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

An overview of 25 years of research on digital personalised learning in primary and secondary education: A systematic review of conceptual and methodological trends - Van Schoors, Rani; Elen, Jan; Raes, Annelies; Depaepe, Fien (British Journal of Educational Technology, 2021)
Due to the increasing digitisation, interest in digital personalised learning (DPL) continues to grow. Many empirical studies on the effect of adaptive tools have used a wide variety of conceptualisations and operationalisations of DPL. This systematic review aims to address the lack of consensus by presenting an analysis of empirical studies on technology for DPL in primary and secondary education. The work is guided by the following questions: (1) What are some different conceptualisations used in DPL research? (2) What types of tools are used in the studies and how are they implemented? (3) What is the current evidence on the impact of DPL with regard to student outcomes considering the nature of the current studies? A Boolean search string was used in the databases Web of Science and ERIC, resulting in a dataset containing 6,908 papers. A screening based on specific inclusion and exclusion criteria yielded 53 papers. Our findings revealed a great diversity in DPL conceptualisations, with several authors not defining the concept and others providing information regarding different elements such as technology, personalisation, personalisation target, personalisation source, personalisation method and personalisation outcomes. In line with these differences in conceptualisation of DPL, several DPL tools were used across the studies. Concerning the impact of DPL, a positive trend was observed on learning outcomes, although methodological differences need to be considered. The review ends with guidelines for future research. Practitioner notes What is already known There are many definitions and terms concerning DPL, resulting in a lack of consensus in conceptualisation. There is a wide variety of DPL tools with different adaptive dimensions. Many authors emphasise the benefits of DPL in educational practice including a possible impact on learning gains. What this paper adds Contribution to a thorough understanding of the conceptualisation of DPL. Insights into the diversity in DPL tools building on a framework of adaptivity by Vandewaetere and Clarebout (2014) and adds focus on tool implementation as a context element. Insight into the impact of DPL taking into account study design and outcome indicators. Implications for practice and/or policy An overview of the affordances of DPL to educational researchers, educational policy makers, and teachers is provided that can encourage them to think about its opportunities for everyday practice. Concrete suggestions for future research are discussed.
Keywords: adaptive learning; adaptive technology; digital personalised learning; educational technology; systematic review

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: computer-assisted learning; learning outcomes; low- and middle-income; meta-analysis; personalisation; personalised adaptive learning

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)
Abstract 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: computer-assisted learning; learning outcomes; low- and middle-income; meta-analysis; personalisation; personalised adaptive learning

Digital Personalised Learning to Improve Numeracy Outcomes in Kenyan Primary School Classrooms - EdTech Hub (EdTech Hub, 2021)

Problem Analysis and Focus of EdTech Hub’s Work: Technology in education in low- and middle-income countries - Hennessy, Sara; Jordan, Katy; Wagner, Daniel A.; EdTech Hub Team (EdTech Hub, 2021)
Keywords: _C:Afghanistan AFG; _C:Bangladesh BGD; _C:Botswana BWA; _C:Congo, Democratic Republic COD; _C:El Salvador SLV; _C:Gambia GMB; _C:Germany DEU; _C:Ghana GHA; _C:India IND; _C:Indonesia IDN; _C:Ireland IRL; _C:Jordan JOR; _C:Kenya KEN; _C:Lebanon LBN; _C:Liberia LBR; _C:Malawi MWI; _C:Pakistan PAK; _C:Peru PER; _C:Philippines PHL; _C:Rwanda RWA; _C:Senegal SEN; _C:Sierra Leone SLE; _C:South Africa ZAF; _C:Tanzania TZA; _C:Uganda UGA; _C:United Kingdom GBR; _C:United States USA; _C:Uruguay URY; _C:Zambia ZMB; _C:eSwatini SWZ; _DOILIVE; _EdTechHub_Output; _MELA_seen; __C:scheme:1; ___working_potential_duplicate; _cover:v3; _zenodo:submitted; _zenodoETH; ⛔ No INSPIRE recid found

A Country-Level Research Review: EdTech in Tanzania - Jordan, Katy; Proctor, Jamie; Koomar, Saalim; Bapna, Akanksha (Zenodo, 2021)
This document presents a review of the research landscape in Tanzania in relation to EdTech research focused on learners, teachers, or systems at the level of school-based education, excluding higher education (HE). The review draws upon the research literature, policy documents, grey literature, and interviews with key stakeholders in order to present an overview of the research landscape in Tanzania. There is a substantial body of relevant EdTech research which has been undertaken in Tanzania in the past decade. Eighty research articles were identified for inclusion in the review. This document provides an overview of trends in this literature and key actors and projects, and provides a specific focus upon existing research which relates to EdTech Hub’s ‘high-potential evidence gaps’ (HPEG) framework. In combination with political economy analysis, three areas for future research which would be practical and likely to have high impact are identified and described.
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:v3; _zenodoETH

