1. Careers in Science, Engineering, Technology (SET) and Health: His and Her story Ingrid Schoon, Andy Ross, and Peter Martin City University, London 17 March 2006 ESRC Social Science Week University of Cambridge ESRC Gender Equality Network GeNet

2. Science related careers Increasing need for well qualified and highly numerate individuals with a background in science related subjects Between 1991 and 2000: number of students with scientific and technical degrees has risen – yet fall in number of students taking science related qualifications at A-level (Sir Gareth Roberts Review, 2002) Under-representation of women in science related courses and occupations (Greenfield Report, 2002)

3. Factors influencing career choice Family background –Parental education –Parental interest and expectations regarding education –Parents occupation and employment –Role models and differential experiences Personal assets –Gender –Academic attainment and aptitude –Belief in own ability –School motivation –Domain specific interests and preferences –Differences in values School experiences –School type –Differential treatment by teachers –Number of science related options

4. Factors influencing career progression Socio-economic family background Gender School experiences/qualifications Motivations/aspirations Occupational stereotypes Career opportunities Family formation

5. But … All factors are likely influences and are difficult to distinguish Different factors are important at different stages in life Most studies are based on relatively homogenous samples, with a limited socio- economic status component Most studies based on cross-sectional data only

6. Life course perspective Linking teenage aspirations to adult outcomes Focus on science-related career development, which: –is influenced by multiple factors –takes place over time –is embedded in socio-historical context How do factors combine in predicting career choice and career development?

7. The Data: Two British Birth Cohorts 195819651970197519801985199019952000 BirthAge 5Age 10Age 16Age 26Age 30 Age7Age 11Age 16Age 23Age 33 Age 42 British Cohort Study (BCS70) National Child Development Study (NCDS) Birth

8. Socio-economic changes since 1960s Increasing gender equality Increasing participation in further education Increasing participation of women in the labour market New technologies Changes in labour market structure Major recession during the 1980s

9. Contextual-developmental model of career development Family Background Personal assets School experiences Career choice Adult Occupational Status BirthChildhood AdolescenceAdulthood

10. SET aspirations at age 16 and SET occupations in early 30s

11. Predicting SET careers by SET aspirations Odds Ratios: –NCDS men: 5.17 –BCS70 men: 6.36 –NCDS women:17.59 –BCS70 women:19.70

12. Predictors of career development Focus on science-related occupations Family background Parental social class Parental education Mothers interest in education Fathers interest in education Parents expectations regarding further education Mothers employment Personal Assets Reading at 11 and 16 Maths at 11 and 16 Self rated math ability School motivation Educational plans Occupational values Well-paid job Helping others Promotion Variety School experience Nr of science related subjects School type Single sex school Teachers general ability rating Teacher rating of math ability

13. Predicting entry into SET Occupation: Family background NCDS men NCDS women BCS70 men BCS70 women Parental social class (I vs IV/V)2.19**1.74#3.25**1.72# Mothers educationns1.93*ns Mothers occupation Not employed (baseline) Semi/unskilled Professional/skilled ns 0.51* ns Mothers interestns Fathers interestns Parental aspirations post 18- education 1.88***2.24*ns

14. Predicting entry into SET occupation: Personal assets NCDS men NCDS women BCS70 men BCS70 women Reading test at age 10/11ns Reading test at age 16ns1.48#ns Math test at age 10/11ns1.42#ns Math test at age 161.30**ns1.67**1.73* Self rated math ability at 161.54**2.41***1.85*ns Educational plans post 18ns2.50**2.14***ns School motivation1.32***ns Values - well-paid jobns - help othersns - promotionns 1.45* - varietyns 1.25*ns SET aspiration2.92***5.90***4.30***9.62***

15. Predicting entry into SET occupation: School environment NCDS menNCDS women BCS70 men BCS70 women Number of science subjects1.18*1.58***ns1.47* Teacher rating general ability (11) ns Teacher rating math ability (16) 1.66***1.95***1.61*2.42* School typens Single sex schoolns

16. Predicting entry into SET occupation: Significant factors in the Full model NCDS men NCDS women BCS70 men BCS70 women Self rated math ability (16)1.34*1.86*ns Math test at age 16ns 1.51*ns School Motivation1.25**ns Educational plansns2.25*1.98**ns Occupational value: Varietyns 1.25*ns SET aspiration2.64***3.79***4.31***8.34*** Number of science subjects1.18*1.58***ns1.47* Teacher rated math ability (16)1.66***1.95***1.61*1.76*

17. Predictors of occupational choice

18. Predictors of occupational choice: Significant factors in the Full model NCDS menNCDS women BCS70 menBCS70 women Reading test (10/11)ns1.35*ns1.43# English Exams (16)ns0.80*ns Self rated math ability (16) ns2.52***ns1.82# Teacher rated math ability (16) ns1.47*ns Educational plans1.40*ns 2.81*** School motivation1.45***ns1.30*ns Help othersns 1.30* Number of science subjects 1.77***2.43***1.34**2.10*** Independent School (vs. LEA) ns1.99*ns

19. Summary: Who becomes a scientist, technologist, engineer, or health professional? Persisting gender imbalance: both in terms of aspiration and occupation Increase in science-related careers is slight, and mainly driven by young men entering IT professions

20. Summary: Predicting entry into a science-related career Interest and attachment to a science- related career are formed early in life Aspirations in adolescence most important School experiences are crucial in attracting young people to a career in science: Teachers maths ratings Number of science subjects entered

21. Conclusion Much remains to be done to improve intake in science-related occupation Findings call for : –equal opportunities in access to science related courses at school –Recognition and encouragement of science and math related ability by teachers –Making school experience more relevant and engaging, feeding the needs and values of young people

22. Thank you For further information please contact: I.Schoon@city.ac.uk