Transcript What is happening to the gap between boys and girls at

What is happening
to the gap between
boys and girls at
GCSE and A level?
Tim Oates, Group Director Research and
Development
Dispelling simplistic representations
of boys’ underachievement
Media attention on ‘underperforming boys’ has paid little attention to important
subtleties in the nature of the problem, and in the findings from research.
In his influential 2001 pamphlet, John Marks failed to highlight that both boys
and girls have improved, but boys have improved less (rather than boys’
performance getting worse in absolute terms). It’s not all boys at all levels/ages
who are underperforming.
There are complex social phenomena behind the differences in boys’ and girls’
relative performance - including gender-stereotypical peer group pressure
amongst boys which reinforces low levels of engagement with learning
(Warrington M, Younger M. 2005).
This is not a new problem; if raw scores in the 11+ had been used to determine
selection, then grammar schools in the 50s and 60s would have been populated
almost exclusively by girls. Likewise, the historical figures for O level
achievement in the 1960s and 70s show a gap in gender achievement, roughly
5% difference in pass rate, 10% in some subjects (eg languages) (Murphy R.
1980).
Understanding where to look to explain gender
differences in attainment
It IS complex
There are no simple explanations for the gender gap; several factors
are likely to have an influence: pupil grouping, assessment
techniques, the curriculum, teaching styles, teacher expectations, role
models, and the way teachers reward and discipline. Ofsted have
evidence of gendered behaviour by teachers – including setting,
attention-management, subject choice advice, and decisions about
entry to tiered papers….and more…
It all begins very early
Babies are actively processing speech before birth; they can recognise a
story that they have heard while still in the womb
DeCasper, A. J. and Spence, M. J. (1986). Prenatal maternal speech
influences: newborns’ perception of speech sounds. Infant Behavior and
Development, 9, 133–50.
Maternal-infant bonding is crucial to engagement with the world
Oates, J. M. and Stevenson, J. (2005) ‘Temperament and development’, in
Oates, J. M., Wood, C. P. and Grayson, A, in Psychological Development and
Early Childhood, Oxford/Milton Keynes, Blackwell Publishing/The Open
University
Gendered behaviour is an insidious element in care and development of
the child
Seavey et al (1975) The effect of gender labels on adults responses to infants.
Sex Roles, 1, 103-109.
Condry and Condry (1976) Sex differences: a study of the eye of the beholder.
Child Development 47, 812-819.Stern and Karraker (1989) Sex stereotyping of
infants: A review of gender labelling studies. Sex Roles, 20, 501-522.
Early experiences affect cognitive development in a profound way;
babies in non-inflected language settings lose the acuity to differentiate
certain sounds in inflected languages
Soderstrom, M. 2002. The acquisition of inflection morphology in early
perceptual knowledge of syntax. Dissertation Johns Hopkins U. Saffran, JR,
A. Senghas, and J.C. Trueswell. 2001. The acquisition of language by
children. Proc Natl Acad Sci U S A. 98 23 12874-12875. Slobin D.I. ed. 1985.
The Cross-Linguistic Study of Language Acquisition. Erlbaum
Differences in PISA in the performance on maths scales of different
nations can be explained in part by different cultural behaviours
Tymms P 2005
Female issues: global
UNESCO
Seminar in ECOWAS Sub-region:
Gender Equality in Basic Education:
Major Challenge to meet Dakar EFA Goals,
18-20 February 2002
Accra, Ghana
50 years after the Universal Declaration of Human Rights, advocating that
Education a fundamental human right, 11 years after the Jomtien Declaration for
All (1990) promoting that education for girls and women as an urgent priority in
attaining the EFA goals, and in spite of all the efforts made by all the
stakeholders including governments, international organisation, nongovernmental organisations and the civil society, the situation of women and
girls’ education is far from satisfactory. According to the EFA 2000 assessment,
60% of 113 million out-of-school children are girls, and of 880 million adult
illiterates, 2/3 are women. Moreover, gender biased practices and attitudes still
prevail in education system and learning environment, including schools, families
and society at large.
Female issues: global
US AID | AFGHANISTAN
More than 90 percent of Afghan women living in rural areas are illiterate.
Afghanistan’s economy was devastated by nearly a quarter century of warfare
and many widows became the sole providers for their families.
Some of the schools that educate girls and boys have recently been targeted by
extremists who oppose the integration and empowerment of girls in Afghanistan.
They seek to intimidate those who advance girls’ education, which was outlawed
under the Taliban until just a few years ago.
Afghan women have taken major steps since 2001. They held leadership
positions in the Constitutional Loya Jirga, a female candidate ran for president,
and thousands of women voted in the 2004 presidential elections and the 2005
parliamentary elections.
