Challenge and Potential of Fine Grain, Cross-Institutional Learning Data

Alan Dix

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

3 Citations (Scopus)
157 Downloads (Pure)

Abstract

While MOOCs and other forms of large-scale learning are of growing importance, the vast majority of tertiary students still study in traditional face-to-face settings. This paper examines some of the challenges in attempting to apply the benefits of large-scale learning to these settings, building on a growing repository of cross-institutional data.
Original languageEnglish
Title of host publication Proceedings of the Third (2016) ACM Conference on Learning @ Scale
PublisherAssociation for Computing Machinery
Pages261-264
ISBN (Print)978-1-4503-3726-7
DOIs
Publication statusPublished - 25 Apr 2016
EventThe Third ACM Conference on Learning @ Scale (L@S 2016) - Edinburgh, United Kingdom
Duration: 25 Apr 201626 Apr 2016

Conference

ConferenceThe Third ACM Conference on Learning @ Scale (L@S 2016)
Country/TerritoryUnited Kingdom
CityEdinburgh
Period25/04/1626/04/16

Keywords

  • MOOCs
  • linked data
  • learning analytics
  • education technology
  • reading lists
  • OER

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