Using Artificial Neural Networks to Identify Learning Styles
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-19773-9_57
Reference12 articles.
1. Popescu, E.: Adaptation provisioning with respect to learning styles in a Web-based educational system: an experimental study. Journal of Computer Assisted Learning 26(4), 243–257 (2010)
2. Graf, S., Chung, H.-L., Liu, T.-C., Kinshuk: Investigations about the effects and effectiveness of adaptivity for students with different learning styles. In: Proceedings of the International Conference on Advanced Learning Technologies, Latvia, pp. 415–419. IEEE, July 2009
3. Dorça, F.A., Lima, L.V., Fernandes, M.A., Lopes, C.R.: Comparing strategies for modeling students learning styles through reinforcement learning in adaptive and intelligent educational systems: An experimental analysis. Expert Systems with Applications 40(6), 2092–2101 (2013)
4. García, P., Amandi, A., Schiaffino, S., Campo, M.: Evaluating Bayesian networks’ precision for detecting students’ learning styles. Computers & Education 49(3), 794–808 (2007)
5. Özpolat, E., Akar, G.B.: Automatic detection of learning styles for an e-learning system. Computers & Education 53(2), 355–367 (2009)
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