Of the 6.8 million Afghans who voted in the September 2005 elections, 43% were
women.
PISA: 2000 and 2003
In PISA 2003, boys performed significantly better than girls on the combined
mathematics scale in 27 participating countries. However, the magnitude of
these gender differences was generally small. No gender differences were
observed in 12 countries and in one country (Iceland) girls performed
significantly better than boys.
As was the case in PISA 2000, girls performed significantly better than boys on
the reading test in all but one country and in all provinces in PISA 2003.
However, the gap between girls and boys in reading was much larger than the
gap between boys and girls in mathematics.
In PISA 2000, no significant gender differences were observed between boys
and girls in any country or any province on the science test. In PISA 2003, in 12
countries, boys performed significantly better than girls in science. However, as
with mathematics, the gap was small, at six points at the OECD average.
In the case of problem solving, girls outperformed boys in only six countries
http://www.pisa.oecd.org/pages/0,2987,en_32252351_32235731_1_1_1_1_1,
00.html
PISA: Finland
The findings of PISA suggest that as a rule Finland has managed to
achieve both high quality and high equality of reading literacy
outcomes. In guaranteeing gender equality, however, Finland has been
less successful – witness the fact that in PISA the gender gap in reading
literacy was widest in Finland, that is, 51 points (the OECD average
being 32 points). Moreover, the gender differences found in Finland
proved significant on all three subscales.
In retrieving information the difference was smallest (44 points), and
in reflection and evaluation greatest (63 points). In interpreting texts, the
difference was 51 points. Compared to previous international reading
literacy assessments, the gender gap, on the whole, seems to have
widened not only in Finland but also in the other OECD countries.
What can we see in qualifications data?
Unpacking differential performance #1
Gender (sex) remains an important category of analysis.
You want a biased test … we can give you a biased test …
Scaffolding (context) (Murphy and Gipps 1987)
Spiders (1999 KS2 tests English)
Rockets (test development forum 2006)
Putative
Relationship between ♀ ♂: version #1
Putative
Relationship between ♀ ♂: version #2
Putative
Relationship between ♀ ♂: version #3
Examples of a Mark Distribution
for an OCR mathematics GCSE
100.00
90.00
80.00
Cumulative Percentage
70.00
60.00
female
50.00
male
40.00
30.00
20.00
10.00
0.00
0
100
200
300
400
500
Mark
600
700
800
900
Examples of a Mark Distribution for
an OCR mathematics GCSE
5.00
4.00
Gender difference
3.00
2.00
diff
1.00
0.00
0
100
200
300
400
-1.00
Mark
500
600
700
800
Examples of a Mark Distribution for
an OCR mathematics GCSE
5.00
100.00
90.00
4.00
80.00
3.00
60.00
female
male
50.00
40.00
Gender difference
Cumulative Percentage
70.00
2.00
diff
1.00
30.00
20.00
0.00
0
10.00
100
200
300
400
0.00
0
100
200
300
400
500
Mark
600
700
800
900
-1.00
Mark
500
600
700
800
National curriculum assessment – trends 1980 to1995
Boys have improved less quickly and significantly than girls, and
therefore the gender gap widened. Boys’ attainment improved
significantly over the period 1980 to 1995. Boys’ attainment in maths
and science at KS2 & 3 slightly exceeded that of girls.
Two case studies:
3D maths (preferential avoidance issues)
science (teaching, teacher training, and facility issues)
National curriculum assessment – current position
Percentages of pupils achieving Level 5 or above
and Level 6 or above in Key Stage 3 tests by gender,
2004-2006
Key Stage 3
Percentage of pupils at Level 5 or above
Boys
Girls
2004
2005
2006
2004
2005
2006
English Test
64
67
65
78
81
80
Reading Test
60
61
59
71
76
74
Writing Test
65
71
69
80
82
83
Mathematics Test
72
73
76
74
74
77
Science Test
65
69
71
67
70
73
Percentage of pupils at Level 6 or above
Boys
Girls
2004
2005
2006
2004
2005
2006
English Test
2764
28
27
41
42
42
Reading Test
26
25
25
38
40
40
Writing Test
29
32
30
43
43
44
Mathematics Test
52
53
57
52
53
57
Science Test
34
38
41
35
36
41
Percentages of pupils achieving Level 4 or above
and Level 5 or above in Key Stage 2 tests and teacher
assessments by gender, 2004-2006
Key Stage 2
Percentage of pupils at Level 4 or above
Boys
Girls
2004
2005
2006
2004
2005
2006
English Test
72
74
74
83
84
85
Reading Test
79
82
79
87
87
87
Writing Test
56
55
59
71
72
75
Mathematics Test
74
76
77
74
7574
75
Science Test
86
86
86
86
87
87
English TA
68
70
72
79
81
82
Mathematics TA
75
76
78
7574
76
78
Science TA
82
82
83
84
84
85
Percentages of pupils achieving Level 4 or above
and Level 5 or above in Key Stage 2 tests and teacher
assessments by gender, 2004-2006
Percentage of pupils at Level 5 or above
Boys
Girls
2004
2005
2006
2004
2005
2006
English Test
2172
21
26
33
33
39
Reading Test
33
39
41
46
47
53
Writing Test
13
10
13
21
21
23
Mathematics Test
33
33
36
29
28
31
Science Test
43
48
45
43
46
46
English TA
220
21
23
30
32
34
Mathematics TA
31
32
34
28
28
30
Science TA
34
37
38
33
35
37
Unpacking differential performance #2
Jean Rudduck and John Gray (Homerton College Cambridge) have undertaken
considerable pupil-based research into differential performance, and remain
concerned at the personal and social consequences of many boys’ failure to develop
engagement with learning and to achieve to a reasonable level whilst they are in
compulsory education.
