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 Rus; Arthur Greesser

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 Rus

Arthur Greesser

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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 language	English
Title of host publication	Learning in the Disciplines: ICLS 2010 Conference Proceedings - 9th International Conference of the Learning Sciences
Publisher	International Society of the Learning Sciences
Pages	45-52
Number of pages	8
Volume	2
Publication status	Published - 29 Jun 2010
Event	9th International Conference of the Learning Sciences, ICLS 2010 - Chicago, IL, United States Duration: 29 Jun 2010 → 2 Jul 2010

Conference

Conference	9th International Conference of the Learning Sciences, ICLS 2010
Country/Territory	United States
City	Chicago, IL
Period	29/06/10 → 2/07/10

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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. In Learning in the Disciplines: ICLS 2010 Conference Proceedings - 9th International Conference of the Learning Sciences (Vol. 2, pp. 45-52). Article 97957 International Society of the Learning Sciences. https://dl.acm.org/doi/10.5555/1854509.3252029

Baker, Ryan S. J. D. ; Gobert, Janice D. ; Van Joolingen, Wouter et al. / 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. Vol. 2 International Society of the Learning Sciences, 2010. pp. 45-52

@inproceedings{6e19dab30e51461a8df1cca5c9bcc719,

title = "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.",

author = "Baker, \{Ryan S. J. D.\} and Gobert, \{Janice D.\} and \{Van Joolingen\}, Wouter and Roger Azevedo and Ido Roll and \{S{\~a}o Pedro\}, Michael and Juelaila Raziuddin and Nathan Krach and \{De Carvalho\}, \{Adriana M. J. B.\} and Jay Raspat and Vincent Aleven and Corbett, \{Albert T.\} and Koedinger, \{Kenneth R.\} and Mihaela Cocea and Arnon Hershkovitz and Amy Witherspoon and Amber Chauncey and Mihai Lintean and Zhiqiang Cai and Vasile Rus and Arthur Greesser",

year = "2010",

month = jun,

day = "29",

language = "English",

volume = "2",

pages = "45--52",

booktitle = "Learning in the Disciplines: ICLS 2010 Conference Proceedings - 9th International Conference of the Learning Sciences",

publisher = "International Society of the Learning Sciences",

address = "United States",

note = "9th International Conference of the Learning Sciences, ICLS 2010 ; Conference date: 29-06-2010 Through 02-07-2010",

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Baker, RSJD, Gobert, JD, Van Joolingen, W, Azevedo, R, Roll, I, São Pedro, M, Raziuddin, J, Krach, N, De Carvalho, AMJB, Raspat, J, Aleven, V, Corbett, AT, Koedinger, KR, Cocea, M, Hershkovitz, A, Witherspoon, A, Chauncey, A, Lintean, M, Cai, Z, Rus, V & Greesser, A 2010, Qualitative, quantitative, and data mining methods for analyzing log data to characterize students' learning strategies and behaviors. in Learning in the Disciplines: ICLS 2010 Conference Proceedings - 9th International Conference of the Learning Sciences. vol. 2, 97957, International Society of the Learning Sciences, pp. 45-52, 9th International Conference of the Learning Sciences, ICLS 2010, Chicago, IL, United States, 29/06/10. <https://dl.acm.org/doi/10.5555/1854509.3252029>

Qualitative, quantitative, and data mining methods for analyzing log data to characterize students' learning strategies and behaviors. / Baker, Ryan S. J. D.; Gobert, Janice D.; Van Joolingen, Wouter et al.
Learning in the Disciplines: ICLS 2010 Conference Proceedings - 9th International Conference of the Learning Sciences. Vol. 2 International Society of the Learning Sciences, 2010. p. 45-52 97957.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Qualitative, quantitative, and data mining methods for analyzing log data to characterize students' learning strategies and behaviors

AU - Baker, Ryan S. J. D.

AU - Gobert, Janice D.

AU - Van Joolingen, Wouter

AU - Azevedo, Roger

AU - Roll, Ido

AU - São Pedro, Michael

AU - Raziuddin, Juelaila

AU - Krach, Nathan

AU - De Carvalho, Adriana M. J. B.

AU - Raspat, Jay

AU - Aleven, Vincent

AU - Corbett, Albert T.

AU - Koedinger, Kenneth R.

AU - Cocea, Mihaela

AU - Hershkovitz, Arnon

AU - Witherspoon, Amy

AU - Chauncey, Amber

AU - Lintean, Mihai

AU - Cai, Zhiqiang

AU - Rus, Vasile

AU - Greesser, Arthur

PY - 2010/6/29

Y1 - 2010/6/29

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/84880558135

M3 - Conference contribution

AN - SCOPUS:84880558135

VL - 2

SP - 45

EP - 52

BT - Learning in the Disciplines: ICLS 2010 Conference Proceedings - 9th International Conference of the Learning Sciences

PB - International Society of the Learning Sciences

T2 - 9th International Conference of the Learning Sciences, ICLS 2010

Y2 - 29 June 2010 through 2 July 2010

ER -

Baker RSJD, Gobert JD, Van Joolingen W, Azevedo R, Roll I, São Pedro M et al. Qualitative, quantitative, and data mining methods for analyzing log data to characterize students' learning strategies and behaviors. In Learning in the Disciplines: ICLS 2010 Conference Proceedings - 9th International Conference of the Learning Sciences. Vol. 2. International Society of the Learning Sciences. 2010. p. 45-52. 97957

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

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