Modeling and Predicting Students Problem Solving Times

PELÁNEK, Radek and Petr JARUŠEK. Modeling and Predicting Students Problem Solving Times. In Proceedings of the 38th International Conference on Current Trends in Theory and Practice of Computer Science. Czech republic: Springer, 2012, p. 637-648. ISBN 978-3-642-27659-0. Available from: https://dx.doi.org/10.1007/978-3-642-27660-6_52.

Basic information

• Original name: Modeling and Predicting Students 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: Czech republic, Proceedings of the 38th International Conference on Current Trends in Theory and Practice of Computer Science, p. 637-648, 12 pp. 2012.
• Publisher: Springer

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Czech Republic
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: printed version "print"
• Impact factor: Impact factor: 0.402 in 2005
• RIV identification code: RIV/00216224:14330/12:00057329
• Organization unit: Faculty of Informatics
• ISBN: 978-3-642-27659-0
• ISSN: 0302-9743
• Doi: http://dx.doi.org/10.1007/978-3-642-27660-6_52
• UT WoS: 000307258500052
• Keywords in English: Problem solving; Modeling; Predicting
• Tags: International impact, Reviewed

Abstract

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.

Links

• GAP202/10/0334, research and development project: Name: Řešení obtížných dobře strukturovaných problémů: spolupráce člověka a počítače

Investor: Czech Science Foundation

• MUNI/A/0914/2009, interní kód MU: Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace (Acronym: SV-FI MAV)

Investor: Masaryk University, Category A