Modeling and Predicting Students Problem Solving Times

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Authors

PELÁNEK Radek JARUŠEK Petr

Year of publication 2012
Type Article in Proceedings
Conference Proceedings of the 38th International Conference on Current Trends in Theory and Practice of Computer Science
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1007/978-3-642-27660-6_52
Field Informatics
Keywords Problem solving; Modeling; Predicting
Description Artificial intelligence and data mining techniques offer a chance to make education tailored to every student. One of possible contributions of automated techniques is a selection of suitable problems for individual students based on previously collected data. To achieve this goal, we propose a model of problem solving times, which predicts how much time will a particular student need to solve a given problem. Our model is an analogy of the models used in the item response theory, but instead of probability of a correct answer, we model problem solving time. We also introduce a web-based problem solving tutor, which uses the model to make adaptive predictions and recommends problems of suitable difficulty. The system already collected extensive data on human problem solving. Using this dataset we evaluate the model and discuss an insight gained by an analysis of model parameters.
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