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. © 2014 Springer International Publishing Switzerland.
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CITATION STYLE
Taraghi, B., Saranti, A., Ebner, M., Großmann, A., & Müller, V. (2014). Adaptive learner profiling provides the optimal sequence of posed basic mathematical problems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8719 LNCS, pp. 592–593). Springer Verlag. https://doi.org/10.1007/978-3-319-11200-8_85
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