The counterintuitive self-regulated learning behaviours of healthcare providers from low-income settings. (June 2021)

• Record Type: Journal Article
• Authors: Tuti, Timothy; Paton, Chris; Winters, Niall
• Is Part Of: Computers & education. Volume 166(2021)
• Publication Date: 2021-06
• Subjects: Mobile learning -- Online learning -- Clinical training -- Latent profile analysis -- Self-regulated learning -- Low-income settings; Education -- Data processing -- Periodicals; Education -- Periodicals; Computers -- Periodicals; Computer-Assisted Instruction -- Periodicals; Éducation -- Informatique -- Périodiques; Electronic journals; 370.285
• DOI: 10.1016/j.compedu.2021.104136
• Languages: English
• ISSNs: 0360-1315

Abstract

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. Highlights: Work experience is most significant in enhancing high self-regulated learning of healthcare providers in Low Income Countries. Help-seeking when using digital learning platforms is generally low in healthcare providers from Low Income Countries. Scaffolding learning content difficulty by SRL profile may boost learning gains from a low-dose-high-frequency training model. SRL might be ill-equipped to capture the influence of context on regulation of learning behaviours within clinical practice.