Investigating the Impact on Learning Outcomes Through the Use of EdTech During Covid-19: Evidence from an RCT in the Punjab province of Pakistan - Adil, Fareeha; Nazir, Rabia; Akhtar, Misbah (EdTech Hub, 2021)
The objective of the current study is to test the impact of low-tech solutions on maths, Urdu, and English scores for students in the underdeveloped district of Bahawalnagar, which is situated in the southern part of Punjab in Pakistan. The target population for this study is Grade 8 students attending private schools. We have tested the impact of three interventions, namely: Teaching at the right level (TaRL), Fortnightly assessments (FAS) Digital teacher training sessions (DTS) Our findings show a significant and positive ‘Intention to Treat’ (ITT) impact on Urdu and English scores of the students in the TaRL treatment group. The students increased their English and Urdu scores by 0.56 SD. However, we found no significant impact of the intervention on maths scores in the TaRL treatment group. Fortnightly assessments and digital teacher training sessions were also found to contribute to higher English scores of the students. However, we found no ITT impact on the maths and Urdu scores for these treatment groups. The Local Average Treatment Effect (LATE) analysis revealed positive and significant improvement in Urdu and English scores of the students in the TaRL treatment group. Key stakeholders whom we interviewed suggested that redesigning the curriculum and incorporating TaRL within this approach could facilitate enhancement in learning outcomes in students in deprived areas. Our findings are important to help inform policymakers on the importance of designing and implementing cost-effective, low-tech solutions to help reduce learning gaps. An output of the EdTech Hub, https://edtechhub.org
Keywords: _r:AddedByZotZen

Using EdTech to Support Learning Remotely in the Early Years. Rapid Literature Review of Evidence from the Global Response to Covid-19. - Korin, Astrid (EdTech Hub, 2021)
An output of the EdTech Hub, https://edtechhub.org This topic brief examines the literature on technology-based, remote approaches to supporting learning in the early years for children from birth to age five, identifying promising practices for using EdTech in early childhood education (ECE) in low- and middle-income countries (LMICs). It draws on the nurturing care framework, Principles for Digital Development, and effective pedagogical practices for ECE.
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:v3; _r:AddedByZotZen; _zenodo:submitted; _zenodoETH

Education during the COVID-19: crisis Opportunities and constraints of using EdTech in low-income countries - Jordan, Katy; David, Raluca; Phillips, Toby; Pellini, Arnaldo (Revista de Educación a Distancia (RED), 2021)
The Covid-19 pandemic has ushered in a period of educational disruption on an unprecedented scale. During this time of crisis, education will not be business as usual, and EdTech alone cannot close the learning gap. It will be dedicated teachers and resilient educators who will ensure learning doesn’t st op — but they could be helped by the right EdTech tools. However, the digital divide means that internet and mobile network access varies greatly in middle and low - income countries. In this discussion paper, we explore some of the key constraints of using EdTech at scale to support education in low - income countries at a time of crisis, and highlight the opportunities that have so far emerged, in a rapidly - changing context. We draw upon evidence and examples to inform policy and programming decisions, moving from the initial emergency response to building resilience in the longer term, and planning to diagnose and treat the learning gaps that have emerged during the crisis.
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; ___working_potential_duplicate; _zenodo:submitted; países de bajos ingresos

A Theory of Change for a Technology-Enhanced Education System in Bangladesh - Clark-Wilson, Alison; Bashir, Amreen; Kaye, Tom (EdTech Hub, 2021)
The first of a trilogy of Theories of Change (TOCs) that focuses on learners as the main beneficiaries of an increasingly technology-enhanced education system in Bangladesh. Initially created with stakeholders to support the monitoring and evaluation of programmes designed to offer distance learning during the 2020 Covid-19 school closures, the TOC describes how access to educational activities of different modalities (TV, Radio, Smartphone, online platforms etc.) should lead to improved educational outcomes for learners in Classes 1-12. Keywords: Bangladesh; Theory of Change; technology-enhanced learning; education An output of the EdTech Hub, https://edtechhub.org
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:analysis:nopdf; _r:AddedByZotZen; _zenodo:submitted

Country-Level Research Review: EdTech in Ghana - Tsapali, Maria; Major, Louis; Damani, Kalifa; Mitchell, Joel; Taddese, Abeba (EdTech Hub, 2021)
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:v3; _zenodo:submitted; _zenodoETH; ⛔ No DOI found

Technology, Teacher Professional Development and Low- and Middle-Income Countries: Technical report on systematic mapping review - Hennessy, Sara; D'Angelo, Sophia; McIntyre, Nora; Koomar, Saalim; Kreimeia, Adam; Cao, Lydia; Brugha, Meaghan; Zubairi, Asma (EdTech Hub, 2021)
An output of the EdTech Hub, https://edtechhub.org
Keywords: ___working_potential_duplicate; _r:AddedByZotZen

Country-Level Research Review: EdTech in Kenya - Myers, Christina; Kaye, Tom; Bapna, Akanksha; Williams, Ayesha; Mitchell, Joel (EdTech Hub, 2021)
An output of the EdTech Hub, https://edtechhub.org
Keywords: _DOILIVE; _r:AddedByZotZen; _zenodo:submitted

