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research article

Designing for impact: a conceptual framework for learning analytics as self-assessment tools

Tormey, Roland  
•
Hardebolle, Cecile  
•
Pinto, Francisco  
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2020
Assessment & Evaluation In Higher Education

Although it is frequently claimed that learning analytics can improve self-evaluation and self-regulated learning by students, most learning analytics tools appear to have been developed as a response to existing data rather than with a clear pedagogical model. As a result there is little evidence of impact on learning. Even fewer learning analytics tools seem to be informed by an understanding of the social context and social practices within which they would be used. As a result, there is very little evidence that learning analytics tools are actually impacting on practice. This paper draws on research in self-regulated learning and in the social practices of learning and assessment to clarify a series of design issues which should be considered by those seeking to develop learning analytics tools which are intended to improve student self-evaluation and self-regulation. It presents a case study of how these design issues influenced the development of a particular tool: the Learning Companion.

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Type
research article
DOI
10.1080/02602938.2019.1680952
Web of Science ID

WOS:000498463700001

Author(s)
Tormey, Roland  
Hardebolle, Cecile  
Pinto, Francisco  
Jermann, Patrick  
Date Issued

2020

Published in
Assessment & Evaluation In Higher Education
Volume

45

Issue

6

Start page

901

End page

911

Subjects

Education & Educational Research

•

learning analytics

•

self-regulated learning

•

social practice

•

feedback

•

dialogue

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
AVP-E-CAPE  
AVP-E-LEARN  
CEDE  
Available on Infoscience
December 5, 2019
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/163552
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