Modeling the Acquisition of Fluent Skill in Educational Action Games

  • Ryan S. J. D. Baker
  • M. P. Jacob Habgood
  • Shaaron E. Ainsworth
  • Albert T. Corbett
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4511)


There has been increasing interest in using games for education, but little investigation of how to model student learning within games [cf. 6]. We investigate how existing techniques for modeling the acquisition of fluent skill can be adapted to the context of an educational action game, Zombie Division. We discuss why this adaptation is necessarily different for educational action games than for other types of games, such as turn-based games. We demonstrate that gain in accuracy over time is straightforward to model using exponential learning curves, but that models of gain in speed over time must also take gameplay learning into account.


Mathematical Skill Educational Game Intrinsic Condition Interactive Learning Environment Educational Data Mining 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Anderson, J.R., Conrad, F.G., Corbett, A.T.: Skill Acquisition and the LISP Tutor. Cognitive Science 13, 467–505 (1989)CrossRefGoogle Scholar
  2. 2.
    Beck, J.E.: Using learning decomposition to analyze student fluency development. In: Proceedings of the workshop on Educational Data Mining at the 8th International Conference on Intelligent Tutoring Systems, pp. 21–28 (2006)Google Scholar
  3. 3.
    Corbett, A.T., Anderson, J.R.: Knowledge Tracing: Modeling the Acquisition of Procedural Knowledge. User Modeling and User-Adapted Interaction 4, 253–278 (1995)CrossRefGoogle Scholar
  4. 4.
    Habgood, M.P.J.: Zombie Division: Intrinsic Integration in Digital Learning Games. In: Proceedings of the Human Centered Technology Workshop (2005)Google Scholar
  5. 5.
    Martin, B., Koedinger, K., Mitrovic, A., Mathan, S.: On Using Learning Curves to Evaluate ITS. In: Proceedings of the 12th International Conference on Artificial Intelligence in Education (AIED-2005), pp. 419–426 (2005)Google Scholar
  6. 6.
    Manske, M., Conati, C.: Modeling Learning in Educational Games. In: Proceedings of the 12th International Conference on Artificial Intelligence in Education (AIED 2005), pp. 411–418 (2005)Google Scholar
  7. 7.
    Prensky, M.: Digital game-based learning. Computers in Entertainment 1(1), 1–4 (2003)CrossRefGoogle Scholar
  8. 8.
    Repenning, A., Clayton, L.: Playing a game: the ecology of designing, building, and testing games as educational activities. In: Proceedings of ED-MEDIA: World Conference on Educational Multimedia, Hypermedia, and Telecommunications (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Ryan S. J. D. Baker
    • 1
  • M. P. Jacob Habgood
    • 1
  • Shaaron E. Ainsworth
    • 1
  • Albert T. Corbett
    • 2
  1. 1.Learning Sciences Research Institute, University of Nottingham, NottinghamUK
  2. 2.Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PAUSA

Personalised recommendations