Winters, N;
Oliver, M;
Langer, L;
(2016)
Can mobile health training meet the challenge of ‘measuring better’?
Comparative Education
, 53
(1)
pp. 115-131.
10.1080/03050068.2017.1254983.
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Abstract
Mobile learning has seen a large uptake in use in low- and middle-income countries. This is driven by rhetorics of easy scaling, reaching the hard-to-reach and the potential for generating analytics from the applications used by learners. Healthcare training has seen a proliferation of apps aimed at improving accountability through tracking and measuring workplace learning. A view of the mobile phone as an agent of change is thus linked with a technocentric approach to measurement. Metrics, initially created as proxies for what gets done by health workers, are now shaping the practices they were intended to describe. In this paper, we show how, despite some valiant efforts, ‘measuring better’ remains difficult to achieve due to entrenched views of what measurement consists of. We analyse a mobile health (mHealth) classification framework, drawing out some implications of how it has been used in training health workers. These lead us to recommend moving away from a view of mobile learning linked tightly to accountability and numbers. We suggest a focus on an alternative future, where ‘measuring better’ is promoted as part of socio-cultural views of learning and linked with a social justice conceptualisation of development.
Type: | Article |
---|---|
Title: | Can mobile health training meet the challenge of ‘measuring better’? |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1080/03050068.2017.1254983 |
Publisher version: | http://doi.org/10.1080/03050068.2017.1254983 |
Language: | English |
Additional information: | © 2016 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Mobile learning, mHealth, categorisation |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media |
URI: | https://discovery.ucl.ac.uk/id/eprint/1532854 |
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