EdTech and Covid-19: Insights from our Sandbox Portfolio. In Collaboration with Sandbox Partner Organisations - Rahman, Asad; Plaut, Daniel; Salami, Taiye; Carter, Alice (EdTech Hub, 2021)
An output of the EdTech Hub, https://edtechhub.org
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _r:AddedByZotZen; _zenodo:submitted

Country-Level Research Review: EdTech in Bangladesh - Zubairi, Asma; Kreimeia, Adam; Kaye, Tom; Ashlee, Amy (EdTech Hub, 2021)
An output of the EdTech Hub, https://edtechhub.org
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; ___working_potential_duplicate; _r:AddedByZotZen; _zenodo:submitted

Cost-Effectiveness and EdTech: Considerations and case studies - Chuang, Rachel; Burnett, Nicholas; Robinson, Elizabeth (EdTech Hub, 2021)
The answer to the question ‘What is cost-effective EdTech?’ is highly nuanced, as it depends on the choice of the initiative, its design, implementation, intended audience, and how the local context is addressed. We compiled select case studies that examine how EdTech was used in cost-effective and less cost-effective ways. An output of the EdTech Hub, https://edtechhub.org
Keywords: F: Helpdesk response; _DOILIVE; _EdTechHub_Output; _MELA_seen; _r:AddedByZotZen; _zenodo:submitted

EdTech and Covid-19: 10 Things to Know - Nicolai, Susan; Wilson, Samuel; Jefferies, Kate (EdTech Hub, 2021)
EDTECH AND COVID-19 10 THINGS TO KNOW Covid-19 has reshaped our world. In education, mass school closures have accelerated the global use of education technologies. Yet the benefits do not reach everyone. Since the start of the pandemic, EdTech Hub and its partners have been researching and applying evidence on what works in technology for education in different contexts. Here…
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:v3; _zenodo:submitted; _zenodoETH

Country-Level Research Review: EdTech in Pakistan - Zubairi, Asma; Halim, Waqas; Kaye, Tom; Wilson, Sam (EdTech Hub, 2021)
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:v3; _zenodo:submitted; _zenodoETH; dode_eth-src-eth; dode_eth-trf2-dode

EdTech evidence for Covid-19 response: Rapid evidence reviews of EdTech use in low-income and crisis contexts - Jordan, Katy; Mitchell, Joel (EdTech Hub, 2021)
An output of the EdTech Hub, https://edtechhub.org
Keywords: _DOILIVE; _r:AddedByZotZen; _zenodo:submitted

Eight Reasons Why EdTech Doesn’t Scale: How sandboxes are designed to counter the issue - Simpson, Lea; Carter, Alice; Rahman, Asad; Plaut, Daniel (EdTech Hub, 2021)
The EdTech Hub’s sandbox approach offers implementers and decision makers a clear way to implement and scale only the most effective EdTech interventions. In this position paper we share our view on why EdTech isn’t scaling and how we see the sandboxes approach addressing them. Keywords: innovation; implementation; sandboxes; EdTech; scale; experimentation An output of the EdTech Hub, https://edtechhub.org
Keywords: _EdTechHub_Output; _MELA_seen; _r:AddedByZotZen

EdTech to Reach the Most Marginalised: A Call to Action - Zubairi, Asma; Kreimeia, Adam; Jefferies, Kate; Nicolai, Susan (EdTech Hub, 2021)
An output of the EdTech Hub, https://edtechhub.org
Keywords: _DOILIVE; ___working_potential_duplicate; _r:AddedByZotZen; _zenodo:submitted

تكنولوجيا التعليم وجائحة كوفيد 19 - .10 أشياء يجب معرفتها - EdTech Hub Team (2021)
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:v3; _zenodo:submitted; _zenodoETH

Les Technologies De L’enseignement Et Le Covid-19 - 10 Choses À Savoir - EdTech Hub Team (2021)
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:v3; _zenodo:submitted; _zenodoETH

Syṡtemic Mixed-Methods Research — a conceptual framework for scalable EdTech research - Haßler, Björn; El-Serafy, Yomna; Khalayleh, Abdullah; McBurnie, Chris (EdTech Hub, 2021)
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:v3; _yl:n; _zenodoODE; dode_eth-src-eth; dode_eth-trf2-dode

Methodology for literature reviews - Haßler, Björn; Adam, Taskeen; Allier-Gagneur, Zoe; Blower, Thomas; Brugha, Meaghan; Damani, Kalifa; Hennessy, Sara; Martin, Kevin; Megha-Bongnkar, Ghislaine; Murphy, Mary; Walker, Hannah; Walker, Hannah (EdTech Hub, 2021)
An output of the EdTEch Hub
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _cover:v3; _yl:k; _zenodoODE; dode_eth-src-eth; dode_eth-trf2-dode

T-TEL Covid-19 Impact Assessment Study - Ananga, Eric; Kadiri, Abdul-Karim; Kporwodu, Marie; Nkrumah, Yahya; Whajah, Francis; Tackie, Majorie (2021)
Keywords: _DOILIVE; _EdTechHub_Output; _MELA_seen; _zenodo:submitted