PELÁNEK, Radek and Petr JARUŠEK. Student Modeling Based on Problem Solving Times. International Journal of Artificial Intelligence in Education. 2015, vol. 25, No 4, p. 493-519. ISSN 1560-4292. Available from: https://dx.doi.org/10.1007/s40593-015-0048-x.
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Basic information
Original name Student Modeling Based on Problem Solving Times
Authors PELÁNEK, Radek (203 Czech Republic, guarantor, belonging to the institution) and Petr JARUŠEK (203 Czech Republic, belonging to the institution).
Edition International Journal of Artificial Intelligence in Education, 2015, 1560-4292.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
RIV identification code RIV/00216224:14330/15:00086953
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.1007/s40593-015-0048-x
UT WoS 000213961100002
Keywords in English student modeling; problem solving; time
Tags International impact, Reviewed
Changed by Changed by: doc. Mgr. Radek Pelánek, Ph.D., učo 4297. Changed: 31/3/2016 14:57.
Abstract
Student modeling in intelligent tutoring systems is mostly concerned with modeling correctness of students' answers. As interactive problem solving activities become increasingly common in educational systems, it is useful to focus also on timing information associated with problem solving. We argue that the focus on timing is natural for certain types of educational problems and we describe a simple model of problem solving times which assumes a linear relationship between a latent problem solving skill and a logarithm of a time to solve a problem. The model is closely related to models from two different areas: the item response theory and collaborative filtering. We describe two parameter estimation techniques for the model and several extensions - models with multidimensional skill, learning, or variability of performance. We describe an application of the proposed models in a widely used computerized practice system. Using both simulated data and real data from the system we evaluate the model, analyse its parameter values, and discuss the insight into problem difficulty which the model brings.
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