Abstract
In learning environment, personalization of contents according to the requirement of an individual student is the most important feature of adaptive educational systems. This process becomes more effective if the system knows the way through which a student learns best. Learning styles are non-stationary and are varied for academic disciplines. Our proposed model considers its non-deterministic nature, effect of the subject domain, and non-stationary aspects during the learning process. Presented approach is novel, simple but more flexible that dynamically and accurately adjusts students learning style variations in a discipline-wise manner. For the evaluation of our proposed model, Visual/Verbal dimension of Felder and Silvermen learning style model is utilized for personalization of Computer Science undergraduate subjects in our experimental prototype. Results show that personalization of contents in a discipline-wise manner is more effective during the learning process of a student.
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References
Froschl, C.: User modeling and user profiling in adaptive e-learning systems. Graz, Austria: Master Thesis (2005)
Knutov, Evgeny, De Bra, Paul, Pechenizkiy, Mykola: Ah 12 years later a comprehensive survey of adaptive hypermedia methods and techniques. New Rev. Hypermedia Multimedia 15(1), 5–38 (2009)
Mulwa, C., Lawless, S., Sharp, M., Arnedillo-Sanchez, I., Wade, V.: Adaptive educational hypermedia systems in technology enhanced learning: a literature review. In: Proceedings of the 2010 ACM Conference on Information Technology Education, p. 73–84. ACM (2010)
El-Bakry, H.M., Saleh, A.A.: Adaptive e-learning based on learner’s styles. Bull. Electr. Eng. Inf. 2(4), 240–251 (2013)
El-Bakry, H.M., Saleh, A.A., Asfour, T.T., Mastorakis, N.: A new adaptive e-learning model based on learner’s styles. In: Proceedings of 13th WSEAS International Conference on Mathematical and Computational Methods In Science and Engineering (MACMESE’11). Catania, Sicily, Italy, pp. 440–448 (2011)
Rozanski, E.P., Haake, A.R.: The many facets of hci. In: Proceedings of the 4th conference on Information technology curriculum, pp. 180–185. ACM (2003)
Brown, E.J., Brailsford, T.J., Fisher, T., Moore, A.: Evaluating learning style personalization in adaptive systems: quantitative methods and approaches. IEEE Trans. Learn. Technol. 2(1), 10–22 (2009)
Fernandes, M.A., Lopes, C.R., Dorca, F.A., Lima, L.V.: A stochastic approach for automatic and dynamic modeling of students learning styles in adaptive educational systems. Inf. Educ. Int. J. (\(\mathbf{Vol11\_2}\)), 191–212 (2012)
Jones, Cheryl, Reichard, Carla, Mokhtari, Kouider: Are students’learning styles discipline specific? Commun. Coll. J. Res. Pract. 27(5), 363–375 (2003)
Dorça, F.A., Lima, L.V., Fernandes, M.A., Lopes, C.R.: A new approach to discover students learning styles in adaptive educational systems. Rev. Bras. Inf. Educ. 21(01), 76 (2013)
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 Syst. Appl. 40(6), 2092–2101 (2013)
Carver, C.A., Howard, R.A., Lane, W.D.: Addressing different learning styles through course hypermedia. IEEE Trans. Educ. 42(1), 33–38 (1999)
Graf, S., Viola, S.R., Kinshuk, T.L.: Representative characteristics of felder-silverman learning styles: An empirical model. In Proceedings of the IADIS International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2006), Barcelona, Spain, pp. 235–242 (2006)
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Hussain, A., Fazal, M.A.U., Karim, M.S. (2015). Intra-domain User Model for Content Adaptation. In: L. Uskov, V., Howlett, R., Jain, L. (eds) Smart Education and Smart e-Learning. Smart Innovation, Systems and Technologies, vol 41. Springer, Cham. https://doi.org/10.1007/978-3-319-19875-0_26
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DOI: https://doi.org/10.1007/978-3-319-19875-0_26
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