With finite financial resources for education around the world, ministers and policymakers are rightly preoccupied with efficiency and value for money. In our recent side event to the Global Education Summit, ‘High-Impact Domestic Financing: Evidence, Equity, Efficiency’, we heard fascinating insights from ministers and experts into how evidence of different types including disaggregated datadata is being used in parts of sub-Saharan Africa and South Asia to inform cost-effective, impactful policy which holds the potential to transform the chances of the most vulnerable students. In this commentary, we examine three key themes which emerged from their discussions.
In the run-up to the Global Education Summit 2021, Education Development Trust co-hosted a successful side event, ‘High-impact domestic financing: evidence, equity, efficiency’, in partnership with the British Council and the UK Foreign, Commonwealth and Development Office (FCDO), bringing together ministers and experts to consider the use of evidence to drive efficiency and equity in education policy. The 90-minute online seminar featured rich discussion with specialist insights from Tony McAleavy (Education Director, Education Development Trust), Alice Wekesa (Gender and Inclusion Specialist, British Council), Wendy Morton MP (Minister for the UK Foreign, Commonwealth and Development Office), Hon. David Sengeh (Minister of Education, Sierra Leone), Hon. Dr Ing Getahun Mekuria (Minister of Education, Ethiopia), Hon. Dr Muraad Raas (Minister of Education, Punjab), Hon. John Ntim Fordjour MP (Deputy Minister of Education, Ghana) and Dr Brajesh Panth (Chief of Education Sector, Asian Development Bank).
Amid the many insights and the productive discussions on the power of data to effect cost-effective change in school systems, several key themes emerged.
Central to evidence-informed policy is decision-makers’ understanding of the systems they are seeking to improve, and education management and information systems (EMIS) are key resources for governments around the world. Almost all countries have these systems – and a linked national system for student assessment – providing them with a potentially powerful tool for targeting resources, monitoring the success of interventions and tracking the experience and outcomes of particular groups of students – for example, vulnerable girls.
Sierra Leone is one country which is making particular use of such a system, with its Education Data Hub, which brings together data on learning outcomes with information on the features and facilities of over 11,000 schools. Such features include a school’s location (for example, remote or accessible, urban or rural), the number of teachers it employs, the level of training school staff have received, as well as whether schools have WASH facilities, toilets, electricity or internet access. This enables decision-makers to dig deep into the data and establish links between these factors and student outcomes, asking new questions which can inform targeted spending and resourcing. Such evidence can also be shared with agencies outside the Ministry of Education (MoE) to inform other programmes which may impact on children’s learning, such as adult literacy in the community, school feeding programmes and social welfare support. Similarly, in Punjab, Pakistan, the Ministry of Education has implemented a student information system to ensure that data on schools’ students, teachers, resources and facilities is collected and analysed to inform decisions on spending and other interventions to support students’ learning. In both cases, access to the right evidence makes effective, targeted resourcing decision possible.
Such system-level data is especially important where it can be combined with evidence of what works from robust research into school improvement. The ‘smart buys’ advocated by the Global Education Evidence Advisory Panel provide a good example of how evidence from research can be mobilised in a way that supports cost-effective education reform.
Moreover, the presence of granular data – at the level of individuals schools and students – makes it possible for policymakers and leaders at all levels of an education system to identify patterns and problems in specific localities and contexts, and to target decision-making accordingly. For example, in Ghana, female student attendance in many rural communities was very low, notably where a lack of sanitary provision meant that adolescent girls would have to miss school during their periods. The evidence of where this was a problem enabled targeted investment in such provision, increasing girls’ participation in education in these areas.
Meanwhile, in Punjab, 70% of children were found to be dropping out of education after Grade 5 (primary level) due to a lack of locally available schools at Grade 6 and above, and the MoE was able to use geotagging to identify areas of particular concern where there were no elementary schools available. This granular data was then used to inform a decision to open afternoon-session lower secondary schools in existing, accessible primary school buildings, which were only in use in the morning. This could enabled two million addition children to remain in education after Grade 5.
Notably, such data and interventions can ensure that basic problems – like attendance and availability of school buildings – can be addressed and thereby facilitate more of a focus on learning outcomes and ensuring that children are learning. This is a critical element of the global learning crisis which predated the Covid-19 pandemic, and will need particular attention as and after students around the world return to the classrooms. For example, once these issues are solved, it is more feasible for decision-makers to look at issues in student performance or attainment in specific contexts, which can provide insights about the specific elements of (for instance) teacher training which may be needed.
Qualitative data can also demonstrate particular needs in these circumstances. For example, the British Council’s recent study on the experiences of teachers and school leaders sought to understand the challenges faced by vulnerable learners and their teachers in the midst of Covid-19. This highlighted not only teachers’ concerns over child exploitation and adolescent marriage and/or pregnancy, but also the professional development needs that would need to be addressed for teachers to be equipped to respond to these challenges.
Finally, it is clear that technology – especially digital technology – is likely to have an important and growing role in the collection, analysis and deployment of evidence for effective education interventions. In Ethiopia, for example, the MoE is rolling out a digital ID for secondary students and making use of blockchain technology to analyse their performance, in order to drive further data-driven decision-making. Such tagged data at the level of individual students may be instrumental in identifying patterns in outcomes and how they relate to teaching and school leadership.
Technology can also be used to facilitate effective data collection. The Tusome programme, a literacy programme introduced by the MoE in Kenya, for example, uses low-cost tablets to collect data and teacher feedback to help close the learning gap and enable millions of children to develop their ability to read – for approximately $27 per pupil.
Technology can of course be deployed in response to problems when they have been identified. In Punjab, for instance, an app was created which enabled its 400,000 teachers to complete administrative activities (such as applications for transfers, pensions, leave, promotions, etc.) from their phones or laptops, without having to travel to offices at the expense of time or energy which should be spent in the classroom, which not only contributed to time-saving and reduced teacher absenteeism, but also enabled them to focus more fully on teaching and learning.