Qualitative, quantitative, and data mining methods for analyzing log data to characterize students' learning strategies and behaviors

Ryan S.J.D. Baker, Janice D. Gobert, Wouter Van Joolingen, Roger Azevedo, Ido Roll, Michael São Pedro, Juelaila Raziuddin, Nathan Krach, Adriana M.J.B. De Carvalho, Jay Raspat, Vincent Aleven, Albert T. Corbett, Kenneth R. Koedinger, Mihaela Cocea, Arnon Hershkovitz, Amy Witherspoon, Amber Chauncey, Mihai Lintean, Zhiqiang Cai, Vasile RusArthur Greesser

Research output: Contribution to conferencePaper

Abstract

This symposium addresses how different classes of research methods, all based upon the use of log data from educational software, can facilitate the analysis of students' learning strategies and behaviors. To this end, four multi-method programs of research are discussed, including the use of qualitative, quantitative-statistical, quantitative-modeling, and educational data mining methods. The symposium presents evidence regarding the applicability of each type of method to research questions of different grain sizes, and provides several examples of how these methods can be used in concert to facilitate our understanding of learning processes, learning strategies, and behaviors related to motivation, meta-cognition, and engagement.

Original languageEnglish (US)
Pages45-52
Number of pages8
StatePublished - 2010
Event9th International Conference of the Learning Sciences, ICLS 2010 - Chicago, IL, United States
Duration: Jun 29 2010Jul 2 2010

Other

Other9th International Conference of the Learning Sciences, ICLS 2010
CountryUnited States
CityChicago, IL
Period6/29/107/2/10

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Education

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  • Cite this

    Baker, R. S. J. D., Gobert, J. D., Van Joolingen, W., Azevedo, R., Roll, I., São Pedro, M., Raziuddin, J., Krach, N., De Carvalho, A. M. J. B., Raspat, J., Aleven, V., Corbett, A. T., Koedinger, K. R., Cocea, M., Hershkovitz, A., Witherspoon, A., Chauncey, A., Lintean, M., Cai, Z., ... Greesser, A. (2010). Qualitative, quantitative, and data mining methods for analyzing log data to characterize students' learning strategies and behaviors. 45-52. Paper presented at 9th International Conference of the Learning Sciences, ICLS 2010, Chicago, IL, United States.