Student perspectives on data provision and use

Starting to unpack disciplinary differences

Jen Mcpherson, Scott J. Fatt, Huong Ly Tong, Danny Y. T. Liu

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

8 Citations (Scopus)

Abstract

How can we best align learning analytics practices with disciplinary knowledge practices in order to support student learning? Although learning analytics itself is an interdisciplinary field, it tends to take a 'one-size-fits-all' approach to the collection, measurement, and reporting of data, overlooking disciplinary knowledge practices. In line with a recent trend in higher education research, this paper considers the contribution of a realist sociology of education to the field of learning analytics, drawing on findings from recent student focus groups at an Australian university. It examines what learners say about their data needs with reference to organizing principles underlying knowledge practices within their disciplines. The key contribution of this paper is a framework that could be used as the basis for aligning the provision and/or use of data in relation to curriculum, pedagogy, and assessment with disciplinary knowledge practices. The framework extends recent research in Legitimation Code Theory, which understands disciplinary differences in terms of the principles that underpin knowledge-building. The preliminary analysis presented here both provides a tool for ensuring a fit between learning analytics practices and disciplinary practices and standards for achievement, and signals disciplinarity as an important consideration in learning analytics practices.

Original languageEnglish
Title of host publicationLAK 2016 Conference Proceedings, 6th International Learning Analytics and Knowledge Conference - Enhancing Impact: Convergence of Communities for Grounding, Implementation, and Validation
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery
Pages158-167
Number of pages10
ISBN (Electronic)9781450341905
DOIs
Publication statusPublished - 25 Apr 2016
Event6th International Conference on Learning Analytics and Knowledge, LAK 2016 - Edinburgh, United Kingdom
Duration: 25 Apr 201629 Apr 2016

Other

Other6th International Conference on Learning Analytics and Knowledge, LAK 2016
CountryUnited Kingdom
CityEdinburgh
Period25/04/1629/04/16

Keywords

  • Disciplinary differences
  • Knowledge
  • Learning analytics
  • Legitimation code theory
  • Sociology of education
  • Student needs

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