Equity targeting: Raising learning profiles for those at the bottom of the pyramid

Sustainable Development Goal 4 commits countries to ensuring “inclusive and equitable quality education.” A growing body of evidence suggests that the goals of equity and quality of education are interlinked – that countries can raise learning outcomes most effectively by addressing issues of equity. To achieve rapid improvements in learning in countries which are lagging behind, it is necessary to “raise the floor” by targeting investment and reform to the lowest performers. We propose a panel presenting evidence from a range of countries on how policies can effectively target the lowest-performing students, achieving rapid improvements in overall learning levels.

Despite large-scale investment in expanding access to education in the last two decades, levels of learning in low- and middle-income countries remain far below those of the OECD. The median level of achievement in many developing countries equates to approximately the 5th percentile of the distribution in OECD countries; a level at which OECD pupils may be expected to receive remedial intervention. This “learning crisis”, where the expansion of schooling is not accompanied by a concomitant expansion of learning, poses a significant barrier to low- and middle-income countries as they strive to harness potential human capital.

A large and expanding set of national and cross-country data demonstrates that inequities in learning between students in low- and middle-income countries not only dwarf, but are key drivers of, inequities between countries. Across the world, countries with higher performance in learning assessments tend to be those with the lowest levels of educational inequality. Analysis of the Programmed for International Student Assessment (PISA) 2015 assessments, conducted in more than 50 countries, show that countries move from low- to middle-tier performance primarily by moving the lowest-performing students towards the middle of the distribution, rather than by raising students in the middle of the distribution towards the top. In other words, raising the performance of the lowest-performing countries is unlikely to be achieved without raising the performance of the lowest-performing individual students. For example, analysis of data from the Young Lives survey suggests that raising girls’ learning outcomes to the average for boys in India could be expected to reduce the performance gap between India and Vietnam by around 20 percent; and raising rural pupils to the level of urban pupils in India would reduce the gap by around 50 percent.

Addressing inequity in learning requires attention to inequities in resources. This entails directing resources – talent, materials, financing – to where the needs are greatest. The Incheon Declaration calls for governments to “allocate resources more equitably across socio-economically advantaged and disadvantaged schools,” and SDG 4 contains an indicator for the “extent to which explicit formula-based policies allocate resources towards disadvantaged populations.” However, in a great many countries, educational investment is at best targeted with a superficially ‘fair’ but inequitable, “one size fits all” approach that ignores existing disparities; or is actively targeted at less needy populations. For example, although students in remote schools in sub-Saharan Africa consistently underperform those in schools closer to urban centers, teachers in the region are typically end up in schools with lesser needs, exacerbating large disparities in staffing.

At the same time, addressing learning inequity requires looking beyond school conditions to students themselves, their backgrounds and characteristics. Analysis of data from the Southern and Eastern Africa Consortium for Monitoring Educational Quality (SACMEQ) III assessments suggests that student household wealth is a key driver of student learning performance. Evidence from the Malawi Longitudinal Schools Survey (MLSS) suggests that parental literacy, home language, and student mindsets have powerful impacts on learning outcomes, even when controlling for school and teacher factors.

Compounding inequities, school-level and student-level disadvantages tend to coincide. Disadvantaged districts and remote areas, which often have students facing the most severe personal barriers to learning, frequently have the least-resourced and lowest-performing schools even in terms of educational value added. In India, for example, students whose mothers have higher education achieve higher learning outcomes than other students; in addition, these students attend schools which improve students’ test scores by up to 0.2 standard deviations more than those attended by students whose mothers have not attended school. Evidence from Malawi suggests that this compounding of disadvantages in terms of school learning environments, staffing, and student populations, acts as a serious barrier to learning: students in schools with three or four such disadvantages achieved scores in the MLSS learning assessments eight percent lower than those in schools with no student disadvantages.

However, targeted attention to the neediest students can achieve rapid reductions in disparities. Following dismal learning performance in the 2014 Service Delivery Indicators (SDI), Tanzania achieved large improvements in learning in the 2016 SDI assessment. This overall improvement in national performance was driven by rapid rises in scores by the previously lowest-performing districts, reflecting targeted support to teacher knowledge and effort in these districts by donor programs.