ADR UK Research Fellows: Grading and Admissions Data for England

Status: Active

The fellows will use key data about predicted and achieved grades, as well as centre assessment grades and calculated grades in 2020 (when assessment practices were changed as a result of the Covid-19 pandemic).  

Research using this de-identified data has the potential to generate better understanding of the impact of these assessment policies on students and schools. 

Read more about the fellows and their projects below.

Dr Konstantina Maragkou

Quantifying pandemic-driven educational assessment modifications: grade predictions, student and school characteristics, and university outcomes

Dr Konstantina Maragkou is a postdoctoral researcher at the University of Cambridge. Her research focuses on the economics of education. Her project will test for the existence of a pandemic-driven modification in A-level assessment and investigate its potential effect on higher education application outcomes from a fairness and equity perspective.

View project details

The project aims to explore the following research questions: 

  • What is the relationship between predicted grades and awarded grades, and how does it vary with individual-, subject- and school-level characteristics?
  • How much did the assessment change within schools as a result of the pandemic, and how does any identified assessment modification vary by school-level characteristics?
  • What is the effect of any modification in assessment on higher education application outcomes? Are external assessments important for student outcomes?

The methodology used in this study:

The research will take place over three phases, using different methods at each stage.

  • For the first phase of the project, a multivariate regression model will be estimated for each cohort. This will show the relationship between UCAS (Universities and Colleges Admissions Service) predicted grades and awarded grades and how individual, subject and school characteristics shape this relationship.
  • The second phase will test for the existence of a pandemic-driven modification in assessment within subjects and schools by considering potential changes in the gap between predicted and awarded grades between the pre-2020 and the 2020 cohorts.
  • The third phase aims to use the quantitative measure of assessment modification to estimate its effect on higher education application outcomes using a difference-in-differences framework coupled with statistical matching techniques.  

Publications

Duration: September 2022 – August 2023

Funding: £107,456

The GRADE fellowship is a partnership between Ofqual, the Department for EducationUCAS and ADR UK.

Dr Oliver Cassagneau-Francis

Exploring the gaps in teacher judgements and the implications for university admissions

Oliver Cassagneau-Francis is a Research Fellow at the Centre for Education Policy and Equalising Opportunities at UCL. He is examining the extent of discrepancies in teacher judgements (measured by comparing predicted and awarded grades) in the English education system and the implications for student outcomes.

View project details

This project aims to explore the following research questions:

  1. Are there systematic differences in how teachers predict the grades of different groups of students, for example by socio-economic status, ethnicity or gender? 
  2. Do differences in teacher predictions across different groups of students differ by the subject of A-level qualification? 
  3. Do teacher-predicted grades and centre-assessed grades (CAGs) affect the university course students ultimately enrolled in?

The methodology used in this study:

  • This study will use a mostly descriptive approach to address research questions 1 and 2, estimating the distributions of predicted and achieved grades for the whole population and conditional on being in certain groups (e.g., by ethnicity, gender and socio-economic status). The project will compare these predicted and achieved grade distributions within and across groups and will also compare actual grades (2018 and 2019) with CAGs (2020) within groups. 
  • These descriptive analyses will provide an overview of any discrepancies across groups in teacher predictions. However, if the underlying distributions of “true” grades are very different across groups, this exercise might be less insightful. To mitigate against this, a regression discontinuity design will be used focusing only on students who were ranked very close to grade boundaries by their teachers in 2020. Comparing the characteristics of the students (e.g., their ethnicity, gender, socio-economic status) who were just awarded a higher grade, to those who just missed out will provide insights on whether certain groups are systematically over- or underpredicted. The same approach will also be used to compare the outcomes of students who look similar across a range of characteristics (including being similarly ranked) but who were awarded different grades.

Funded value: £176,314 (full economic cost)

Duration: 15 August 2023 – 15 December 2024

Publications


About the data

The data shared through the GRADE initiative includes three main sources of de-identified, linked administrative data:

  • The Office of Qualifications and Examinations Regulation (Ofqual) – including data on GCSE and A level examinations and qualifications collected from awarding organisations
  • Department for Education – including extracts of the National Pupil Database for GCSE and A level students
  • UCAS – including data from the university application process.

For more information about the data, access the Grading and Admissions Data for England (GRADE) framework.

The dataset is accessible to accredited researchers via the Office for National Statistics Secure Research Service.

Categories: ADR UK Research Fellows, ADR England, Office for National Statistics, Children & young people

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