SISTEMA UNITARIO DE COMPENSACIÓN REGIONAL DE PAGOS SUCRE

There is a reasonably strong and broad consensus as to what constitutes STEM-related skills and knowledge at least in terms of the specific academic disciplines that fall within the scope of science, technology, engineering and mathematics.

Under this approach holding particular qualifications is generally used as a proxy for ‘skills’. This is imperfect as people may have developed STEM competencies outside their study for qualifications. However, this proxy is typically used in the STEM literature and terms like ‘STEM skills’ and ‘STEM subjects/qualifications’ tend to be used interchangeably. In practical terms, subject classifications, particularly those developed for the higher education sector, allow STEM disciplines to be categorised in a discrete and understandable way. This is demonstrated by Table 4 which shows the clear split between STEM and non-STEM subjects. A number of leading reports use this subject classification to identify STEM graduates, including BIS in its report on the demand for STEM skills and CIHE in its report on STEM demand.

Table 4: Higher education subject areas by STEM status

Subject group Categorisation

(1) Medicine & dentistry STEM

(2) Subjects allied to medicine STEM

(3) Biological sciences STEM

(4) Veterinary science STEM

(5) Agriculture & related subjects STEM

(6) Physical sciences STEM

(7) Mathematical sciences STEM

(8) Computer science STEM

(9) Engineering & technology STEM

(A) Architecture, building & planning Non-STEM

(B) Social studies Non-STEM

(C) Law Non-STEM

(D) Business & administrative studies Non-STEM

(E) Mass communications & documentation Non-STEM

(F) Languages Non-STEM

(G) Historical & philosophical studies Non-STEM

(H) Creative arts & design Non-STEM

(I) Education Non-STEM

Source: Higher Education Statistics Agency

This makes the task of assessing the supply of people from higher education holding STEM qualifications a relatively straightforward task (see section 2.5 above).

A more painstaking approach has been required to identify STEM qualifications delivered through the further education and skills system. A series of FE and Skills STEM Data

reports have been produced, which analyse the Learning Aims Database, the Individual Learner Record and other Further Education. The most recent report (Harrison, 2012) identified 15,000 STEM qualifications, which accounted for 25 per cent of all funded qualification achievements through the FE and skills system in the 2010/11 academic year. To be classified as STEM within this approach, qualifications are required to have learning outcomes that are deeply rooted in science, mathematics or engineering and/or are of a ‘technical’ or ‘technology-application/use’ nature. They may also be classified as STEM if the qualification is judged to provide a degree of learning that will aid progression in S, T, E or M.

However, for the purposes of this review we are primarily interested in demand for STEM skills and the particular types of STEM skill which demonstrate the greatest need. In order to assess the demand for STEM skills in the labour market the typical approach that is adopted is to seek to identify those occupations and industry sectors that have a significant requirement for STEM skills. It is then possible to apply indicators of demand relating to employment, vacancies and pay.

Approaches vary with regard to the methods used to identify STEM-intensive occupations and industries; ranging from the application of expert knowledge and judgment in selecting relevant occupational and sectoral categories, through to the use of harder empirical methods. The approaches used by a selection of leading studies are considered below. However, as Bosworth notes “the issue of precisely where to draw the line between STEM and non-STEM never goes away” and is perhaps not fully resolvable.

In his assessment of Technician employment in the UK economy Mason (2011) identified SET (science, engineering, technology) occupations as those in which the application of scientific, engineering and/or technological skills and knowledge is central to the job- holder’s work. The process of identification involved the application of judgment to the list of occupational categories contained with the Standard Occupational Classification. This judgment-based approach is perhaps the most common and is also used in BIS (2009) to identify scientific occupations and by the Institute for Employment Research as the basis for its projections of demand for STEM graduates (CIHE, 2009).

In order to assess supply and demand for high level STEM skills Bosworth (2013) uses empirical methods to identify occupations and sectors that have an intensive requirement for individuals holding qualifications at degree level and above in STEM subjects. The definition of STEM subjects is a standard one reflecting the discussion above. Occupations and sectors are considered to fall within the STEM category if they reach particular thresholds in terms of both the density of graduates employed (STEM graduates as a proportion of total employment) and the proportion of the total number of the corresponding STEM group employed within the economy.

A number of the leading studies differentiate between different types of STEM skill and occupation, according to the purpose and scope of the study. For example, Bosworth separates out occupations in the medical sphere from what he terms “core” STEM occupations. Mason excludes occupations that are mathematics-based (such as actuaries and statisticians) rather than science, technology or engineering based from his review of technicians.

3.2.1 STEM occupations

The concept of an occupation is a key mechanism for understanding the demand for skills in the workplace, particularly when thinking about apprenticeships. It encapsulates the key dimensions of skill level and skill content (specialisation) with reference to the skills required to do a job (ONS, 2010).

It has been argued that a defined occupation should be the foundation for all apprenticeships to ensure that there is a link to occupational competency and it has been further argued that recent developments in policy and practice have eroded this link (Gatsby Foundation, 2013).

It is because occupation is the pre-eminent indicator of a job’s skills level / content and because it is linked at a conceptual level to apprenticeships that we have used it as the organising framework for our assessment of labour market need.