Careers in Science, Engineering, Technology (SET) and Health: His and Her story Ingrid Schoon, Andy Ross, and Peter Martin City University, London 17 March.
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Careers in Science, Engineering, Technology (SET) and Health:
His and Her storyIngrid Schoon, Andy Ross, and Peter Martin
City University, London
17 March 2006
ESRC Social Science Week
University of Cambridge
ESRC Gender Equality Network
GeNet
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 Robert’s Review, 2002)
• Under-representation of women in science related courses and occupations (Greenfield Report, 2002)
Factors influencing career choice• Family background
– Parental education– Parental interest and expectations regarding
education– Parent’s 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
Factors influencing career progression
• Socio-economic family background• Gender • School experiences/qualifications• Motivations/aspirations• Occupational stereotypes• Career opportunities• Family formation
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
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?
The Data: Two British Birth Cohorts
1958 1965 1970 1975 1980 1985 1990 1995 2000
Birth
Age 5
Age 10
Age 16
Age 26
Age 30
Age7
Age 11
Age 16
Age 23
Age 33
Age 42
British Cohort Study (BCS70)
National Child Development Study (NCDS)
Birth
Socio-economic changes since 1960’s
• 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 1980’s
Contextual-developmental model of career development
Family Background
Personal assets
School experiences
Career choice
Adult Occupation
al Status
Birth Childhood Adolescence Adulthood
SET aspirations at age 16 and SET occupations in early 30’s
0
5
10
15
20
SET aspiration SET occupation
SET aspiration 17.2 13.5 7.4 5.4
SET occupation 11.1 9.4 3.1 2.7
BCS70 men NCDS menBCS70 women
NCDS women
Predicting SET careers by SET aspirations
• Odds Ratios:– NCDS men: 5.17– BCS70 men: 6.36– NCDS women: 17.59– BCS70 women:19.70
Predictors of career development
Focus on science-related occupations
Family background•Parental social class
•Parental education
•Mother’s interest in education
•Father’s interest in education
•Parents expectations regarding further education
•Mother’s 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
•Teacher’s general ability rating
•Teacher rating of math ability
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#
Mother’s education ns 1.93* ns ns
Mother’s occupation•Not employed (baseline)•Semi/unskilled•Professional/skilled
nsns
nsns
0.51*ns
nsns
Mother’s interest ns ns ns ns
Father’s interest ns ns ns ns
Parental aspirations post 18- education
1.88*** 2.24* ns ns
Predicting entry into SET occupation: Personal assets
NCDS men
NCDS women
BCS70 men
BCS70 wome
n
Reading test at age 10/11 ns ns ns ns
Reading test at age 16 ns 1.48# ns ns
Math test at age 10/11 ns 1.42# ns ns
Math test at age 16 1.30** ns 1.67** 1.73*
Self rated math ability at 16 1.54** 2.41*** 1.85* ns
Educational plans post 18 ns 2.50** 2.14*** ns
School motivation 1.32*** ns ns ns
Values - well-paid job ns ns ns ns
- help others ns ns ns ns
- promotion ns ns ns 1.45*
- variety ns ns 1.25* ns
SET aspiration 2.92*** 5.90*** 4.30*** 9.62***
Predicting entry into SET occupation:
School environmentNCDS men
NCDS women
BCS70 men
BCS70 women
Number of science subjects
1.18* 1.58*** ns 1.47*
Teacher rating general ability (11)
ns ns ns ns
Teacher rating math ability (16)
1.66*** 1.95*** 1.61* 2.42*
School type ns ns ns ns
Single sex school ns ns ns ns
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 ns
Math test at age 16 ns ns 1.51* ns
School Motivation 1.25** ns ns ns
Educational plans ns 2.25* 1.98** ns
Occupational value: Variety ns ns 1.25* ns
SET aspiration 2.64*** 3.79*** 4.31*** 8.34***
Number of science subjects 1.18* 1.58*** ns 1.47*
Teacher rated math ability (16) 1.66*** 1.95*** 1.61* 1.76*
Predictors of
occupational choice
Predictors of occupational choice: Significant factors in the Full model
NCDS men
NCDS women
BCS70 men BCS70 women
Reading test (10/11) ns 1.35* ns 1.43#
English Exams (16) ns 0.80* ns ns
Self rated math ability (16)
ns 2.52*** ns 1.82#
Teacher rated math ability (16)
ns 1.47* ns ns
Educational plans 1.40* ns ns 2.81***
School motivation 1.45*** ns 1.30* ns
Help others ns ns ns 1.30*
Number of science subjects
1.77*** 2.43*** 1.34** 2.10***
Independent School (vs. LEA)
ns 1.99* ns ns
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
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: Teacher’s maths ratings Number of science subjects entered
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
Thank you
For further information please contact:
I.Schoon@city.ac.uk
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