Setting learning analytics in context

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Part of a panel discussion at Learning Analytics and Knowledge 2014 - LAK14 - in Indianapolis.
This presentation contains the first and last sections of the panel discussion.

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Setting learning analytics in context

  1. 1. Setting learning analytics in context: overcoming the barriers to large-scale adoption Rebecca Ferguson, Doug Clow Shane Dawson, Leah Macfadyen Shirley Alexander, Alfred Essa LAK14: Indianapolis
  2. 2. “The many elements of the „TEL Complex‟ must all be taken into account as an innovation is designed, developed and embedded” Scanlon, E., Sharples, M., Fenton- O'Creevy, M., Fleck, J., Cooban, C., Ferguson, R., Cross, S., Waterhouse, P. (2013). Beyond Prototypes. London: TEL Research Programme.
  3. 3. Beyond Prototypes model of the TEL Complex
  4. 4. Data wrangling at The Open University Rebecca Ferguson The Open University, UK LAK14: Indianapolis
  5. 5. Disparate data VLE (Moodle) data Survey data Help desk data Library data Assessment data Registration data 250,000 students around the world Faculty expertise Learning design Learning outcomes Assessment strategy Module connections Resource understanding Data Wranglers Tacit knowledge
  6. 6. Talking the same language Resource page? Sub page? URL? Significance of dates?
  7. 7. Understanding learning design How many forums? What were their roles? How were they timetabled?
  8. 8. Agreeing on conventions 80% agreed or strongly agreed that…. Is that 80% of registered students? 80% of those who completed the survey? 80% of those who completed both survey and course? Or is it 80% of survey respondents who completed the course and did not select „not applicable‟
  9. 9. Thinking through ethical issues Support, not surveillance Reporting at module level, not individual level Survey responses kept apart from activity data Making data accessible, not overwhelming Negotiating meaning, not dictating interpretation

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