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Malawi Longitudinal Schools Survey: Creating Equal Opportunities for Malawi’s Children

Tue, April 16, 5:00 to 6:30pm, Hyatt Regency, Floor: Pacific Concourse (Level -1), Pacific G

Proposal

One of the poorest countries in sub-Saharan Africa, Malawi faces severe constraints in resources throughout its education system. Moreover, those resources which are available are inequitably distributed, creating widespread disparities in conditions, staffing and practices between schools. The Malawi Longitudinal Schools Survey is the first nationally representative longitudinal survey of schools in a developing country. The baseline survey reveals the extent of inequities in resources and conditions between schools, with schools in even sub-district areas varying widely in terms of infrastructure quality, staffing and availability of teaching and learning materials.

This paper presents findings from the baseline round of the MLSS survey, carried out in 2016. Baseline data collection was performed in 559 Government primary schools, 50 in urban areas and the remainder in rural areas, covering all 34 education districts in the country. The first-round sample analyzed here is representative of Malawi’s primary schools on a wider national scale across a range of key indicators, including school size and staffing level. The issues identified here are relevant for Malawi’s education system as a whole, as well as for other low-income countries in Africa that have encountered similar challenges of high repetition and dropout coupled with low learning in recent years.

Analytical Framework. The study follows a longitudinal design in 559 schools across Malawi, with surveys of school infrastructure and resources, teacher qualifications, and student demographic characteristics (including key equity dimensions such as socioeconomic status), as well as learning outcomes. The equity analysis examines geographic disparities in resource allocation across primary schools in Malawi, and examines the extent to which resource deprivation is predictive of learning outcomes. The baseline, carried out in 2016, demonstrates the extent to which schools in remote areas suffer extreme deprivation in terms of infrastructure quality, staffing and availability of teaching and learning materials. Schools in remote areas are not only less likely to have access to basic amenities such as electricity and water than schools close to trading centers; but also have significantly fewer teachers per student, lower quality infrastructure, and fewer classroom facilities and educational materials. These disparities reflect inequities in resources: while remote schools receive similar levels of government finance, they are much less likely to receive community contributions in cash or kind, and devote significant resources to construction of housing to attract teachers, rather than investing in essential teaching infrastructure. National education policies in Malawi are largely agnostic to this variation, and resources and inputs are insufficiently targeted to the neediest schools. These inequities in service provision exacerbate existing socioeconomic disparities, as the schools facing these challenges are those most likely to have large numbers of students from the poorest households and those without literate parents, factors which regression analysis suggests are significant impediments to learning. The schools which face the biggest challenge in teaching students are those which must tackle the task with the least resources.

What impact do these inequities have on learning? Employing multivariate regression analysis, we identify core disadvantages at the school, teacher, and student level, which we use to construct a disadvantage index to measure the coincidence of multiple areas of disadvantage at schools. These disadvantages are mostly associated with remote schools. We find that schools with multiple disadvantages – in terms of physical conditions, staffing, and the socioeconomic background of students – have substantially higher rates of dropout than those with fewer disadvantages, higher rates of repetition, and lower learning outcomes.

Contribution: As noted above, the baseline survey analysis is the first stage of the Malawi Longitudinal Schools Survey. The findings will inform policy makers in the country, and help address the resource disparities across geographic areas within Malawi. Further, this study offers a methodological contribution to the understanding of disparities at the subnational level, focusing on the mismatch between deprivation and need, on the one hand, and resource availability, on the other. Over time, with improvements to system-level data, this concept of compound disadvantages may form the basis of a system for more appropriate targeting of Malawi’s limited resources to schools.

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