Metrics of equity in education

• In Event: Measurement of Equity in Education: A Handbook

Proposal

This presentation, based on chapter 3 of the Equity Handbook, guides researchers and practitioners through a standard process in the identification of relevant equity considerations, as well as the provision of basic technical and operational framing for the most common metrics of equity in education. The audience will be guided through various visualization and measurement techniques representing equality of condition (univariate measures of inequality) and impartiality (bi- and multi-variate measures of inequality).

The presentation begins with a visual representation of inequality, followed by the technical details behind measuring inequality under different conditions, along with examples drawn from country- and program-level data for each of the highlighted approaches. For each case, the discussion will detail the underlying data requirements, the appropriateness and applicability of each measure, as well as insights into the advantages and disadvantages of each.

The presentation will then outline four overarching families of measurements, including differences (gaps), ratios, dispersion, and cumulative information. Under each family of measurements, the presentation will showcase popular measures, such as the range, parity indices, the standard deviation, and the Gini coefficient, among others. The subsequent portion of the presentation discusses these measures in the context of aggregated data, or more generally, bivariate associations between educational outcomes and sociodemographic subpopulation groupings. This approach aims at quantifying inequality between different subgroups of the population to ascertain the degree of impartiality within a given context.

The overarching objective is to present a set of technical approaches that are available for education researchers and analysists of education statistics to improve understanding of the nature and magnitude of inequities in national education systems.

Authors

• Wael Moussa, FHI 360

• Carina Omoeva, FHI 360