Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/357
Title: Situating Deep Multimodal Data on Game-Based STEM Learning
Authors: Anderson, Craig G.
Binzak, John V.
Dalsen, Jennifer
Saucerman, Jenny
Jordan-Douglass, Anna
Kumar, Vishesh
Turker, Aybuke
Berland, Matthew
Squire, Kurt
Steinkuehler, Constance
Issue Date: Jul-2016
Publisher: Singapore: International Society of the Learning Sciences
Citation: Anderson, C. G., Binzak, J. V., Dalsen, J., Saucerman, J., Jordan-Douglass, A., Kumar, V., Turker, A., Berland, M., Squire, K., & Steinkuehler, C. (2016). Situating Deep Multimodal Data on Game-Based STEM Learning In Looi, C. K., Polman, J. L., Cress, U., and Reimann, P. (Eds.). Transforming Learning, Empowering Learners: The International Conference of the Learning Sciences (ICLS) 2016, Volume 2. Singapore: International Society of the Learning Sciences.
Abstract: As STEM embedded games become more prevalent in classrooms, the need for teachers and researchers to understand the ways in which students learn in these complex environments increases. This paper describes a multimodal datastream approach to understanding student learning in an informal game-embedded curriculum. Through a multi-stream approach, we have more information on what students are using and how they are improving, which in preliminary analyses, proves to be more complex than one might think. Importance of multiple data streams in analyzing complex learning environments and future directions for more complex analyses are discussed.
URI: https://repository.isls.org/handle/1/357
https://doi.dx.org/10.22318/icls2016.150
Appears in Collections:ICSL 2016

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