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: overcoming the barriers to large-scale adoption

Rebecca Ferguson, Doug Clow

Shane Dawson, Leah Macfadyen

Shirley Alexander, Alfred Essa

LAK14: Indianapolis

“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.

Beyond Prototypes model of the TEL Complex

Data wranglingat The Open University

Rebecca FergusonThe Open University, UK

LAK14: Indianapolis

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

Talking the same language

Resource page? Sub page? URL?Significance of dates?

Understanding learning design

How many forums?What were their roles?How were they timetabled?

Agreeing on conventions

80% agreed or strongly agreed that….

Is that80% of registered students?80% of those who completed the survey?80% of those who completed both survey and course?

Or is it80% of survey respondents who completed thecourse and did not select ‘not applicable’

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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