Introduction

On 20 March 2020, English schools closed indefinitely. This closure lasted five months, only to fully reopen before the next academic year in September 2020. Between May and July, students were commonly expected to sit a series of standardised assessments in primary, secondary, further and higher education institutions. However due to the forced closure of schools, few examinations were taken within schools. Instead, individual grades were estimated through an ‘algorithm’, a standardised method of assessment prediction based upon a series of metrics that will be discussed later. Centre-assessed grades (teacher predicted grades from this point onwards) was the only recognised alternative to the standardisation algorithm within government, a system that would allow for teachers to predict student outcomes as the formal basis from which final outcomes are drawn. The initial announcement of the algorithm's estimations came on 13 August 2020, the day of the A-level results in England. The results produced widespread inaccuracies, whereby 39 per cent of pupils’ grades were ‘downgraded’ compared to teachers’ predictions and previous examination results (Adams, Weale and Barr, 2020). Due to the high-stakes nature of A-levels and the increasing economic and professional importance intricately linked with career opportunities, many students were bemused, and others devastated, at their individual final grades. This individual disappointment collectivised in national protests that attracted significant media attention during the COVID-19 lockdown (Adams and Stewart, 2020; Gant, 2020).

What these protests highlighted was the systemic inequalities in the distribution of attainment levels (Craven, 2020). For example, pupils attending private schools saw the largest attainment ‘inflation’ in the highest academic accolades, A/A*, when compared with previous years of average institution attainment (OFQUAL, 2020a). Pupils from lower-income, disadvantaged backgrounds suffered the most significant systematic downgrading of results by socioeconomic status (Duncan et al, 2020). Moreover, there were many concerns that the algorithm would also exacerbate existing racialised inequalities in attainment. An Equality and Human Rights Commission report vocalised these concerns, stating that the Office of Qualifications and Examinations Regulation's (OFQUAL) algorithm ‘could have a lasting effect on young people from certain ethnic minority backgrounds and disabled pupils and those with special educational needs, who are already disproportionately disadvantaged’ if not administered correctly (Wilthew, 2020: 4).