The unfairness of our current exams system has been highlighted and exacerbated by Covid-19 pandemic. The GCSE and A’level results fiasco in 2020 led to anger and concern and the Government has announced that in 2021 grades will be awarded on the basis of teacher assessment, which has raised further concerns about grade inflation and a widening of the gap between disadvantaged students and those in better resourced settings. Sammy Wright, the Social Mobility Commissioner for Schools and Higher Education, put it succinctly in January 2021: “As such, qualifications for 2021 can never be an objective measure of performance in the way we are used to, no matter how much we might wish it.” https://www.gov.uk/government/news/2021-exams-a-bigger-disaster-than-last-year
This is a proposal to design a system for representing students’ overall grades and taking into account their personal circumstances and the circumstances of their school. This will enable managers, HE and FE admissions officers and others responsible for making decisions about students’ next steps, to make a fairer assessment of those students than simply their grades. This system could be extended to include students’ grades at other points where they change organisations, for example, at transition from primary to secondary or after GCSEs when they may be moving to a college or different school or applying for an apprenticeship or a job.
This is similar to the information that Oxford University collects to contextualise applicants A’level grades. (https://www.ox.ac.uk/admissions/undergraduate/applying-to-oxford/decisions/contextual-data#) While that is admirable, it is not a national system that is urgently needed.
The limitations of exams in assessing children have been well documented and it is clear that using the same test for all children does lead to inconsistencies and does not provide us with an objective measure of what each child can and could do. An alternative to exams is teacher assessments but there are significant issues around bias and moderation.
As an example, let us start with Matt who is one of five children living in a 3-bedroomed social housing flat. His dad has a disability and his mum works as a cleaner in a hospital. He goes to his local comprehensive which has 64.5% (The data used in these example are from real schools but the names of the schools are not included. The data is from the governments database for 2018/19 https://www.compare-school-performance.service.gov.uk/?_ga=2.157336634.1889990133.1613985343-514386259.1613985343) of children on Free School Meals (FSM). During the period between lockdowns when schools were open, he had to spend 18 days at home isolating because of contacts with positive cases. He shares a bedroom with his brother and they have an old laptop and one Chromebook for the whole family. They have basic internet connectivity and cannot afford to upgrade. Matt’s school offered three live lessons a day – maths, English and science – but he cannot always access these. He goes to school once a week to collect worksheets and resources. Matt is studying for three A-levels and is predicted AAB. In Matt’s school, the average A’level result is D.
Archie lives in a four-bedroomed privately owned house with his brother, mum and dad. Both his parents are in full time employment and have worked from home during lockdowns. He goes to a private school, with no children on FSMs. He did not have to isolate at home during the period between lockdowns. When schools were only open to key workers’ children and vulnerable children, he accessed live lessons for the whole of the school day. Archie is studying for four A-levels and is predicted A*A*AA. The average A-level result in Archie’s school is an A.
Imagine you are a university admissions officer or responsible for choosing apprenticeships for a law firm. How are you going to think about these children when the details you receive are simply Matt AAB and Archie A*A*AA?
And then there are many different possibilities in between – Sheila lives in a social housing and shares a bedroom with her brother. She has her own laptop and plenty of data. She attends a school with 47.1% of children on FSMs. She’s predicted AAB. The average A-level result at her school is a C.
Or Gilly, who lives at home with her sister and parents with space and technology. Her school is a grammar school and she had two periods of isolation at home during lockdown. She’s predicted ABB. Her school has 6.3% on FSM and the average A-level result is an A.
If we create a table that includes this information as a way of contextualising the outcomes of exams which rather than assuming a level playing field between all school and home situations, will enable those making decisions about these students’ futures to understand their achievements in context. So for our four example students, their data could be represented below:
Student Name Type of School % FSM Average A-level result Home environment (1 = very under resourced, 2= average, 3= well resourced) Exceptional circumstances Predicted results
Matt comprehensive 64.5% D 1 20% of school missed due to isolating AAB
Archie private 0% A 3 N/A A*A*AA
Sheila comprehensive 47.1% C 2 N/A AAB
Gilly grammar 6.%3 A 3 20% of school missed due to isolating ABB
The measure for the home environment and exceptional circumstances would have to be generated within a school and could easily be incorporated into, for example, a UCAS form. All the other data is existing data held by schools and the government This kind of representation could also be used for GCSE results and admissions to Sixth Form Colleges and Further Education as well as to the end of KS2 results when children leave primary schools.
The aim is not to produce an index – as that would involve reducing the complex data too much to enable significant judgements. However, by simply presenting that extra information alongside the bare details of the exam grades, admissions tutors and others making decisions can do this on the basis of information that is more deeply rooted in the student’s context.