Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/636
Title: Data Moves: Restructuring Data for Inquiry in a Simulation and Data Analysis Environment
Authors: Wilkerson, Michelle
Lanouette, Kathryn
Shareff, Rebecca
St. Clair M St. Clair St. Clair, Natalya
Bulalacao, Nicole
Erickson, Tim
Heller, Joan I
Finzer, William
Reichsman, Frieda
Issue Date: Jul-2018
Publisher: International Society of the Learning Sciences, Inc. [ISLS].
Citation: Wilkerson, M., Lanouette, K., Shareff, R., St. Clair M St. Clair St. Clair, N., Bulalacao, N., Erickson, T., Heller, J. I., Finzer, W., & Reichsman, F. (2018). Data Moves: Restructuring Data for Inquiry in a Simulation and Data Analysis Environment. In Kay, J. and Luckin, R. (Eds.) Rethinking Learning in the Digital Age: Making the Learning Sciences Count, 13th International Conference of the Learning Sciences (ICLS) 2018, Volume 3. London, UK: International Society of the Learning Sciences.
Abstract: We explore data transformations, actions investigators take to make datasets more useful for intended inquiries. Fourteen young adults were interviewed while they interacted with online science and engineering games and were provided their own gameplay log data to improve their scores. We investigate the conditions under which data transformations are likely to emerge; provide examples of data moves as enacted by participants; and propose an initial taxonomy of data transformations and potential developmental supports.
URI: https://doi.dx.org/10.22318/cscl2018.1383
https://repository.isls.org//handle/1/636
Appears in Collections:ICLS 2018

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