Abstract
Applications that try to enhance learners’ knowledge can profit by the creation and analysis of learner profiles. This work deals with the derivation of an optimal sequence of questions by comparing similar learning behaviour of users of a mathematics training application. The adaptation of the learners’ clusters to the answers of the revised optimal question sequence improves learning.
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Wei, X., Yan, J.: Learner Profile Design for Personalized E-Learning Systems. In: Proceedings of the International Conference on Computational Intelligence and Software Engineering, pp. 1–4 (2009)
Zghal Rebaï, R., Ghorbel, L., Zayani, C.A., Amous, I.: An Adaptive Method for User Profile Learning. In: Catania, B., Guerrini, G., Pokorný, J. (eds.) ADBIS 2013. LNCS, vol. 8133, pp. 126–134. Springer, Heidelberg (2013)
Taraghi, B., Ebner, M., Saranti, A., Schön, M.: On Using Markov Chain to Evidence the Learning Structures and Difficulty Levels of One Digit Multiplication. In: Proceedings of the 4th International Conference on Learning Analytics and Knowledge, Indianapolis, USA, pp. 68–72 (2014)
Murphy, K.P.: Machine Learning a probabilistic prospective. The MIT Press, Cambridge (2012)
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Taraghi, B., Saranti, A., Ebner, M., Großmann, A., Müller, V. (2014). Adaptive Learner Profiling Provides the Optimal Sequence of Posed Basic Mathematical Problems. In: Rensing, C., de Freitas, S., Ley, T., Muñoz-Merino, P.J. (eds) Open Learning and Teaching in Educational Communities. EC-TEL 2014. Lecture Notes in Computer Science, vol 8719. Springer, Cham. https://doi.org/10.1007/978-3-319-11200-8_85
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DOI: https://doi.org/10.1007/978-3-319-11200-8_85
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11199-5
Online ISBN: 978-3-319-11200-8
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