Madeleine Arnott (Cambs) argued that the most significant issue in explaining
difference is the way in which boys and girls regard school (Arnott M, 1997).
Amongst boys, it’s ‘cool’ to be seen not to work or comply. Alongside this, boys tend
to blame poor performance on externalised factors (‘bad teaching’, ‘wrong test
questions’), while girls tend to blame themselves and their competence, and work
harder in consequence to improve and to overcome problems.
Girls and Boys used gender friendship groupings to cope with transition (Galton et
al, 1999) .
Jean Rudduck’s work on GCSE preparation suggests that boys tend to leave it to
the last minute and rely on ‘natural talent’; in subjects where you need to build skills
and knowledge over time (eg languages, English etc). This adversely affects their
performance; leads to the peculiar subject choices post-16.
Studies by teachers in schools (eg Beacon School Crowborough, 1993) revealed
very different patterns of boys’ and girls’ homework effort.
Proportion of students gaining A (relative to cohort)
Proport
English
English
English Literature
English Literature
Modern Languages
Modern Languages
Mathematcis
Mathematcis
Double Science
Double Science
Single Science
Single Science
Biology
Biology
Chemistry
Chemistry
Physics
Physics
0%
10%
Female
20%
Male
0%
ive to cohort)
e
Proportion of students gaining A (within gender)
English
English Literature
Modern Languages
Mathematcis
Double Science
Single Science
Biology
Chemistry
Physics
20%
0%
10%
20%
Female
Male
30%
Proportion of students gaining A (relative to cohort)
Proportion of students gaining A (within gender)
English
English
English Literature
English Literature
Modern Languages
Modern Languages
Mathematcis
Mathematcis
Double Science
Double Science
Single Science
Single Science
Biology
Biology
Chemistry
Chemistry
Physics
Physics
0%
10%
Female
20%
Male
0%
10%
20%
Female
Male
30%
Proportion of students gaining C (within gender)
Proportion of students gaining C (relative to cohort)
English
English
English Literature
English Literature
Modern Languages
Modern Languages
Mathematcis
Mathematcis
Double Science
Double Science
Single Science
Single Science
Biology
Biology
Chemistry
Chemistry
Physics
Physics
0%
20%
10%
Female
Male
0%
20%
10%
Female
Male
30%
Proportion of students gaining A*-C (relative to cohort)
Proportion of students gaining A*-C (within gender)
English
English
English Literature
English Literature
Modern Languages
Modern Languages
Mathematics
Mathematics
Double Science
Double Science
Single Science
Single Science
Biology
Biology
Chemistry
Chemistry
Physics
Physics
0%
10%
20%
30%
Female
40%
Male
50%
60%
0%
10%
20%
30%
40%
50%
Female
60%
Male
70%
80%
90%
100%
Number of Biology compared to Double Science candidates
A* - Female
A* - Male
A - Female
A - Male
C - Female
C - Male
0
10000
20000
30000
Biology
40000
50000
Double Science
60000
70000
80000
Number of Chemistry compared to Double Science candidates
A* - Female
A* - Male
A - Female
A - Male
C - Female
C - Male
0
10000
20000
30000
Chemistry
40000
50000
Double Science
60000
70000
80000
Number of Physics compared to Double Science candidates
A* - Female
A* - Male
A - Female
A - Male
C - Female
C - Male
0
10000
20000
30000
Physics
40000
50000
Double Science
60000
70000
80000
Modern language GCSEs taken - German, French and Spanish
25000
20000
15000
F
M
10000
5000
0
2001
2003
2005
Others categories are equally, if not more, significant for policy
It is important to recognise that while gender is a valuable category
for analysis and causes can be attributed to gendered aspects of
educational practice and to gendered attitudes and approaches to
learning by pupils themselves, social class and ethnicity are still
more determining of achievement than gender. (Cambridge
Assessment 2006). Child poverty, irrespective of gender, remains a
pressing social policy issue (Robinson P, 1998).
