Theory-led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning

Authors

  • Nick Kelly Australian Digital Futures Institute, University of Southern Queensland
  • Kate Thompson Centre for Research in Computer Supported Learning and Cognition (CoCo), The University of Sydney
  • Pippa Yeoman Centre for Research in Computer Supported Learning and Cognition (CoCo), The University of Sydney

DOI:

https://doi.org/10.18608/jla.2015.22.3

Keywords:

Automated discourse analysis, collaborative learning, orchestration, learning analytics, topic detection

Abstract

This paper describes theory-led design as a way of developing novel tools for learning analytics. It focuses upon the domain of real-time automated discourse analysis (ADA) of group learning activities to facilitate instructor orchestration of online groups. The paper outlines the literature on the development of LA especially within the domain of ADA, and proposes that there is reason to conduct more tool development based upon first-principles. It describes first principles as being drawn from theory and subsequently informing the structure and behaviour of tools and presents a framework for this process. The framework is substantiated through the example of developing a new tool for assisting instructors with the orchestration of online groups. A description of the tool is given and examples of results from use with real-world data are presented. The paper concludes that whilst design purely from first principles may be elusive, the call is for more intent to explicitly connect the design process to theory on the basis that this has the potential to yield innovation when developing tools as well as the prospect of a the outcomes from tools connecting back to theory.

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Published

2015-12-07

How to Cite

Kelly, N., Thompson, K., & Yeoman, P. (2015). Theory-led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning. Journal of Learning Analytics, 2(2), 14-43. https://doi.org/10.18608/jla.2015.22.3

Issue

Vol. 2 No. 2 (2015): Learning Analytics and Learning Theory

Section

Special Section: Learning Analytics and Learning Theory

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