What is 'Nudging' and How Does it Change Behaviour in Education? - Koomar, Saalim (EdTech Hub, 2024)
This Learning Brief is part of the EdTech Hub Learning Brief Series, providing practical resources for people working to improve the use of technology in education. In this brief, we look at the behaviour change strategy of leveraging concise messages at strategic decision points (i.e., ‘nudging’) to influence the behaviour of a recipient towards a desired outcome. We focus on EdTech Hub’s work concerning nudge messaging. It builds on work from messaging interventions in Ghana and Kenya, linking these to the broader literature on the topic. It emphasises that although there is a strong and growing evidence base for nudge technologies, effective implementation remains dependent upon context-specific adaptation. It is not inevitable that nudge messaging interventions will lead to positive outcomes — indeed, outcomes are often mixed. It is therefore vital to understand the specific impacts of interventions on particular groups of recipients. We present findings and recommendations that should inform how nudging technologies in education are approached and what decision-makers need to consider in order to ensure uptake and minimise risks. Lastly, we explore areas that require further research, namely, the changing nature of nudging due to artificial intelligence, the safeguarding risks of nudging, persisting questions about cost-effectiveness, and how nudging can more specifically target learning. Keywords: Behavioural psychology; EdTech; education; messaging; nudging; participation An output of the EdTech Hub, https://edtechhub.org/
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Keywords: _r:AddedByMyEducationEvidence

EdTech for Education in Emergencies: A Rapid Evidence Review - Barnes, Katrina; Ramesh Vasudevan, Sharanya; Flam, Rebekka (EdTech Hub, 2025)
This Rapid Evidence Review (RER) provides a synthesis of recent evidence relating to the implementation of EdTech programmes, platforms, and devices in emergency contexts. The main aim of the review is to provide education decision-makers, funders, and implementers (among others) with a clear picture of ‘what works’ regarding EdTech in emergencies. Crucially, it also aims to create an understanding of the conditions necessary to ensure the effectiveness of these interventions. Accordingly, the results of the review are grouped under three key themes: types of EdTech that are most effective in emergencies; barriers and challenges that limit EdTech effectiveness in emergencies; and conditions for effective implementation of EdTech in emergencies. Keywords: Education in Emergencies; EdTech; crisis contexts; remote learning An output of the EdTech Hub, https://edtechhub.org/
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Keywords: _r:AddedByMyEducationEvidence

Understanding Teacher School Choice Preferences: What Matters Most for Teacher Deployment in Sierra Leone? (EdTech Hub Preprint, 2023)
This exploratory mixed-methods study investigates the factors that shape where teachers want to work in Sierra Leone. We identify five dominant factors: monetary incentives, school conditions, opportunities for professional development and support, school location, and relationships with the school and the community. Importantly, these factors combine to push and pull teachers to different locations. Moreover, the factors interact with individual teacher characteristics such as gender, family status, and experience to influence school choice preferences. This set of factors — and their interaction with certain teacher characteristics — continues to shape preferences as teachers move up the career ladder. Keywords: Teacher deployment, teacher preferences, Sierra Leone, teacher supply, remote schools 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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Keywords: _r:AddedByMyEducationEvidence

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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