Please use this identifier to cite or link to this item: http://hdl.handle.net/10497/18024
Title: 
Authors: 
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.
URI: 
Appears in Collections:Conference Papers

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