Proportion of students gaining A/A* (w ithin social class)
Proportion of students gaining A*-C (w ithin social class)
English
English
English Literature
English Literature
Modern Languages
Modern Languages
Mathematics
Mathematics
Double Science
Double Science
Single Science
Single Science
Biology
Biology
Chemistry
Chemistry
Physics
Physics
0%
10%
20%
No FSM
30%
FSM
40%
50%
0%
10%
20%
30%
40%
50%
No FSM
60%
FSM
70%
80%
90%
100%
Gender and subject choice
• While girls are now achieving better academic results than boys
at age 16, relatively few young women are choosing science or
science-related subjects for further study.
• Boys dominate in maths, science and technology at A level and
far more men than women study these subjects in higher
education. This has significant implications for men’s and
women’s career choices and future earnings: 60% of working
women are clustered in only 10% of occupations; and men are
also under-represented in a number of occupations.
Top A Levels
FEMALE
MALE
2001
GS
2003
11.62%
GS
2005
9.66%
GS
2001
9.62%
GS
2003
11.88%
GS
2005
9.98%
GS
10.12%
EngLit
7.79
EngLit
7.36
EngLit
7.62
Math
10.29
Math
7.86
Math
7.61
Bio
6.24
Psy
6.24
Psy
7.35
Phy
6.08
Phy
5.58
History
5.34
Math
6.22
Bio
5.94
Bio
6.05
Geo
4.90
BS
5.05
Phy
5.34
Psy
5.04
Math
4.85
History
4.73
BS
4.78
History
4.79
Bio
4.99
History
4.33
History
4.42
Soc
4.41
Chem
4.61
Geo
4.59
BS
4.74
Chem
4.01
Soc
4.20
Chem
3.94
Bio
4.44
Bio
4.42
Chem
4.73
Soc
3.85
Chem
3.80
Math
3.93
History
4.28
Chem
4.20
Geo
4.38
Geo
3.69
Geo
3.39
Geo
3.12
EngLit
3.61
EngLit
3.42
EngLit
3.30
BS
3.44
BS
3.07
Media
2.98
PE
2.88
ICT
3.24
PE
3.18
Uptake of individual subjects by sex in
2001-2005 (% of A-level entry)
Male
Subject
General Studies
English Literature
Mathematics
Biology
History
Geography
Chemistry
Business Studies
Physics
Psychology
Sociology
Media/Film/TV.Stds.
Sports/P.E. Stds.
ICT
English Language
English
French
D & T design
Economics
Art & Des. – Fine Art
Drama
Art & Design
Com.Stds/Computing
Religious Stds.
Law
Politics
German
Music
Spanish
Maths (Further)
D&T Product Design
2001
42
13
32
16
15
18
18
16
22
5
4
5
9
4
4
4
4
4
10
2
7
9
2
3
4
2
2
1
4
-
2002
29
14
26
16
17
17
15
17
21
6
4
7
10
10
5
4
4
9
9
4
3
3
8
2
3
4
2
2
1
3
-
2003
28
12
26
15
17
17
14
16
20
7
4
7
11
10
5
4
4
9
4
4
3
7
3
4
5
2
2
1
3
9
2004
28
12
26
14
18
16
14
16
18
8
4
8
10
8
4
4
4
8
4
4
2
6
4
4
4
2
2
2
4
8
2005
28
14
26
16
18
14
16
14
18
10
4
8
10
8
6
4
4
8
4
4
2
4
4
4
6
2
2
2
4
9
Uptake of individual subjects by sex in
2001-2005 (% of A-level entry)
Female
Subject
General Studies
English Literature
Mathematics
Biology
History
Geography
Chemistry
Business Studies
Physics
Psychology
Sociology
Media/Film/TV.Stds.
Sports/P.E. Stds.
ICT
English Language
English
French
D & T design
Economics
Art & Des. – Fine Art
Drama
Art & Design
Com.Stds/Computing
Religious Stds.
