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Title: Analytics of social processes in learning contexts: A multi-level perspective
Authors: Rose, Carolyn P.
Gaesevic, Dragan
Dillenbourg, Pierre
Jo, Yohan
Tomar, Gaurav
Ferschke, Oliver
Erkens, Gijsbert
van Leeuwen, Anouschka
Janssen, Jeroen
Brekelmans, Mieke
Tan, Jennifer Pei-Ling
Koh, Elizabeth
Caleon, Imelda S.
Jonathan, Christin
Yang, Simon
Keywords: Learning analytics
Social analytics
Discourse analytics
Issue Date: Jun-2016
Citation: Rose, C. P., Gaesevic, D., Jo, Y., Tomar, G., Ferschke, O.,…Yang, S. (2016). Analytics of social processes in learning contexts: A multi-level perspective. In C. K. Looi, J. Polman, U. Cress, & P. Reimann (Eds.). Transforming learning, empowering learners: The International Conference of the Learning Sciences (ICLS) 2016, Volume 1 (pp. 24-34). Singapore: International Society of the Learning Sciences.
Abstract: In the past two decades, the field of Machine Learning has not only greatly expanded in terms of the plethora of increasingly powerful modeling frameworks it has provided, but has also birthed the applied fields of Educational Data Mining and Learning Analytics. Learning Analytics has blossomed as an area in the Learning Sciences, promising impact for various stakeholders working at different educational levels, such as Instructional Designers, Students, Instructors, Policymakers and Administrators. This symposium offers a taste of cutting edge work across each of these levels, with a common emphasis on analytics applied to social processes.
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