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|DOI (Digital Object Identifier) Link:||https://doi.org/10.1145/2330601.2330636|
|Google Scholar:||Look up in Google Scholar|
This paper develops Campbell and Oblinger's five-step model of learning analytics (Capture, Report, Predict, Act, Refine) and other theorisations of the field, and draws on broader educational theory (including Kolb and Schön) to articulate an incrementally more developed, explicit and theoretically-grounded Learning Analytics Cycle.
This cycle conceptualises successful learning analytics work as four linked steps: learners generating data that is used to produce metrics, analytics or visualisations. The key step is 'closing the loop' by feeding back this product to learners through one or more interventions.
This paper seeks to begin to place learning analytics practice on a base of established learning theory, and draws several implications from this theory for the improvement of learning analytics projects. These include speeding up or shortening the cycle so feedback happens more quickly, and widening the audience for feedback (in particular, considering learners and teachers as audiences for analytics) so that it can have a larger impact.
|Item Type:||Conference Item|
|Copyright Holders:||2012 ACM|
|Extra Information:||LAK '12
Proceedings of the 2nd International Conference on Learning Analytics and Knowledge
Editors: Simon Buckingham Shum, Dragan Gasevic, Rebecca Ferguson
ACM New York, NY, USA ©2012
|Keywords:||learning analytics; academic analytics, analytics; policy; feedback|
|Academic Unit/School:||Learning Teaching and Innovation (LTI) > Institute of Educational Technology (IET)
Learning Teaching and Innovation (LTI)
|Interdisciplinary Research Centre:||Centre for Research in Education and Educational Technology (CREET)|
|Depositing User:||Doug Clow|
|Date Deposited:||12 Sep 2012 09:13|
|Last Modified:||07 Feb 2017 16:10|
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