Predicting player moves in an educational game: A hybrid approach

Yun En Liu, Travis Mandel, Eric Butler, Erik Andersen, Eleanor O’Rourke, Emma Brunskill, Zoran Popović

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Open-ended educational tools can encourage creativity and active engagement, and may be used beyond the classroom. Being able to model and predict learner performance in such tools is a critical component to assist the student, and enable tool refinement. However, open-ended educational domains typically allow an extremely broad range of learner input. As such, building the same kind of cognitive models often used to track and predict student behavior in existing systems is challenging. In addition, the resulting large spaces of user input coupled with comparatively sparse observed data, limits the applicability of straightforward classification methods. We address these difficulties with a new algorithm that combines Markov models, state aggregation, and player heuristic search, dynamically selecting between these methods based on the amount of available data. Applied to a popular educational game, our hybrid model achieved greater predictive accuracy than any of the methods alone, and performed significantly better than a random baseline. We demonstrate how our model can learn player heuristics on data from one task that accurately predict performance on future tasks, and explain how our model retains parameters that are interpretable to non-expert users.

Original languageEnglish (US)
Title of host publicationProceedings of the 6th International Conference on Educational Data Mining, EDM 2013
EditorsSidney K. D'Mello, Rafael A. Calvo, Andrew Olney
PublisherInternational Educational Data Mining Society
ISBN (Electronic)9780983952527
StatePublished - Jan 1 2013
Externally publishedYes
Event6th International Conference on Educational Data Mining, EDM 2013 - Memphis, United States
Duration: Jul 6 2013Jul 9 2013

Publication series

NameProceedings of the 6th International Conference on Educational Data Mining, EDM 2013

Conference

Conference6th International Conference on Educational Data Mining, EDM 2013
CountryUnited States
CityMemphis
Period7/6/137/9/13

Keywords

  • Educational games
  • User modeling

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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