Student intersectional sociodemographic and school variation in GCSE final grades in England following Covid-19 examination cancellations

In 2020, COVID-19 forced the cancellation of all student end-of-school examinations in England. Schools were asked to provide centre assessment grades (CAGs), offering their best estimates for what students would have achieved had they sat their examinations. Although initially replaced in favour of grades calculated via an algorithm, students were eventually awarded their CAGs following widespread public outcry over the calculated grades. Whether CAGs were unfairly awarded across different student groups and schools in 2020 compared to previous years is a key question. However, existing analyses of bias in CAGs are limited by a lack of attention to potential interactions between student characteristics, and thus to hidden differential grade inflation across intersectional groups. We addressed this by examining student GCSE performance in 2018, 2019, and 2020 via a Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) analysis of intersectional sociodemographic variation which we cross-classified with schools given their role in generating CAGs. Overall, a picture of stability emerged, where despite substantial overall grade inflation in 2020, the use of CAGs did not appear to have generated new or divergent intersectional relationships in comparison to previous years, suggesting CAGs showed a similar susceptibility to bias as normal examinations.

Authors

Institutions

Publication Details

Journal
Oxford Review of Education
Published
2024-10-02
DOI
https://doi.org/10.1080/03054985.2024.2407624
Citations
3
Primary Topic
Racial and Ethnic Identity Research
Type
article
Field-Weighted Citation Impact
3.40

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Student intersectional sociodemographic and school variation in GCSE final grades in England following Covid-19 examination cancellations

George Leckie, Lucy Prior
3 citations
Oxford Review of Education
Racial and Ethnic Identity Research
3.40
article

Student intersectional sociodemographic and school variation in GCSE final grades in England following Covid-19 examination cancellations

George Leckie, Lucy Prior
article en
3 citations

Abstract

In 2020, COVID-19 forced the cancellation of all student end-of-school examinations in England. Schools were asked to provide centre assessment grades (CAGs), offering their best estimates for what students would have achieved had they sat their examinations. Although initially replaced in favour of grades calculated via an algorithm, students were eventually awarded their CAGs following widespread public outcry over the calculated grades. Whether CAGs were unfairly awarded across different student groups and schools in 2020 compared to previous years is a key question. However, existing analyses of bias in CAGs are limited by a lack of attention to potential interactions between student characteristics, and thus to hidden differential grade inflation across intersectional groups. We addressed this by examining student GCSE performance in 2018, 2019, and 2020 via a Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) analysis of intersectional sociodemographic variation which we cross-classified with schools given their role in generating CAGs. Overall, a picture of stability emerged, where despite substantial overall grade inflation in 2020, the use of CAGs did not appear to have generated new or divergent intersectional relationships in comparison to previous years, suggesting CAGs showed a similar susceptibility to bias as normal examinations.

Oxford Review of EducationVol. 51(5)
University of Bristol (GB)
Economic and Social Research Council
Openalex Percentile: Top 7%
Racial and Ethnic Identity Research
3.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.