Law
Politics
German
Music
Spanish
Maths (Further)
D&T Product Design
2001
40
29
17
22
16
13
14
12
5
15
13
6
5
2
8
9
9
1
4
5
11
9
2
3
4
2
2
1
4
-
2002
27
27
13
22
16
12
14
10
5
18
13
8
5
4
8
8
8
4
3
7
8
6
8
2
3
4
2
2
1
3
-
2003
26
26
13
202
16
12
13
10
5
20
13
9
5
5
8
7
7
3
8
8
6
7
3
4
5
2
2
1
3
9
2004
26
26
14
20
16
12
12
8
4
22
12
10
6
4
8
8
6
2
8
8
6
6
4
4
4
2
2
2
4
8
2005
26
26
12
20
16
10
12
8
4
24
14
10
6
4
8
8
6
2
8
8
6
4
4
4
6
2
2
2
4
9
Most common combinations of at least three A-level
subjects in 2001-2005 excluding General Studies
(%of candidates with at least three A-levels)
2001
Combination
%
Cum%
Biology
Chemistry
Mathematics
4.2
4.2
Chemistry
Physics
Mathematics
2.9
7.1
Biology
Chemistry
Physics
1.6
8.7
Biology
Chemistry
Geography
1.0
9.7
Physics
Mathematics
Computing
0.9
10.6
Chemistry
Physics
Mathematics
0.9
11.5
Physics
Mathematics
Geography
0.6
12.1
Biology
Chemistry
Physics
0.6
12.7
History
Sociology
English Lit.
0.6
13.3
History
English Lit.
French
0.6
13.9
Further Maths
Mathematics
2002
Combination
%
Cum%
Biology
Chemistry
Mathematics
2.7
2.7
Chemistry
Physics
Mathematics
1.9
4.6
Biology
Chemistry
Physics
1.4
6.1
Biology
Chemistry
Geography
1.0
7.1
Physics
Mathematics
Computing
0.7
7.9
Biology
Chemistry
Physics
0.7
8.6
Biology
Chemistry
Psychology
0.7
9.3
Chemistry
Physics
Mathematics
0.7
10.0
History
Sociology
English Lit.
0.5
10.5
Physics
Mathematics
D&T Prod.Design
0.5
11.0
Mathematics
Further Maths.
2003
Combination
%
Cum%
Biology
Chemistry
Mathematics
2.7
2.7
Chemistry
Physics
Mathematics
1.8
4.5
Biology
Chemistry
Physics
1.3
5.8
Biology
Chemistry
Geography
0.9
6.7
Biology
Chemistry
Psychology
0.8
7.5
Physics
Mathematics
Computing
0.7
8.2
Biology
Chemistry
Physics
0.6
8.8
Chemistry
Physics
Mathematics Further Maths
0.6
9.4
History
Psychology
English Lit.
0.6
9.9
Physics
Mathematics
Geography
0.5
10.4
Mathematics
2004
Combination
%
Cum%
Biology
Chemistry
Mathematics
2.9
2.9
Chemistry
Physics
Mathematics
1.6
4.5
Biology
Chemistry
Physics
1.1
5.6
Biology
Chemistry
Geography
0.9
6.5
Biology
Chemistry
Psychology
0.9
7.4
Biology
Chemistry
Physics
0.8
8.2
Chemistry
Physics
Mathematics Further Maths
0.7
8.9
History
Psychology
English Lit.
0.5
9.4
History
Religious
Studies
English Lit.
0.5
9.9
Physics
Mathematics
D&T Product Design
0.5
10.4
Mathematics
2005
Combination
%
Cum%
Biology
Chemistry
Mathematics
2.9
2.9
Chemistry
Physics
Mathematics
1.5
4.4
Biology
Chemistry
Physics
1.1
5.6
Biology
Chemistry
Psychology
1.0
6.5
Biology
Chemistry
Geography
0.8
7.4
Biology
Chemistry
Physics
Mathematics
0.7
8.1
Chemistry
Physics
Mathematics
Further Maths
0.7
8.8
History
Psychology
English Lit.
0.7
9.4
History
Religious
Studies
English Lit.
0.5
10.0
History
Politics
English Lit.
0.5
10.5
Female
First class
2:1
2:2
3/pass
Unc
Total
3015
25075
18430
3555
1520
51595
Male
95/96
5.8%
7.4%
48.6% 39.2%
35.7% 37.6%
6.9% 11.8%
2.9%
3.9%
Female
3285
17320
16605
5225
1735
44170
11495
56560
29935
3975
5800
107770
Male
2004/05
10.6% 12.1%
52.5% 44.3%
27.8% 31.5%
3.7%
6.8%
5.4%
5.4%
10275
37650
26375
5785
4580
85025
Occupational segregation
Occupation segregation is one of the main causes of the gender pay
gap. Women’s employment is highly concentrated in certain
occupations and those occupations which are female-dominated are
often the lowest paid. In addition, women are still under-represented in
the higher paid jobs within occupations – the “glass ceiling” effect.
