Organised Sessions

Tuesday 16th April 09:00-11:00


Economics pedagogy research – getting started

Session Chair: Alvin Birdi, University of Bristol and Economics Network

This session focuses on research into economics education, specifically within higher education, that will be divided into two halves. The first will introduce insights from our latest critical review of research in economics pedagogy published over the years 2022 and 2023. However, we will also draw insights and comparisons from work published in earlier years. The aim is to identify key trends that are emerging across economics teaching, learning and assessment, in the light of the Covid pandemic and the rapid expansion of tools such as Chat GPT, as well as around themes such as diversity and inclusion. We will also present ideas on teaching innovation that emerge from the critical review that educators can introduce into their classrooms and assessments. The second half of the session will have a more practical focus and discuss how colleagues can use these insights, whether in their own teaching, to inform an application for an Advance HE fellowship (or similar scheme) or to get started in pedagogical research themselves.

Speakers

Steven Proud, University of Bristol
Ashley Lait, University of Bristol


Women, Work and Retirement

Session Chair: Lori Curtis, University of Waterloo

This session will present three papers examining aspects of women’s experiences in the labour market in different stages and countries. 

Speakers

Kate Rybczynski, University of Waterloo 
Pomme Theunissen, Maastricht University
Lori Curtis, University of Waterloo


Monetary Policy: A Broad Perspective

Session Chair: Alexander Haas, University of Oxford

Three to four papers on monetary policy and its interaction with a broad range of topics including debt and fiscal consolidations, inequality, and financial stability.

Speakers

Xiaoshan Chen, Durham University
Oliver de Groot, University of Liverpool
Alexander Haas, University of Oxford


Teacher assessment, teacher prediction and mismatch

Session Chair: Lindsey Macmillan, UCL Centre for Education Policy and Equalising Opportunities

Paper 1

Exploring SES, gender, and ethnicity gaps in teacher judgements. 

We exploit the 2020 exam cancellation to explore discrepancies across student groups in teacher judgement. In 2020, students were unable to sit exams and most schools were closed, so in-class tests were also not possible. Instead, teachers were asked to provide students with the grade they could have attained had they sat the exam. These were known as CAGs. As part of the CAG process, teachers were asked to rank each student within each grade level. To assess the extent to which there are discrepancies in teacher judgements by pupil characteristics, we exploit these rankings, focusing on those individuals who were just “awarded” or just missed out on a given grade. We use a regression discontinuity design (RDD) to test for imbalances in the proportions of students from different groups around grade thresholds. We will present evidence on the existence (or otherwise) of teacher discrimination by a range of characteristics including gender, ethnicity, and socio-economic status (SES). 

Authors 

Oliver Cassagneau-Francis –UCL Centre for Education Policy and Equalising Opportunities
Lindsey Macmillan – UCL Centre for Education Policy and Equalising Opportunities
Richard Murphy – Department of Economics, University of Texas at Austin
Gill Wyness – UCL Centre for Education Policy and Equalising Opportunities


Paper 2 

Ethnic gaps in attainment in teacher assigned grades. 

We explore the contribution of stereotyping to attainment gaps between pupils from different ethnic groups when grades are assigned by teachers. We exploit a change in assessment methods to compare grades based on teacher predictions to grades received through blindly marked examinations. When grades are assigned by pupils’ teachers, ethnic minorities receive higher grades in Maths and lower grades in English than White British pupils compared to when grades are assigned through blindly and externally marked examinations. These effects do not disappear when differences between groups and cohorts are accounted for, with group-specific stereotyping remaining a convincing explanation of the results.

Authors 

Hester Burn –Institute of Social and Economic Research, University of Essex
Birgitta Rabe –Institute of Social and Economic Research, University of Essex
Laura Fumagalli –Institute of Social and Economic Research, University of Essex


Paper 3   

What do kids learn from exams? 

How grades are assigned to students are a fundamental part of schooling systems. These serve to ration scarce educational resource, provide a range of information to schools, and may promote learning. At the same time, they provide information to students about academic progress and ability. In practice, there is a large variety in how grades are assigned. A key variation is teacher assessment or exam-based grading. This paper uses a setting, Norway, where both are used, but exam grading is randomly assigned to students. Using register data, we demonstrate systematic differences in grade assignment by teachers across different student groups. In the narrowest comparison, these remain even holding school stringency of marking and the prior attainment of students constant. We subsequently focus on mathematics performance. We demonstrate that randomly being assigned to a math exam, and through this receiving a worse exam grade, is consequential in terms of later educational decisions. 

Authors 

Colin Green –Department of Economics, Norwegian University of Science and Technology
Jon Marius Vaag Iversen – NTNU Social Research, Centre for Economic Research 
Lindsey Macmillan –UCL Centre for Education Policy and Equalising Opportunities
Richard Murphy –Department of Economics, University of Texas at Austin
Gill Wyness – UCL Centre for Education Policy and Equalising Opportunities


Paper 4   

Mismatch in higher education: school type, applications, and teacher predictions.

A growing body of research has examined the match between student ability and degree quality, revealing that mismatch is widespread, and that disadvantaged students are more likely to undermatch, enrolling in lower quality courses than expected given their achievement. In this paper we examine a major shock in the UK education system due to the Covid-19 pandemic, in which all national exams were cancelled and instead, students were given teacher predicted grades. This resulted in widespread grade inflation, increasing the number of students eligible for top courses, and forcing many courses to expand. We observe very large gaps in match between those from state and independent schools, though there is no evidence that these gaps widened as a result of the pandemic. This is likely because students had already applied to courses before the grade inflation occurred so had limited ability to capitalize on it. We utilize new data on applications and teacher predicted grades to explore why pupils from independent schools are more likely to overmatch among low attainers. 

Authors Jo Blanden – Department of Economics, University of Surrey 
Oliver Cassagneau-Francis – UCL Centre for Education Policy and Equalising Opportunities
Lindsey Macmillan – UCL Centre for Education Policy and Equalising Opportunities
Gill Wyness – UCL Centre for Education Policy and Equalising Opportunities








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