Adaptive Practice of Facts in Domains with Varied Prior Knowledge

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Authors

PELÁNEK Radek PAPOUŠEK Jan STANISLAV Vít

Year of publication 2014
Type Article in Proceedings
Conference Proceedings of the 7th International Conference on Educational Data Mining (EDM 2014)
MU Faculty or unit

Faculty of Informatics

Citation
Field Informatics
Keywords adaptive learning; student modeling; recommendation; prior knowledge
Description We propose a modular approach to development of a computerized adaptive practice system for learning of facts in areas with widely varying prior knowledge: decomposing the system into estimation of prior knowledge, estimation of current knowledge, and selection of questions. We describe specific realization of the system for geography learning and use data from the developed system for evaluation of different student models for knowledge estimation. We argue that variants of the Elo rating systems and Performance factor analysis are suitable for this kind of educational system, as they provide good accuracy and at the same time are easy to apply in an online system.
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