Louis Major and Gill Francis
Summary
This rapid evidence review (RER) provides an overview of existing research on the use of technology to support personalised learning in low- and middle-income countries (LMICs). The RER has been produced in response to the widespread global shutdown of schools resulting from the outbreak of Covid-19. It therefore emphasises transferable insights that may be applicable to educational responses resulting from the limitations caused by Covid-19. In the current context, lessons learnt from the use of technology-supported personalised learning — in which technology enables or supports learning based upon particular characteristics of relevance or importance to learners — are particularly salient given this has the potential to adapt to learners’ needs by ‘teaching at the right level’.
This RER provides a summary of the potential benefits of technology-supported personalised learning as well as identifying possible limitations and challenges. It intends to inform educational decision makers, including donors and those in government and NGOs, about the potential to use technology-supported personalised learning as a response to the current pandemic. The findings and recommendations are also anticipated to be of interest to other education stakeholders (e.g. researchers and school leaders).
The RER involved a systematic search for academic and grey literature to address the overarching question: What is known about personalised learning through using technology that can be of value in responding effectively to mass school shutdowns in LMICs? After a rigorous screening process, 24 studies (in 12 countries) published since 2006 were analysed. Details on the inclusion criteria, as well as the associated limitations, are explained in the methodology section. Two specific research questions (RQs) guided the enquiry:
- How has technology-supported personalised learning been implemented in LMICs?
- What key themes are reported in the literature that may inform a response to the Covid-19 pandemic?
While a number of potential research limitations must be taken into account, on the whole, an encouraging and positive impact on learning outcomes is reported. Indeed, the RER demonstrates that there is a growing base of strong evidence on the impact of technology-supported personalised learning to support school-age learners in LMIC contexts.
Research involving a range of digital technologies and learners of various ages is reported. Studies mainly target instruction in mathematics and science although there are examples of research involving the development of non-cognitive skills. Importantly, the RER corroborates previous research which suggests there is no agreed definition of technology-supported personalised learning. It notes that ‘personalised learning’ does not necessarily mean ‘individualised learning’; it can include group-level adaptation and collaborative learning. Levels of personalisation also appear to fall on a con