Wednesday 25th October, 2023

The long-term goal for this project is to ensure that the supply of AI tools for education in low and middle-income countries (LMICs) are high quality, and available to meet the needs of their students. We want to create a vibrant community of AI in education in LMICs. This challenge is too great for any single organisation. However, by sharing our ideas and building collaboratively, we aim to help shape the development of AI use in education in LMICs.

There are three elements to the programme:

1. Convenings

Events to bring the community together and discuss challenges and solutions. The first of these was held on 3rd October and focussed on AI & Assessments. The event brought together nearly 100 participants from across 17 low-income countries, mostly across sub-Saharan Africa, alongside participants from North America and Europe including educators from government, international and local NGOs, implementers, tech-startup networks, technology developers and large assessment companies – event summary available here.

2. Learning by Doing

Grantees will be given funds to support the piloting and development of their tools.

3. Open Knowledge Platform

This will host materials used in the convening, and will grow to host ideas, guidance, shared knowledge and open-source code and tools to help the education community learn how to sensibly integrate AI into their work helping children learn. It will be a space that helps shape the development of new tools and products, and the integration of AI into existing ones. It will help tech-innovators and educators by lowering the cost of their tools and shaping them to best practice for FLN. We welcome any contributions here – this is a space to share your ideas and learnings.

More details will be shared soon! In the meantime please contact Sirin Tangpornpaiboon if you have any queries.

Sirin.Tangpornpaiboon@fabinc.co.uk

AI & Assessments Event Summary PDF (1.4MB)

Monday 7th March, 2022

Fab Inc is pleased to announce it is launching a study on the impact of GIS-supported teacher allocation in Sierra Leone as part of a research portfolio from EdTech Hub. The portfolio represents the largest public-private investment in primary research around EdTech evidence in low- and middle-income countries to date.

The nearly GBP 5.5 million-portfolio was commissioned by EdTech Hub to fill the evidence gap decision-makers grapple with when choosing EdTech interventions to support children, teachers, and school communities. Our study, The impact of GIS-supported teacher allocation in Sierra Leone, will specifically focus on how a preference matching model can be used to ensure the best outcomes.

“We are thrilled to be collaborating with Fab Inc as one of the studies in our research portfolio,” says EdTech Hub Executive Director Verna Lalbeharie. “The evidence generated by this study, we hope, will inform key, future education decisions, and influence the design, development and implementation of EdTech solutions for our world’s most vulnerable learners.”  

EdTech Hub initially issued a call for expressions of interest in Summer 2021; 104 proposals were received. The 13 selected studies will take place in and focus on Bangladesh, Ghana, Kenya, Pakistan, Sierra Leone, and Tanzania. The EdTech Hub research portfolio will be conducted over the next two to three years and is supported by the FCDO, Bill & Melinda Gates Foundation, and the World Bank.

Friday 17th September, 2021

This report learned from the experience of both Ebola and data management efforts to help inform post-Covid-19 recovery including a data architecture for a resilient education data ecosystem in Sierra Leone and elsewhere. This was built on the construction of a combined database containing Annual School Census data at the school level from 2015–2019, and at the district level from 2011–2013.

Analysis of enrolment and Ebola case data highlighted the ongoing importance of geographical and economic factors in determining education access, over and above the short-term health impacts of such crises. This has also enabled a detailed consideration of the data architecture within Sierra Leone to inform ongoing stakeholder discussions in this area, as well as demonstrating the potential benefits of improved data structures for data analysis, visualisation, and use through a dashboard.

This has been warmly received, with the government looking to take over ownership of the database, display the dashboard publicly, and inform ongoing policy development and implementation. Finally, key principles and step-by-step guides for replicating this work have been provided to support similar efforts in other countries which face comparable challenges to Sierra Leone in terms of both data availability and consistency, and the potential use of this data to support Covid-19 school reopening.

Full Paper PDF (6.5MB)

Wednesday 14th April, 2021

In this video abstract for Young Lives, María José Ogando Portela discusses her and Dr Paul Atherton’s paper on First Generation Learners and introduce a dynamic definition – using longitudinal data to identify where children become a first generation learner by reaching a grade not reached by their parents.

Friday 19th March, 2021

“GIS offers a visual and more nuanced understanding of teacher shortages, and it helps identify local solutions” says Ally Mackintosh.

Tuesday 15th December, 2020

The Education Workforce Initiative (EWI), funded by UK Aid, partnered with Fab Inc. and Sierra Leone’s Teaching Service Commission (TSC) to support strengthening the education workforce. The research and analysis applied a systemic lens across the workforce lifecycle, considering how to improve the supply and demand of teachers across Sierra Leone, but especially in the most disadvantaged areas.

The project worked adaptively and collaboratively with stakeholders across government, teacher unions, and development partners to produce a series of research and policy papers aimed at supporting both government policymaking and development partner activities. These five evidence papers covered key aspects of the education workforce: management; spatial analysis; supply and needs; recruitment and matching; and costed options.

1. Education Workforce Management in Sierra Leone (PDF 2.1MB)
2. Education Workforce Spatial Analysis in Sierra Leone (PDF 2.2MB
3. Education Workforce Supply and Needs in Sierra Leone (PDF 1.8MB)
4. Education Workforce Recruitment and Matching in Sierra Leone (PDF 1.7MB)
5. Education Workforce Costed Options Paper (PDF 1.7MB)

Tuesday 17th November, 2020

Outsmarting your parents: Being a first-generation learner in developing countries

Abstract: We use data from the Young Lives surveys, in Ethiopia, India, Peru, and Vietnam, to highlight an underappreciated phenomenon—that a substantial proportion of students in developing countries are the first in their families to go to school. We term these students first‐generation learners (FGLs). We both propose a simple “static” definition of FGL status—where a child’s parents have no education attainment—and utilise the panel dynamics of the Young Lives data set to look at a “dynamic” definition—where the child, in any given round of data collection, is enrolled at a level which his or her parents did not reach. We show descriptive statistics on the scale of this problem across the four countries. We find strong, consistent patterns of relative educational deprivation for FGLs. We tentatively explore the pathways through which FGL status may affect outcomes and find possible explanations through an inability to support with homework and lower aspirations. We look at how becoming an FGL affects the probability of being in school using child fixed‐effects estimations and find it increases the vulnerability of children to drop out.

Review of Development Economics, Vol. 24, Issue 4, November 2020