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Analysis of a Simple Model of Problem Solving Times

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7315))

Abstract

Our aim is to improve problem selection and recommendation in intelligent tutoring systems by modeling students problem solving times. We describe a simple model which assumes a linear relationship between latent problem solving ability and a logarithm of time to solve a problem. We show that this model is related to models from two different areas: the item response theory and collaborative filtering. Each of these areas provides inspiration for parameter estimation procedure and for possible extensions. The model is already applied in a widely used “Problem solving tutor”; using the data collected by this system we evaluate the model and analyse its parameter values.

This work is supported by GA ČR grant no. P202/10/0334.

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References

  1. Anderson, J., Boyle, C., Reiser, B.: Intelligent tutoring systems. Science 228(4698), 456–462 (1985)

    Article  Google Scholar 

  2. Baker, F.: The basics of item response theory. University of Wisconsin (2001)

    Google Scholar 

  3. Corbett, A., Anderson, J.: Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction 4(4), 253–278 (1994)

    Google Scholar 

  4. Csikszentmihalyi, M.: Flow: The psychology of optimal experience. HarperPerennial, New York (1991)

    Google Scholar 

  5. De Ayala, R.: The theory and practice of item response theory. The Guilford Press (2008)

    Google Scholar 

  6. Jarušek, P., Pelánek, R.: What determines difficulty of transport puzzles? In: Proc. of Florida Artificial Intelligence Research Society Conference, pp. 428–433. AAAI Press (2011)

    Google Scholar 

  7. Jarušek, P., Pelánek, R.: Modeling and Predicting Students Problem Solving Times. In: Bieliková, M., Friedrich, G., Gottlob, G., Katzenbeisser, S., Turán, G. (eds.) SOFSEM 2012. LNCS, vol. 7147, pp. 637–648. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  8. Koren, Y., Bell, R.: Advances in collaborative filtering. In: Recommender Systems Handbook, pp. 145–186 (2011)

    Google Scholar 

  9. Van der Linden, W.: A lognormal model for response times on test items. Journal of Educational and Behavioral Statistics 31(2), 181 (2006)

    Article  MathSciNet  Google Scholar 

  10. Mulder, J., Linden, W.: Multidimensional adaptive testing with kullback–leibler information item selection. Elements of Adaptive Testing, 77–101 (2010)

    Google Scholar 

  11. Van Der Linden, W.: Conceptual issues in response-time modeling. Journal of Educational Measurement 46(3), 247–272 (2009)

    Article  MathSciNet  Google Scholar 

  12. Vanlehn, K.: The behavior of tutoring systems. International Journal of Artificial Intelligence in Education 16(3), 227–265 (2006)

    Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Jarušek, P., Pelánek, R. (2012). Analysis of a Simple Model of Problem Solving Times. In: Cerri, S.A., Clancey, W.J., Papadourakis, G., Panourgia, K. (eds) Intelligent Tutoring Systems. ITS 2012. Lecture Notes in Computer Science, vol 7315. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30950-2_49

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  • DOI: https://doi.org/10.1007/978-3-642-30950-2_49

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30949-6

  • Online ISBN: 978-3-642-30950-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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