Examining the Employability of Maths Graduates: Triangulation between Employer, Alumni and Student perceptions

1. School of Mathematics FACULTY OF MATHEMATICS AND PHYSICAL SCIENCES Examining the Employability of Maths Graduates: Triangulation between Employer, Alumni and Student perceptions Dr Samantha Pugh* and Dr Margit Messmer Faculty of Mathematics and Physical Sciences

2. Outline • Overview of the project • Methodology • Surveys • Analysis of the data • Findings and interpretation • Impact on Teaching – the story so far… • Further new developments

3. Overview of the Project Engaging with Employers to Enhance the Employability of Mathematics Graduates Project Aims • Work with a number of key employers and other stakeholders across a range of relevant sectors to ascertain what skills and attributes are required in Mathematics graduates, and • Form strategic partnerships with key employers to develop a range of learning activities that give students experience of “real world” examples that can be embedded into our programmes.

4. Methodology • Research into current view of generic and STEM graduate attributes • Investigation of Maths graduate specific skills • Base survey on published lists of “employability skills” from various sources • Adopt approach from HEA Physical Sciences Subject centre: Skills deficits (Hanson and Overton) • Align findings from different groups • Action research to inform curriculum development

5. The Surveys - participants • Current Students: • Cross-sectional – 41 • Students with a Year in Industry - 6 • Alumni: Longitudinal - 19 • Employers: “warm” contacts - 19

6. The Surveys - Employers • Nature of the organisation • Skills of graduate recruits in Mathematics • Already have • Lacking • Unable to comment • What skills and attributes does your organisation require? • Essential • Desirable • Will provide training • Not important • Preparedness of graduate recruits

7. The Surveys – Students • Students on or returning from Year in Industry • Skills developed in Mathematics programmes • In the core programme • Co-curricular activities • During my placement • No opportunity to develop • What skills and attributes does/did your organisation require? • Essential • Desirable • Provided training • Not important • Level of perceived preparedness of all students

8. The Surveys – Alumni • Their current employment • Skills developed in Mathematics programmes • In the core programme • Co-curricular activities • During my placement • No opportunity to develop • What skills and attributes does/did your organisation require? • Essential • Desirable • Provided training • Not important • Preparedness upon graduation

9. The Skills and Attributes • Skills developed in Mathematics programmes • In the core programme • Co-curricular activities • During my placement • No opportunity to develop • What skills and attributes does/did your organisation require? • Essential • Desirable • Provided training • Not important • General IT user skills • Computer programming • Oral/verbal communication skills • Presentation skills • Written communication skills • Professional presentation/conduct • Team working skills • Foreign language skills • Problem solving skills • Management/leadership skills • Logical thinking • Literacy skills • Administrative/organisational skills • Industry/business specific knowledge • Initiative/proactive • Decision making skills • Influencing skills • Self reliant • Commercial/business awareness • Critical and reflective thinker • Innovative/enterprising • Ethical awareness • Motivated/enthusiastic • Global and cultural perspective • Career focussed/ambitious • Technical skills (pure maths) • Technical skills (applied maths) • Technical skills (statistics)

10. Analysis of the Data - method • Assign a numerical value to responses: • Essential = +2 • Desirable = +1 • Will train = 0 • Not Important = -1 • Triangulate against present or lacking • Triangulate against taught in core

11. Analysis of the Data - output

12. Findings and Interpretation • Established a set attributes clearly identified as deficient but essential: • Leadership/management • Written communication • Initiative • Presentation skills • Verbal communication • Teamwork

13. Interesting comments… • I think you are heading in the wrong direction in trying to commercialise the syllabus Alumnus Low number of applicants with required attitude/motivation; low number of applicants with required skills Employer Focus on developing skills; actually getting the job is down to the individual. 3rd Yr Student • I recruit for my department and we often find that mathematics and engineering graduates are very well prepared for our line of work due to their logical/critical thinking.Alumnus

14. What employers want – industry vs. academia • Perceived tension between academic and employer requirements. • Key skills and attributes required for academic research: • High academic achievement • Experience of completing an independent research project • Enthusiasm for the subject • Preparedness • Career focussed • Ability to communicate effectively • Willingness/ability to network

15. Impact on Teaching… the story so far… • Additional skills components in level 1 • New level 2 module: Maths at Work • Changes to level 3 information skills • Mini-presentations • Established an External Advisory Board • Integrates teaching and research • Industrial presentations • Networking opportunities

16. Level 2: Maths at Work • Team based industrial project • Commercial collaborators • Group presentation to non-expert audience • Technical report • Skills development • Integrated careers workshops • CV writing • Mock interview workshop • Focus on reflection

17. Thank you for your interest! Any questions??? Samantha Pugh S.L.Pugh@leeds.ac.uk