Students’ walk through tutoring: Using a random walk analysis to profile students

Erica L. Snow, Aaron D. Likens, G. Tanner Jackson, Danielle S. McNamara

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

Abstract

The purpose of this study was to investigate students’ patterns of interactions within a game-based intelligent tutoring system (ITS), and how those interactions varied as a function of individual differences. The analysis presented in this paper comprises a subset (n=40) of a larger study that included 124 high school students. Participants in the current study completed 11 sessions within iSTART-ME, a game-based ITS, that provides training in reading comprehension strategies. A random walk analysis was used to visualize students’ trajectories within the system. The analyses revealed that low ability students’ patterns of interactions were anchored by one feature category whereas high ability students demonstrated interactions across multiple categories. The results from the current paper indicate that random walk analysis is a promising visualization tool for learning scientists interested in capturing students’ interactions within ITSs and other computer-based learning environments over time.

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
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

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Keywords

  • Individual differences
  • Intelligent Tutoring Systems
  • Random walk analysis
  • Sequential pattern analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

Cite this

Snow, E. L., Likens, A. D., Tanner Jackson, G., & McNamara, D. S. (2013). Students’ walk through tutoring: Using a random walk analysis to profile students. In S. K. D'Mello, R. A. Calvo, & A. Olney (Eds.), Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013 (Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013). International Educational Data Mining Society.