The gender pay gap is derived from median hourly earning
(excluding overtime) for men and women. The full-time gender pay
gap currently stands at 13.0 per cent using the median and 17.1 per
cent using the mean, which means that women who work full time
are paid on average just 87.0 per cent of men’s hourly earnings using
the median and 82.9 per cent using the mean. There was a
decrease in the full-time gender pay gap of 1.5 percentage points in
2005 using the median and 0.7 percentage points using the mean.
(Since October 2004 Office for National Statistics has recommended
measuring the gender pay gap using the median, rather than the
mean value. This is because the mean value can be distorted by a
small number of very-high earning individuals who are predominantly
men.)
First degree
Masters
PhD
HND/FD
Female
Male
Total
Female
Male
Total
Female
Male
Total
Marketing, Sales and Advertising
Professionals
4.5
4.1
4.3
3.1
2.3
2.7
1.3
0.6
1.0
Commercial, Industrial and Public Sector
Managers
8.2
12.1
9.8
19.1
28.9
23.7
6.2
7.9
Scientific Research, Analysis &
Development Professionals
1.1
1.0
1.1
3.6
3.0
3.3
16.5
Engineering Professional
0.8
5.8
2.9
0.9
5.3
2.9
Health Professionals and Associate
Professionals
17.1
6.7
12.8
9.6
3.7
Education Professionals
9.0
3.4
6.7
14.0
Business and Financial Professionals
and Associate Professionals
6.5
8.3
7.2
Information Technology Professionals
1.2
7.7
Arts, Design, Culture and Sports
Professionals
4.4
Legal Professionals
Female
Male
Total
2.2
1.5
1.9
7.1
9.5
10.2
9.8
18.3
17.4
0.3
0.5
0.4
1.9
6.5
4.3
0.6
8.2
4.4
6.9
4.9
6.9
5.9
3.1
0.3
1.7
8.2
11.3
24.0
21.1
22.5
5.1
1.8
3.4
7.5
10.4
8.8
2.7
3.7
3.2
2.4
2.6
2.5
3.9
2.0
6.8
4.2
0.5
4.2
2.4
1.2
6.7
3.9
6.2
5.1
4.9
4.3
4.6
1.9
1.6
1.7
5.4
7.3
6.3
0.8
0.6
0.7
1.3
1.3
1.3
0.3
0.7
0.5
0.2
0.1
0.1
Social & Welfare Professionals
4.5
1.7
3.3
9.0
2.7
6.0
11.6
3.6
7.4
2.6
0.5
1.5
Other Professionals, Associate
Professional and Technical Occupations
3.8
7.3
5.3
11.4
11.0
11.2
24.1
21.3
22.6
2.8
8.5
5.6
Numerical Clerks and Cashiers
3.4
3.4
3.4
1.0
1.0
1.0
0.3
0.1
0.2
2.9
2.2
2.6
Other Clerical and Secretarial
14.4
9.4
12.3
7.5
4.6
6.2
2.2
1.2
1.6
11.4
6.9
9.2
Retail, Catering, Waiting and Bar Staff
8.6
9.0
8.7
1.6
1.9
1.8
0.2
0.3
0.2
17.1
19.7
18.4
Other Occupations
11.7
13.1
12.3
3.3
4.2
3.7
1.1
1.7
1.4
32.9
23.0
28.0
Unknown Occupations
0.2
0.3
0.2
0.2
0.3
0.3
0.5
0.4
0.4
0.3
0.2
0.2
All occupations
100
100
100
100
100
100
100
100
100
100
100
100
Gender breakdown amongst occupations
Amongst first degree graduates entering health professions, there were 3.6
times more females than males. This is attributed partly to the popularity of
nursing, and to a lesser extent, medicine, as first degree subjects of choice
amongst women. At PhD level, those entering health occupations, albeit at a
much smaller number than for first degree and Masters graduates, were more
likely to be males (3:2 male: female).
Similarly, amongst first degree graduates entering education professions, there
were 3.8 times more females than males; for social & welfare professions, 3.7
times; legal professions, two times; scientific research, analysis & development
professionals, 1.7 times; and marketing, sales and advertising professionals,
1.6 times.
On the other hand, of first degree graduates entering the engineering
professions, there were 5.5 times more males than females; for IT professions,
4.6 times, and for other professional, associate professional and technical
occupations, 1.4 times.
Qualification requirement by type of job
•
•
•
Although female first degree graduates were more likely than their male peers to
be in health professions or associate professions, they were less likely to report
that their degree was a formal requirement and more likely to say that it has not
been required for obtaining their employment. Many of the female graduates
employed in these occupations were nurses, of which only around half (54%)
reported that a degree was a formal requirement. In contrast, relatively few male
graduates went into nursing and of those working in the health professions, a
higher proportion were employed as doctors, for which a medicine degree,
unsurprisingly, was formally required.
