A smartphone-based adaptive learning approach to gamified clinical training in low-income countries
Keywords: clinical training
technology enhanced learning
smartphones
adaptive learning
low income countries
mobile phones
knoweldge tracing

Of the estimated 2.9 million neonatal lives that are lost each year globally, Sub-Saharan Africa (SSA) has the highest overall risk of death within the first 24 hours of life, accounting for 37% of global deaths. Severe workforce shortages, coupled with a health workforce skill imbalance and maldistribution, and a lack of training opportunities are likely to be key contributors to this high mortality rate. Given the lack of capacity to run face-to-face training at scale, new digital approaches that leverage the growing ubiquity of smartphone devices are being considered for training across SSA’s health systems. However, little evidence exists on the implementation of digital learning interventions that are: (a) relevant to the context of SSA; (b) consider healthcare providers’ diverse initial and continuing clinical training needs; and (c) adapt learning content as learners continue to develop their knowledge. This is despite research – from non-clinical, highresource contexts – showing that digital learning platforms that use either gamified approaches or adapt to learner needs have a significant positive effect on learning outcomes.

This thesis aims to study how gamified approaches to smartphone-based learning can be configured to support scaffolded Self-Regulated Learning (SRL) for clinical training in low-income countries (LICs). Through studying the contextual, self-directed learning needs of healthcare providers, this thesis builds a systematic understanding of the nature and pattern of use of gamified digital learning interventions and their impact on clinical learning outcomes.

The research questions addressed are: (a) What is the effectiveness of offering adaptive versus standardised feedback on learning gains on neonatal care emergency scenarios?; (b) What is the effect learner characteristics and SRL behaviours had on individualised learning gains?; and (c) What are the knowledge tracing approaches that are most suited for this context and subject domain?; (d) What are the learning experiences and perceptions of healthcare providers regarding gamified smartphone-based learning?, and (e) How do these learning experiences influence their SRL efforts? The methodology used to answer these questions was divided into three phases incorporating semi-structured in-depth interviews, Nominal Group Technique, survey methodology and a randomised experiment. The target population was healthcare providers of all cadres from low-income countries, from students to consulting specialist physicians.

The findings detail how adaptive learning can be designed and implemented to leverage the SRL behaviours of healthcare providers. They shed light on why within-platform learning feedback (that elaborates on the consequences of [in]action or erroneous action) is preferred to reflective feedback, and illuminate clinicians’ expectations of learning experiences. Overall, the findings suggest that digital learning platforms should help to build a learner’s confidence in the knowledge gained, so as it can be applied in their routine clinical setting. By doing so, future improvements in clinical outcomes in LIC health systems may be realised as part of holistic workplace capacity development strategies.