Abstract
In this paper, we present an intelligent tool implemented as a learning social network. An author can create, display, and share lessons, intelligent tutoring systems and other components among communities of learners in web-based and mobile environments. The tutoring systems are tailored to the student’s learning style according to the model of Felder-Silverman. The identification of the student’s learning style is performed using self-organizing maps. The main contribution of this paper is the implementation of a learning social network to create, view and manage adaptive and intelligent tutoring systems using a new method for automatic identification of the student’s learning style. We present the architecture of the social network, the method for identifying learning styles, and some experiments made to the social network.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
O’Reilly, T.: What is Web 2.0, http://oreilly.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html
Ivanova, M.: Knowledge Building and Competence Development in eLearning 2.0 Systems. In: I-KNOW’08, Graz, Austria, September 3-5, pp. 84–91 (2008)
Murray, T., Blessing, S., Ainsworth, S.: Authoring Tools for Advanced Technology Learning Environments. Kluwer Academic Publishers, Dordrecht (2003)
Jong, T., de Limbach, R., Gellevij, M., Kuyper, M., Pieters, J., Joolingen, W.R.: Cognitive tools to support the instructional design of simulation-based discovery learning environment: the SIMQUEST authoring system. In: Plomp, T.j., van den Akker, J., Nieveen, N., Gustafson, K. (eds.), pp. 215–224. Kluwer Academic Publishers, The Netherlands (1999)
Arruarte, A., Fernández, I., Ferrero, B., Greer, J.: The IRIS Shell: How to build ITSs from Pedagogical and Design Requisites. International Journal of Artificial Intelligence in Education 8, 341–381 (1997)
Brusilovsky, P., Schwarz, E.: Web-based education for all: A tool for developing adaptive courseware. Computer Networks and ISDN Systems 30(1-7), 291–300 (1998)
Carmona, C., Castillo, G., Millán, E.: Designing a Bayesian Network for Modeling Student’s Learning Styles. In: Díaz, P., Kinshuk, Aedo, I., Mora, E. (eds.) ICALT 2008, pp. 346–350. IEEE Computer Society, Los Alamitos (2008)
Graf, S., Kinshuk, Liu, T.: Identifying Learning Styles in Learning Management Systems by Using Indications from Students’ behavior. In: Díaz, P., Kinshuk, Aedo, I., Mora, E. (eds.) ICALT 2008, pp. 482–486. IEEE Computer Society, Los Alamitos (2008)
Limongelli, C., Sciarrone, F., Vaste, J.: LS-PLAN: An Effective Combination of Dynamic Courseware Generation and Learning Styles in Web-based Education. In: Nejdl, W., Kay, J., Pu, P., Herder, E. (eds.) AH 2008. LNCS, vol. 5149, pp. 133–142. Springer, Heidelberg (2008)
Zatarain-Cabada, R., Barrón-Estrada, M.L., Sandoval, G., Osorio, M., Urías, E., Reyes-García, C.A.: Authoring Neuro-fuzzy Tutoring Systems for M and E-Learning. In: Aguirre, A.H., Borja, R.M., Reyes-García, C.A. (eds.) MICAI 2008. LNCS (LNAI), vol. 5317, pp. 789–796. Springer, Heidelberg (2008)
Attewell, J.: Mobile technologies and learning: A technology update and mlearning project summary. Learning and Skills Development, http://www.m-learning.org/reports.shtml
Romero, C., Ventura, S., Hervás, C., De Bra, P.: An Authoring Tool for Building Both Mobile Adaptable Tests and Web-Based Adaptive or Classic Tests. In: Wade, V., Ashman, H., Smyth, B. (eds.) AH 2006. LNCS, vol. 4018, pp. 203–212. Springer, Heidelberg (2006)
Attewell, J.: From Research and Development to Mobile Learning: Tools for Education and Training Providers and their Learners, http://www.mlearn.org.za/CD/papers/Attewell.pdf
Felder, R.M., Solomon, B.A.: Index of Learning Styles Questionnaire, http://www.engr.ncsu.edu/learningstyles/ilsweb.html
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zatarain-Cabada, R., Barrón-Estrada, M.L., Angulo, V.P., García, A.J., García, C.A.R. (2010). Identification of Felder-Silverman Learning Styles with a Supervised Neural Network. In: Huang, DS., Zhang, X., Reyes García, C.A., Zhang, L. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2010. Lecture Notes in Computer Science(), vol 6216. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14932-0_60
Download citation
DOI: https://doi.org/10.1007/978-3-642-14932-0_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14931-3
Online ISBN: 978-3-642-14932-0
eBook Packages: Computer ScienceComputer Science (R0)