Of first degree graduates entering work as business and financial professionals
and associate professionals, 52.6% were females and 47.4% were males. Males
working in these types of jobs, however, were more likely than their female
counterparts to believe that their degree was a formal requirement, with 41.3%
noting that this was the case compared with 32.5% of females. Female graduates
were also more likely to report that their qualification was not required: 21%
reported that this was the case compared with 17.5% of males.
Female graduates were not only less likely than male graduates to be in IT
occupations, they were less likely to be in IT jobs for which a degree qualification
was a requirement.
The link to later learning
While the gap can legitimately be analysed as a gender gap (since
detailed work has indicated that different psychological and social
mechanisms are at work in respect of males and females) the
increasing gap in performance can be seen as testimony to the
success of measures designed to enhance the performance of girls.
The improved – and improving – performance of girls is testimony to
the things which were put in place to allow women access to science
and maths, and to learning and assessment – it can be viewed as the
product of the success of education in overcoming sociallydetermined problems.
Fashion Designer
Chef
Computer Programmer
Doctor
Road Sweeper
Car Mechanic
Bank Clerk
Solicitor
Traffic Warden
Painter and Decorator
Primary School Teacher
Hotel Manager
Supermarket Shelf Filler
Police Officer
Hotel Receptionist
Journalist
Scientist
Factory Worker
Builder
Bank Manager
Cleaner
Electrician
Firefighter
Secondary School Teacher
Nurse
Sales Assistant
Accountant
Typist
Bus Driver
Percentage breakdown of key stage 1 primary
school pupils who stated that occupations
3: Percentage
were for a man,Figure
woman
orbreakdown
both of key stage 1 primary school pupils
who stated that occupations were for a man, woman or both
100%
90%
80%
70%
60%
50%
40%
both
woman
man
30%
20%
10%
0%
Fashion Designer
Chef
Computer Programmer
Doctor
Road Sweeper
Car Mechanic
Bank Clerk
Solicitor
Traffic Warden
Painter and Decorator
Primary School Teacher
Hotel Manager
Supermarket Shelf Filler
Police Officer
Hotel Receptionist
Journalist
Scientist
Factory Worker
Builder
Bank Manager
Cleaner
Electrician
Firefighter
Secondary School Teacher
Nurse
Sales Assistant
Accountant
Typist
Bus Driver
Percentage breakdown of key stage 2
primary school pupils who stated that
Figure 4: Percentage breakdown of key stage 2 primary school pupils
occupations were
for a man, woman or both
who stated that occupations were for a man, woman or both
100%
90%
80%
70%
60%
50%
40%
both
woman
man
30%
20%
10%
0%
Occupations
Man %
Woman %
Both %
N
Bus Driver
67
2
31
638
Typist
10
41
49
641
Accountant
23
19
58
635
Sales Assistant
15
21
64
634
Nurse
3
68
29
640
Secondary School Teacher
16
19
65
640
Firefighter
81
1
18
643
Electrician
75
7
18
639
Cleaner
20
48
32
637
Bank Manager
37
12
51
644
Builder
91
2
7
641
Factory Worker
31
15
54
641
Scientist
36
14
50
642
Journalist
27
17
56
641
Hotel Receptionist
18
26
56
641
Police Officer
44
3
53
641
Supermarket Shelf Filler
18
24
58
635
Hotel Manager
43
14
43
639
Primary School Teacher
5
36
59
635
Painter and Decorator
47
8
45
640
Traffic Warden
37
15
48
646
Solicitor
35
17
48
643
Bank Clerk
22
22
56
643
Car Mechanic
82
5
13
639
Road Sweeper
64
9
27
640
Doctor
40
8
52
644
Computer Programmer
36
17
47
641
Chef
53
12
35
641
Fashion Designer
10
59
31
638
Percentage
breakdown of
Key stage 1
Primary school
pupils who
stated that
occupations
were for a man,
woman or both
Occupations
Man %
Woman %
Both %
N
Bus Driver
56
1
43
926
Typist
3
44
53
923
Accountant
14
15
71 (58)
921
Sales Assistant
18
17
65
925
Nurse
1
54
45 (29)
927
Secondary School
Teacher
10
15
75
925
Firefighter
77
1
22
924
Electrician
86
2
12
921
Cleaner
7
60
33
921
Bank Manager
32
6
62
926
Builder
92
1
7
926
Factory Worker
32
8
60
924
Scientist
18
4
78 (50)
916
Journalist
11
15
74
922
Hotel Receptionist
5
42
53
925
Police Officer
30
1
69
924
Supermarket Shelf Filler
12
17
71
921
Hotel Manager
36
7
57
923
Primary School Teacher
3
26
71
921
Painter and Decorator
47
4
49
920
Traffic Warden
23
13
64
925
Solicitor
23
11
66
921
Bank Clerk
15
17
68
918
Car Mechanic
86
1
13
922
Road Sweeper
75
4
21
923
Doctor
33
2
65
921
Computer Programmer
36
6
58
922
Chef
46
4
50
921
Fashion Designer
2
66
32
921
Percentage
breakdown of
Key stage 2
Primary school
pupils who
stated that
occupations
were for a man,
woman or both
Trajectory of occupational stereotyping
KS1
KS2
KS3
KS4
Post 16
