Skip to content

Blog post

Measuring inequalities in student learning and how to close the gap

Sanghamitra Bandyopadhyay, Professor of Development Economics at Queen Mary University of London

Equity in learning is a core goal of all teaching institutions (OECD, 2018). For universities, most assessments of inequalities in student performance are undertaken ex post, once the examination results have been published, and so too late to impact upon the students’ achievements for that year. Measuring inequalities in student learning ex ante, while instruction is in progress, however, is difficult. In this blog post we will discuss how we can measure inequalities in student learning ex ante and present an example of how we may address such inequalities in learning with no prior knowledge of learning inequalities of the cohort.

Ideally, university teachers need to have a portrait of inequalities in student achievement of their current cohort before they start teaching. There are some difficulties presented with this objective. First, what do we mean by student equity? Do we mean that all students have equal opportunities to enable them to obtain higher grades; or do we simply mean that they develop greater learning abilities (Jencks, 1988)? Second, if we focus simply on learning outcomes (that is, measured via student performance), how do we measure inequalities in their potential performance before instruction takes place?

‘If we focus simply on learning outcomes (measured via student performance), how do we measure inequalities in their potential performance before instruction takes place?’

This difficulty also lies at the core of understanding how to measure inequality for other known measurable entities, such as income and wealth (Sen, 1980). The problem of not having data about inequalities in student learning at the onset of teaching is similar to that of a statistician having incomplete data or even no data. For the lecturer standing at the podium, the audience are just an unsorted sample of students, without any prior knowledge of their specific learning abilities.

There are some solutions to the problem of incomplete data (Little & Rubin, 2019). There are simple methods by which we can combine several sources of data – for example, of the same class but different module, and of the same module but earlier years – to obtain a credible picture of extant inequalities in performance to proxy for inequalities in learning for a given cohort.

But how can the lecturer reach these students in the lecture theatre? Indeed, the lecturer in the lecture theatre has a precious opportunity to enhance student learning outcomes equitably. Lecturers do often exercise their significant individual powers like rock stars. Joseph Schumpeter who was known by his students for his oratory skills, was also infamous for pursuing Harvard University library staff to ensure provision of adequate (and often obscure) texts for his students. Amartya Sen’s packed lectures on the economics of poverty at the London School of Economics are known to have broken health and safety rules with students thronging the windowsills and stairways.

An example at hand relates to innovations that were implemented by universities to ensure high-quality teaching delivery during the peak of the Covid-19 pandemic. As part of our hybrid teaching model, the School of Business and Management at Queen Mary University of London proposed that we deliver a live lecture Q&A session to support the online lectures and seminars, which I implemented for an undergraduate macroeconomics module. While it initially appeared to serve as a forum for students with queries about the lecture material, as the weeks progressed a new synergy emerged that was not predicted by any of us. Students would voluntarily show up with different needs – some students were vulnerable; others were there for topics well beyond the purview of the module. Students of all abilities voluntarily attended this lecture session due to the anonymity offered by the large lecture theatre and the flexibility of the session’s intended goal. Opening up the floor to students in the lecture theatre via a Q&A session worked as a credible tool to address unknown inequalities in learning in the class cohort.

However we choose to define educational equity – whether as the provision of equal opportunities for learning or equity in student performance – with some creative structuring of our teaching we can reach all our students successfully in the lecture theatre and address inequalities in student learning and performance. With both ex ante knowledge of vulnerable students and using innovations in teaching delivery, universities should be able to successfully address inequalities in student learning.


I thank the teaching and learning team at the School of Business and Management at Queen Mary University of London, Patrick McGurk, Aktar Hussain and Mike Noon who inspired and supported the teaching innovation discussed in this blog, and the editor of BERA Blog, Rowena Passy, for useful comments.


Jencks, C. (1988). Whom must we treat equally for educational opportunity to be equal? Ethics, 98(3), 518–533. 

Little, R. & Rubin, D. (2019). Statistical analysis with missing data (3rd edition). Wiley.

Organisation for Economic Co-operation and Development [OECD]. (2018). Equity in education: Breaking down barriers to social mobility.

Sen, A. (1980). Equality of what? Tanner lectures on human values (pp. 197–220). Cambridge University Press.