Qualitative, quantitative, and data mining methods for analyzing log data to characterize students' learning strategies and behaviors
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. © ISLS.
Publication Title
Learning in the Disciplines: ICLS 2010 Conference Proceedings - 9th International Conference of the Learning Sciences
Recommended Citation
Baker, R., Gobert, J., Van Joolingen, W., Azevedo, R., Roll, I., & São Pedro, M. (2010). Qualitative, quantitative, and data mining methods for analyzing log data to characterize students' learning strategies and behaviors. Learning in the Disciplines: ICLS 2010 Conference Proceedings - 9th International Conference of the Learning Sciences, 2, 45-52. Retrieved from https://digitalcommons.memphis.edu/facpubs/3103