It’s all down to coursework: impact of
changes in curriculum content and
assessment methods on differential
performance
Researchers who disagree about the educational merits and social
justice of new forms of assessment (Marks J, 2000; Ellwood J, 2000;
Murphy P; 1998) agreed that coursework and new curriculum
content in the national curriculum and in examinations have had a
positive effect on girls’ performance. However, the notion that ‘…it’s
all down to coursework…’ is not supported by way in which
enhanced girls’ performance has not been entirely in synch with
changes in assessment approaches:
English moved from being 100% coursework and over the period of
introduction of coursework and its reduction, the gender gap
continued to increase
Boaler, Murphy, William, Ellwood, Epstein,
Rudduck, Younger & Warrington
Girls do better in qualifications with coursework for a number of
reasons: they do well when they can discursively explore a subject;
they attend to all the pieces of work which contribute to the end
grade even if they only count for a small %, whereas boys place
greater status and emphasis on the ‘big bang’ of the exam – all the
small bits of diligence on the seemingly insignificant pieces of
coursework add up to a better overall exam grade for the girls
What can we do
Stand back and do nothing
One single thing
A complex mix which is monitored with sophistication
Boaler’s re-orientation of explanation
Mathematical equity – underachieving
boys or sacrificial girls?
Boaler J 1998
“….gender patterns are shifting, not because of a climate of boy
disadvantage, but because of a climate that is moving closer to
equality of opportunity, in which girls are being allowed to achieve. I
would therefore like to turn a popular media perspective on its head
and propose a history of male overachievement, gained at the
expense of the oppression of girls, that is now being replaced by a
more equitable system of opportunity in which the group that works
hardest and longest is allowed to achieve the greatest rewards…’
Effort
Motivation to understand
Boaler - continued
In Boaler’s carefully-designed study:
91% of girls regarded understanding as the most important aspect of
learning mathematics, compared with 65% of boys
4% of girls regarded remembering rules and methods as the most
important, compared with 24% of boys
5% of girls regarded getting a lot of work done as the most or second
most important aspect of learning mathematics, compared with 19%
of boys
Boaler - continued
Girls seeking deep understanding in order to progress, not
overcoming maladaptive tendencies through increased effort.
Pedagogy in maths attuned to boys – rapid pace, covering ground,
deriving scores.
Studiousness and scholarly interest being seen as feminine/nonmasculine traits.
Learning identity is crucial.
Closed textbook approach of school 1
Dominance of a culture of short term goals relating to speed and getting
correct answers
Large number of disaffected girls who were motivated and attained well
in other subjects
Many boys did not like maths but were willing to adapt to learning
culture.
Open task method school 2
High performance overall
Small number of disaffected boys who were also disruptive in other
subjects
Disaffected boys spread in end attainment relative to scores on entry
GCSE results % of entrants
School 1 – Closed textbook approach
Girls
Boys
9% A-C
20% A-C
77% A-G
76% A-G
(84% of cohort entered)
School 2 – Open task method
Girls
Boys
15% A-C
13% A-C
91% A-G
90% A-G
(94% of cohort entered)
Finding schools with a consistent record
in closing the gap
Younger M, Warrington M et al 2005
Couldn’t find the schools
Four classes of intervention strategies
Pedagogic – eg space and time to talk and reflect about reading
Individual – eg realistic and challenging target-setting
Organisational – eg selective use of single-sex teaching groups
Socio-cultural – eg paired reading schemes between yr3 and yr5 pupils
Their research ‘…does not support the view that there is a case for
boy-friendly pedagogies. Pedagogies which appeal to and engage
boys are equally girl-friendly. They characterise quality teaching, and
as such are just as suitable and desirable for girls as for boys…’
The importance of seeing the full life trajectories of
males and females
This is not a picture of the education system being solely
responsible in some way for the gender gap; it is more that social
and other stereotypes and pressures impact on education. This is
endorsed by the situation in the labour market, in adult learning and
in vocational qualifications; here, the whole situation reverses.