The effectiveness of technology-supported personalised learning in low- and middle-income countries: A meta-analysis - Major, Louis; Francis, Gill A.; Tsapali, Maria (British Journal of Educational Technology, 2021)
Digital technology offers the potential to address educational challenges in resource-poor settings. This meta-analysis examines the impact of students' use of technology that personalises and adapts to learning level in low- and middle-income countries. Following a systematic search for research between 2007 and 2020, 16 randomised controlled trials were identified in five countries. Studies involved 53,029 learners aged 6–15 years. Coding examined learning domain (mathematics and literacy); personalisation level and delivery; technology use; and intervention duration and intensity. Overall, technology-supported personalised learning was found to have a statistically significant—if moderate—positive effect size of 0.18 on learning (p = 0.001). Meta-regression reveals how more personalised approaches which adapt or adjust to learners' level led to significantly greater impact (an effect size of 0.35) than those only linking to learners' interests or providing personalised feedback, support, and/or assessment. Avenues for future research include investigating cost implications, optimum programme length, and teachers' role in making personalised learning with technology effective. Practitioner notes What is already known about this topic? Promoting personalised learning is an established aim of educators. Using technology to support personalised learning in low- and middle-income countries (LMICs) could play an important role in ensuring more inclusive and equitable access to education, particularly in the aftermath of COVID-19. There is currently no rigorous overview of evidence on the effectiveness of using technology to enable personalised learning in LMICs. What this paper adds? The meta-analysis is the first to evaluate the effectiveness of technology-supported personalised learning in improving learning outcomes for school-aged children in LMICs. Technology-supported personalised learning has a statistically significant, positive effect on learning outcomes. Interventions are similarly effective for mathematics and literacy and whether or not teachers also have an active role in the personalisation. Personalised approaches that adapt or adjust to the learner led to significantly greater impact, although whether these warrant the additional investment likely necessary for implementation at scale needs to be investigated. Personalised technology implementation of moderate duration and intensity had similar positive effects to that of stronger duration and intensity, although further research is needed to confirm this. Implications for practice and/or policy: The inclusion of more adaptive personalisation features in technology-assisted learning environments can lead to greater learning gains. Personalised technology approaches featuring moderate personalisation may also yield learning rewards. While it is not known whether personalised technology can be scaled in a cost-effective and contextually appropriate way, there are indications that this is possible. The appropriateness of teachers integrating personalised approaches in their practice should be explored given ‘supplementary’ uses of personalised technology (ie, additional sessions involving technology outside of regular instruction) are common.
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:analysis:nopdf; _zenodo:submitted; computer-assisted learning; learning outcomes; low- and middle-income; meta-analysis; personalisation; personalised adaptive learning; ⛔ No DOI found

Randomised Controlled Trial Protocol: Digital personalised learning to improve literacy and numeracy outcomes in Kenyan classrooms - Major, Louis; Daltry, Rebecca; Otieno, Mary; Otieno, Kevin; Zhao, Annette; Hinks, Jessica; Sun, Chen; Friedburg, Aidan (EdTech Hub, 2023)
This protocol provides a detailed overview of a cluster-randomised controlled trial (RCT) being undertaken in pre-primary schools in Kenya. The RCT seeks to rigorously investigate the impact of a classroom-integrated digital personalised learning (DPL) tool on early grade numeracy and literacy learning outcomes. The protocol is being disseminated prior to endline data analysis to promote transparency and a comprehensive understanding of the RCT approach and design. This protocol was originally published in October 2023. This is an updated version where we have a) clarified that the sample size stated in Sections 2 and 2.2 is the 'pre-attrition' sample; and b) added a paragraph to Section 2.4.1 to provide further clarification regarding the use of code-switching. No changes to the analytical approach have been made. Keywords: digital personalised learning; DPL; Randomised controlled trial; RCT; research methodology; learning outcomes; Kenya An output of the EdTech Hub, https://edtechhub.org
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Artificial Intelligence and Education Systems in 2035: Fourteen trends and five scenarios for how the future might unfold - Rahman, Asad; Freeman, Abigail (EdTech Hub, 2025)
This strategic foresight study aims to understand the shifts that might take place in education systems in low- and middle-income country (LMIC) contexts, given developments in artificial intelligence (AI) that might occur over the next 10 years. It begins by capturing fourteen trends, relating to AI that might affect the development of education systems in LMICs. After identifying trends, we combined them to sketch five concrete, tangible scenarios. This understanding will inform a multi-year programme of work, addressing how LMICs can strengthen their capacity, in light of such future possibilities. An output of the EdTech Hub, https://edtechhub.org/
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EdTech Evidence From Covid-19 Response: A thematic review of primary research from Bangladesh, Ghana, Kenya, Pakistan and Sierra Leone - Nicolai, Susan; Jefferies, Kate; Stepanek Lockhart, Ashley (EdTech Hub, 2023)
To better understand the use of EdTech interventions as part of response to the Covid-19 pandemic, EdTech Hub commissioned ten small-scale research studies in five low- and middle-income countries: Bangladesh, Ghana, Kenya, Pakistan, and Sierra Leone. This paper includes insight into research methodologies across these studies, with particularly interesting findings on how EdTech effectiveness is being measured. A semi-structured thematic analysis further provides insights in relation to four main user groups of learners, girls, teachers, and parents and caregivers and points to a series of cross-cutting factors that are important for EdTech interventions in low-resource settings. An overarching takeaway centres on the fact that having technology in place is a small part of EdTech effectiveness, with wider teaching and learning ecosystems accompanying EdTech deserving more attention. Overall, the studies reveal a symbiotic relationship between people and technology, reinforcing that EdTech works best when users are involved across design, iteration, awareness building, and engagement. Keywords: EdTech, Covid-19, digital, education, learning, remote An output of the EdTech Hub, https://edtechhub.org
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Minoritised Languages, Education, and Technology: Current practices and future directions in low- and middle-income countries - Zhao, Annette; Mitchell, Joel; Gasanabandi, Gentille; Ullah, Noor; Barnes, Katrina; Koomar, Saalim (EdTech Hub, 2024)
This article explores the current status and future directions of mother-tongue-based multilingual education (MTB MLE) and the use of technology in low- and middle-income countries (LMICs), focusing on the use of minoritised mother tongues. An initial literature review of available academic sources in multiple languages reveals a lack of evidence on the use of technology in MTB MLE across different countries, especially multilingual contexts with greater linguistic diversity. To understand the issue in greater detail and to offer recommendations informed by current practice, interviews and a collaborative workshop with four organisations with relevant educational technology (EdTech) initiatives were conducted. The analysis covers facilitating and limiting factors these organisations have encountered, and the potential positive impact on learners and society generally. We conclude by identifying practical, policy, and research priorities for multilingual education and educational technology in general.
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