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
ZenodoArchiveID: 7074857 ZenodoArchiveConcept: 7074856 KerkoCite.ItemAlsoKnownAs: 10.5281/zenodo.6326179 10.5281/zenodo.7074857 10.53832/edtechhub.0114 2405685:K5BJUBRE 2405685:REW8F5TJ 2405685:U6G7C62D
Keywords: _r:AddedByZotZen

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/
ZenodoArchiveID: 10628960 KerkoCite.ItemAlsoKnownAs: 10.53832/edtechhub.1011 ZenodoArchiveConcept: 10628959
Keywords: _r:AddedByMyEducationEvidence

Technology-Supported Personalised Learning: A Rapid Evidence Review - Major, Louis; Francis, Gill A. (EdTech Hub, 2020)
This publication is one part of a series of rapid evidence reviews that has been produced by the EdTech Hub. The purpose of the rapid evidence reviews is to provide education decision-makers with accessible evidence-based summaries of good practice in specific areas of EdTech. They are focused on topics which are particularly relevant in the context of widespread global challenges to formal schooling as a result of COVID-19. All the rapid evidence reviews are available at edtechhub.org.
ZenodoArchiveID: 4556925 PreviousDOI: 10.5281/zenodo.3948175 PreviousDOI: 10.5281/zenodo.4477170 PreviousShortDOI: 10/gg7sp2 KerkoCite.ItemAlsoKnownAs: 10.5281/ZENODO.3948175 10.5281/zenodo.3948174 10.5281/zenodo.3948175 10.5281/zenodo.4477170 10.5281/zenodo.4556925 2339240:6NYL4Q6K 2339240:782897NS 2339240:CQIWZXYK 2339240:FFVXKB6Y 2339240:FH2WAXTQ 2339240:KAWEDEAZ 2339240:L9THHN3N 2339240:P8B4HPZC 2339240:QLA593HB 2339240:T58E6LDA 2339240:T8L6PTRX 2339240:VZBB4HAF 2405685:839AFBBS 2405685:89H7NAA7 2405685:A2II5ZV7 2405685:A49KTEL6 2405685:AT6JS3QN 2405685:CJR7PMKJ 2405685:DEXS2WA8 2405685:FFSBB3JJ 2405685:NQSPAG3I 2405685:RVZFVD7G 2405685:U95XV67E 2405685:WJRBJQBN 2534378:8FA5G2KF
Keywords: F: Evidence review; LP: English; _DOILIVE; _EdTechHub_Output; _MELA_seen; ___working_potential_duplicate; _cover:v3; _zenodo:submitted; _zenodoETH

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/
ZenodoArchiveID: 15792725 KerkoCite.ItemAlsoKnownAs: 10.53832/edtechhub.1125 ZenodoArchiveConcept: 15792724
Keywords: _r:AddedByMyEducationEvidence

Effective Use of EdTech for Remedial Learning Programmes: Considerations for Mongolia - Upadhyay, Arjun; Shoobridge, James; Moss Coflan, Caitlin (EdTech Hub, 2020)
This document was produced in response to a request from the World Bank Mongolia team to: 1. Outline the evidence of effective practices on remedial education generally. 2. Explore appropriate uses of EdTech to support remedial education. 3. Summarise the implications of these findings for Mongolia.
previousDOI: 10.5281/zenodo.3958080 KerkoCite.ItemAlsoKnownAs: 10.5281/zenodo.3958080 10.5281/zenodo.5651111 2339240:3DJBGPQM 2339240:AWK2HEZ5 2405685:IJGQTHH9 2405685:UMZVQ4TV 2405685:ZEDSYPGH
Keywords: F: Helpdesk response; _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:analysis:nopdf; _zenodo:submitted

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.
ZenodoArchiveID: 7267302 ZenodoArchiveConcept: 7267301 KerkoCite.ItemAlsoKnownAs: 10.5281/zenodo.7267302 10.53832/edtechhub.0127 2339240:V7ARHU93 2405685:GBBGHCBH 2405685:QADQUWU3 2405685:UTTZNZ24
Keywords: _r:AddedByZotZen