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The counterintuitive self-regulated learning behaviours of healthcare providers from low-income settings

Abstract:
Self-regulated learning (SRL) is useful for understanding self-directed learning practices. However, SRL behaviours - despite being deemed highly context-dependent - remain mostly unexplored for healthcare workers in low-income countries. This study details how SRL strategies vary and impact on healthcare providers' learning gains when using digital learning platforms. We apply Latent Profile Analysis (LPA) to questionnaire responses from a sample of 264 healthcare providers, arguably the first time LPA has been applied for the context in this subject-domain. We identified four SRL profiles: High, Above-Average with Low Help-Seeking, Average, and Low SRL profiles with significant differences in SRL strategies between the four profiles confirmed by Kruskal-Wallis test and logistic regression. Healthcare providers with more specialised clinical training were most likely to be in the Low SRL profile, but compared to the other profiles, maximised possible learning gains in the fewest learning iterations. From our findings, SRL may not adequately represent the nature of the interaction between these learners and contextual characteristics. Exploring the important role of various external learning regulation behaviours that influence healthcare providers SRL might help address this shortcoming. These findings provide insights into the learner factors to consider when implementing technology-mediated learning in these resource-contexts. They also offer plausible future research directions into how to maximise healthcare providers’ learning gains on digital platforms that is informed by how learners in low-income contexts regulate their self-directed learning.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.compedu.2021.104136

Authors


More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Education
Role:
Author
ORCID:
0000-0002-7915-3004
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Tropical Medicine
Role:
Author
ORCID:
0000-0001-6952-9621
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Education
Role:
Author


Publisher:
Elsevier
Journal:
Computers & Education More from this journal
Volume:
166
Article number:
104136
Publication date:
2021-02-06
Acceptance date:
2021-01-15
DOI:
ISSN:
0360-1315


Language:
English
Keywords:
Pubs id:
1158969
Local pid:
pubs:1158969
Deposit date:
2021-01-27

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