Learning Analytics for Online Discussions: Embedded and Extracted Approaches

Authors

  • Alyssa Wise Simon Fraser University
  • Yuting Zhao Simon Fraser University
  • Simone Hausknecht Simone Fraser University

DOI:

https://doi.org/10.18608/jla.2014.12.4

Keywords:

Online learning, computer mediated communication, learning analytics, asynchronous discussion groups, student participation

Abstract

This paper describes an application of learning analytics that builds on an existing research program investigating how students contribute and attend to the messages of others in asynchronous online discussions. We first overview the E-Listening research program and then explain how this work was translated into analytics that students and instructors could use to reflect on their discussion participation. Two kinds of analytics were designed: some embedded in the learning environment to provide students with real-time information on their activity in-progress; and some extracted from the learning environment and presented to students in a separate digital space for reflection. In addition, we describe the design of an intervention though which use of the analytics can be introduced as an integral course activity. Findings from an initial implementation of the application indicated that the learning analytics intervention supported changes in students’ discussion participation. Five issues for future work on learning analytics in online discussions are presented. One, unintentional versus purposeful change; two, differing changes prompted by the same analytic; three, importance of theoretical buy-in and calculation transparency for perceived analytic value; four, affective components of students’ reactions; and five, support for students in the process of enacting analytics-driven changes.

Author Biography

Alyssa Wise, Simon Fraser University

Associate Professor, Faculty of Education

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Published

2014-08-07

How to Cite

Wise, A., Zhao, Y., & Hausknecht, S. (2014). Learning Analytics for Online Discussions: Embedded and Extracted Approaches. Journal of Learning Analytics, 1(2), 48-71. https://doi.org/10.18608/jla.2014.12.4