Urgent Action Needed to Improve Maths and Statistical Skills
A new analysis of OECD survey data by researchers at Cambridge and the Institute of Education suggests that as many as 40% of adults in England and Northern Ireland are unable to calculate simple proportions and more than half are unable to interpret a basic line graph. Average rankings on basic mathematical tasks of this kind place England and Northern Ireland in the bottom third of the 30 countries who participated in the survey.
These findings reinforce accumulating evidence of Britain’s relative weakness in mathematics and statistics-related skills. These deficiencies are alarming given that such skills are essential or important for a large majority of jobs in the UK economy.
In a 2015 NIESR report drawing on Skills and Employment Survey data, we estimated that:
- Roughly three out of ten jobs require at least basic arithmetical skills (such as adding, subtracting, multiplying or dividing numbers or using decimals, percentages or fractions).
- In addition, another four out of ten jobs require the ability to apply quantitative skills at a more advanced level than basic arithmetic, ranging from use of descriptive statistics to highly complex mathematical procedures.
Only about 5-6% of all people in employment are classified to occupations which intrinsically rely on high levels of maths- or statistics-related skills: professional engineers, scientists and IT specialists; actuaries, economists and statisticians; and chartered and certified accountants. However, people holding university degrees or professional qualifications in ‘numerate subjects’ are sought after across the economy, not just in jobs specifically related to their qualifications. Thus it is common for employers to report shortages of people with STEM (science, technology, engineering and maths) skills.
But at least equal attention needs to be paid to maths skill deficiencies in many other occupations and activities in which accuracy in measurement and data analysis is vital to organisational performance and sometimes critical for public health and safety.
Examples cited by the Advisory Committee on Mathematics Education include hospital staff calculating dosages of medications and patients’ nutritional requirements; production operators’ using statistical process control methods of data collection and analysis; financial services staff advising customers on mortgages and making underwriting decisions; chemicals laboratory technicians preparing solutions to specified concentrations; railways staff responsible for monitoring track quality; managers in many industries making cases for capital investments; and civil servants responsible for reviewing evidence on the effects of government policies.
Intensive case study research reviewed in a 2013 Sutton Trust report has shown that in jobs of this kind, even if employees have ostensibly gained the required level of maths skills by passing GCSE exams in maths at Grade C or above, many of them subsequently have difficulty in applying basic mathematical skills in the ‘complex settings’ of workplaces and lack the ability to recognise obvious errors in their work – with severe negative consequences for the performance of organisations which they work for.
One fundamental problem is that, for several decades, the great majority of school pupils in England, Wales and Northern Ireland have been allowed to stop studying maths at the age of 16. Thus, even if they do gain good or adequate maths qualifications at that age, many of them have effectively forgotten most of the maths that they once knew by the time they enter the labour market or go to university.
Most other industrial nations do not encourage a majority of upper secondary students to stop studying maths or statistics at the age of 16 and the foolishness of allowing this to occur in most parts of the UK has been widely recognised for many years. Had decisive action been taken decades ago, when the issues were already well understood, the UK’s workforce would now be populated by much larger numbers of people with the maths and statistical skills needed to carry out their jobs. But this issue has been fudged or openly shirked by one government after another in the last 40 years.
Only a minority of post-16 students can be expected to study pure mathematics to a high level. However, as recent reports by the British Academy and the Smith Review of Post-16 Mathematics make clear, there is every reason to provide a wide range of courses that will help large numbers of post-16 students to retain and improve the maths and statistical skills that are so badly needed in workplaces and in higher education studies.
To date progress in this area has been hesitant and piecemeal in nature, with the Department for Education recently offering new incentives to schools and colleges in England to try and increase the currently low student numbers on post-GCSE maths courses while concerns continue about low pass rates in GCSE maths re-sits .
One serious impediment to concerted action in post-16 maths education is the shortage of qualified maths teachers, in large part due to so few people studying maths beyond the age of 16 in the past.
Recent analysis by Education Datalab for the Gatsby Foundation suggests that even modest increases in the salaries of maths teachers could help to increase their retention in schools and alleviate shortages. However, a policy approach relying solely on salary increases for maths teachers could take years to bear fruit and could be offset to some extent by continuing competition for numerate graduates from employers in other sectors. Hence more urgent action is needed to expand post-16 maths education.
For example, teaching economies of scale could be achieved by concentrating the bulk of maths and statistics teaching for post-16 students in selected teaching centres in different parts of the country. Experimentation will be needed to identify the best ways to staff such centres (including offering competitive salaries) and coordinate their efforts with other educational institutions in each region. Therefore, this initiative should start with pilot centres but, if proven successful, they should be extended nation-wide.
Class sizes in these specialist maths teaching centres will inevitably be too big for classroom teaching to be sufficient so the centres will also need to offer carefully-designed self-learning materials, making use of innovative technologies. This approach should be combined with on-line support from personal tutors for all students and preferably include some opportunities for face-to-face assistance in small tutorial groups as well.
At the same time these specialist centres should also deliver part-time maths and statistics courses for people who are already in employment. Such courses should not just aim to increase the numbers of adults gaining formal qualifications in mathematics but also to improve employees’ ability to apply maths and statistical skills when needed in the course of their jobs.
These part-time courses should be coordinated with current apprenticeship training but extend well beyond it. Given how loudly many employers complain about apparent shortages in maths and statistical skills, this should surely be one area of training that they will willingly help pay for in combination with public spending.
Geoff Mason is Visiting Professor at the Centre for Research on Learning and Life Chances (LLAKES), UCL Institute of Education. A Fellow at NIESR, he was formerly Senior and Principal Research Fellow at NIESR for many years.