Wong, L.H., Looi, C.K.: Adaptable learning pathway generation with ant colony optimization. Educ. Technol. Soc. 12(3), 309–326 (2009)
8.
Gutiérrez, S., Valigiani, G., Collet, P., Kloos, C.D.: Adaptation of the ACO heuristic for sequencing learning activities. In: Proceedings of the EC-TEL, pp. 17–20 (2007)
9.
Despins, J.P.: Connaitre les styles d’apprendissage pour mieux respecter les façons d’apprendre les enfants. Vie Pedagogique 39, 10–16 (1985)
10.
Herrmann, N.: The creative brain*. J. Creat. Behav. 25(4), 275–295 (1991)CrossRef
11.
Felder, R.M.: Matters of style. ASEE Prism 6(4), 18–23 (1996)
12.
Keefe, J.W.: Profiling and Utilizing Learning Style. NASSP, 1904 Association Drive, Reston, VA 22091-1578 (1988)
13.
Huynh, O.M.S.V.N., Nakamori, Y.: k-Prototypes Algorithm for Clustering Mixed Numeric and Categorical Data (2003)
14.
Berkhin, P.: A survey of clustering data mining techniques. In: Grouping Multidimensional Data, pp. 25–71. Springer, Berlin, Heidelberg (2006)
15.
16.
17.
Hong, C.: A Survey of Model-Based Clustering Algorithms for Sequential Data (2002)
18.
Malo Herrera, E.: Modelo de clustering para el análisis de los datos poblacionales del cáncer. Universidad de Valparaíso, Chile (2007)
19.
Metadata
Title
Sequencing Educational Contents Using Clustering and Ant Colony Algorithms
Authors
María José Franco Lugo
Christian von Lücken
Esteban Ramírez Espinoza
Copyright Year
2016
Book
Smart Education and e-Learning 2016

Print ISBN: 978-3-319-39689-7

Electronic ISBN: 978-3-319-39690-3

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-39690-3_33

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