Radek Pelánek
ABSTRACT
Personalized educational systems adapt their behavior based on student performance. Most student modeling techniques, which are used for guiding the adaptation, utilize only the correctness of student's answers. However, other data about performance are typically available. In this work we focus on response times and wrong answers as these aspects of performance are available in most systems. We analyze data from several types of exercises and domains (mathematics, spelling, grammar). The results suggest that wrong answers are more informative than response times. Based on our results we propose a classification of student performance into several categories.
- Ryan SJ Baker, Albert T Corbett, and Vincent Aleven. 2008. More accurate student modeling through contextual estimation of slip and guess probabilities in bayesian knowledge tracing. In Proc. of Intelligent Tutoring Systems. Springer, 406--115. Google Scholar
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- S Klinkenberg, M Straatemeier, and HLJ Van der Maas. 2011. Computer adaptive practice of Maths ability using a new item response model for on the fly ability and difficulty estimation. Computers & Education 57, 2 (2011), 1813--1824. Google ScholarDigital Library
- Jan Papoušek, Radek Pelánek, Jiří Rihák, and Vít Stanislav. 2015. An Analysis of Response Times in Adaptive Practice of Geography Facts. In Proc. of Educational Data Mining. 562--563.Google Scholar
- Radek Pelánek. 2017. Bayesian knowledge tracing, logistic models, and beyond: an overview of learner modeling techniques. User Modeling and User-Adapted Interaction 27, 3 (2017), 313--350. Google ScholarDigital Library
- Radek Pelánek and Jiří Rihák. 2017. Experimental Analysis of Mastery Learning Criteria. In Proc. of User Modelling, Adaptation and Personalization. ACM, 156--163. Google ScholarDigital Library
- Radek Pelánek and Jiří Rihák. 2016. Properties and Applications of Wrong Answers in Online Educational Systems. In Proc. of Educational Data Mining. 466--471.Google Scholar
- W.J. Van Der Linden. 2009. Conceptual Issues in Response-Time Modeling. Journal of Educational Measurement 46, 3 (2009), 247--272.Google ScholarCross Ref
- Yutao Wang, Neil T Heffernan, and Cristina Heffernan. 2015. Towards better affect detectors: effect of missing skills, class features and common wrong answers. In Proc. of Learning Analytics And Knowledge. ACM, 31--35. Google ScholarDigital Library
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