Please use this identifier to cite or link to this item: http://hdl.handle.net/10497/19441
Title: A taxonomy for teacher-actionable insights in learning analytics
Authors: Koh, Elizabeth
Tan, Jennifer Pei-Ling
Keywords: Learning analytics
Teacher
Design
Taxonomy
Actionable insight
Issue Date: 2017
Citation: Koh, E., & Tan, J. P. L. (2017). A taxonomy for teacher-actionable insights in learning analytics. In W. Chen, J.-C. Yang, A. F. Mohd Ayub, S. L. Wong, & A. Mitrovic (Eds.), Proceedings of the 25th International Conference on Computers in Education (pp. 517-519). New Zealand: Asia-Pacific Society for Computers in Education. Retrieved from http://icce2017.canterbury.ac.nz/proceedings_main
Abstract: In the field of learning analytics (LA), actionable insight from LA designs tends to be a buzzword without clear understandings. As the teacher is a key stakeholder, what teacher-actionable insights can be derived from LA designs? Towards providing greater clarity on this issue, we concretize a taxonomy of LA decision support for teacher-actionable insights in student engagement. Four types of decision support are conceived in this taxonomy with relevant teacher implications. Through this taxonomy, we hope to offer possible pathways for
actionable insight in LA designs and make clearer the role of the teacher.
URI: http://hdl.handle.net/10497/19441
Website: http://icce2017.canterbury.ac.nz/proceedings_main
Appears in Collections:Conference Papers

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