The Gender Gap in STEM: The Unique Case of Computer Science · The Gender Gap in STEM: The Unique...
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The Gender Gap in STEM: The Unique Case of Computer Science Linda J. Sax UCLA
Transcript of The Gender Gap in STEM: The Unique Case of Computer Science · The Gender Gap in STEM: The Unique...
The Gender Gap in STEM: The Unique Case of Computer Science
Linda J. Sax
UCLA
Overview of Two STEM Projects
Gender Trends in STEM: 1971-2011
BRAID Initiative to Study Diversity in Computer Science
Total Enrollment in Colleges and
Universities (1966-2013)
0
2
4
6
8
10
12
1419
66
196
819
7019
7219
7419
7619
7819
80
198
219
84
198
619
88
199
019
92
199
419
96
199
820
00
200
220
04
200
620
08
2010
2012
Mill
ion
s
Women
Men
Source: National Center for Education Statistics, 2015
Women Overrepresented Across All Fields, but Underrepresented in STEM
57
35
43
65
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
All Bachelor's Degree Recipients STEM Bachelor's Degree Recipients
Proportions of Bachelor’s Degree Recipients, by Gender
Women MenSource: National Center for Education Statistics, Digest of Education Statistics, 2011
Explanations for the Gender Gap in STEM
Educational Settings
Forces Beyond the Classroom
Educational Settings
Women begin to opt out of STEM courses in middle and high school Women underrepresented in AP courses in STEM
(Calculus, Physics, Chemistry, Computer Science)
Unwelcome climate in many college STEM majors Large lecture halls, grading on a curve
Underrepresentation of women = Less opportunity for female friendship groups in STEM
Teachers/Faculty More traditional teaching practices (emphasis on lecturing, not student-
centered methods)
Faculty seen as intimidating (more impactful for female students)
Lack of female role models and mentors in STEM
Forces Beyond the Classroom
Sense of belonging in STEM Science perceived as masculine domain by students and parents
Science careers perceived as competitive, unwelcoming and difficult to balance work-family
Societal benefits matter, but not clearly understood
Women’s Lower Self-confidence (% rating “above average” or “highest 10%” in 2011):
Computer abilities (47.4% of men, 30.3% of women)
Math abilities (55.6% of men, 36.1% of women)
Enduring Gender Gap in Self-Rated Mathematical Ability
(% Above Average or Highest 10%)
0%
10%
20%
30%
40%
50%
60%
19
71
19
73
19
75
19
77
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79
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99
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01
20
03
20
05
20
07
20
09
20
11
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
How Has the Gender Gap in STEM Changed Over Time?
31.9
29.1
32.6
28.0
36.6
12.7 11.0
15.8 14.4
20.0
0
5
10
15
20
25
30
35
40
1976 1986 1996 2006 2011
Proportion of Students Intending to Major in STEM, by Gender
Men Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Gender Gap Narrows…Then Widens
-19.2 -18.1
-16.8
-13.6
-16.6
-25
-20
-15
-10
-5
0
1976 1986 1996 2006 2011
Difference in Men’s and Women’s Intention to Major in STEM
Proportion of Women-Men
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Need to Consider Differences Across STEM Fields
Computer Science
Biological Sciences
Math
Engineering Physical Sciences
Women’s Relative Representation in STEM Varies by Field
58 43 39
18 18
42 57 61
82 82
0%
20%
40%
60%
80%
100%
Biological Sciences Mathematics/Statistics Physical Sciences Engineering Computer Science
Proportions of Bachelor’s Degree Recipients, by Gender (2014)
Women Men
Source: National Center for Education Statistics, Digest of Education Statistics, 2015
Biological Sciences Gender Gap Reversal
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
11%
12%
13%
14%
15%
19
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79
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20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Math/Statistics No Gender Gap
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
11%
12%
13%
14%
15%
19
71
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19
73
19
74
19
75
19
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77
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79
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20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Physical Sciences Diminished Gender Gap
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
11%
12%
13%
14%
15%
19
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99
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20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Engineering Stable(ish) Gender Gap
0%
5%
10%
15%
20%
25%
19
71
19
72
19
73
19
74
19
75
19
76
19
77
19
78
19
79
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80
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01
20
02
20
03
20
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20
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20
06
20
07
20
08
20
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20
11
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Computer Science Fluctuating Gender Gap
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
11%
12%
13%
14%
15%
19
71
19
72
19
73
19
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76
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77
19
78
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79
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02
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05
20
06
20
07
20
08
20
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20
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20
11
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Proportion of Prospective Computer Science Majors who are Female (1971-2011)
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
1971
1972
1973
1974
1975
1976
1977
1978
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200
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2010
2011
Women as % of all Computer Science Majors
Global demand for individuals with computer science training
(valuable in any field)
Computer-related careers among the fastest growing and
highest paying occupations
Number of colleges offering a CS degree has grown from 123 to
600 in past forty years
Women remain vastly underrepresented in CS occupations
Women only 20% of software developers = women’s voices not
reflected in many emerging technologies
Why Focus on Computer Science?
In order to attract more women to CS, we need to better understand female CS majors
How do they differ from male computer science majors?
How do they differ from women in other STEM fields?
How have they changed over the past four decades?
NSF-Funded Research (HRD #1135727)
CIRP Freshman Survey Over 8 million students entering over 1,000
baccalaureate institutions
Focuses on 5 STEM fields: Biological sciences, Computer Science, Engineering, Math/statistics, Physical Sciences
Analyzes female and male STEM majors over the past 40 years (1971-2011)
Data Source
Data Source: CIRP Freshman Survey Over 8 million students entering over 1,000
baccalaureate institutions between 1971-2011 Key comparison groups
54,845 women and 149,766 men planning to major in CS More than 1.7 million students planning to major in biological
sciences, physical sciences, math/stats, and engineering
Summary of findings in: Background traits Self-ratings Community orientation Career aspirations
Methods
Key Findings: Background Traits
Racial/Ethnic Distribution of Female Computer Science Majors (1971-2011)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
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19
93
19
95
19
97
19
99
20
01
20
03
20
05
20
07
20
09
20
11
White
Asian
Black
Hispanic
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Percentage of CS Bachelor’s Degree Earners who are Female, by Race/Ethnicity
15.3%
17.9%
20.6% 21.8%
26.9%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
White Hispanic American Indian Asian Black
% Female
Median Family Income (1971-2011) (In 2011 Dollars)
$0
$20,000
$40,000
$60,000
$80,000
$100,000
$120,000
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
20
07
20
09
20
11
Women in STEM
Women in CS
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
A+/A High School GPA, by Field and Gender (2011)
0.0
10.0
20.0
30.0
40.0
50.0
60.0
All CS Biology Phys Eng Math
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Women Averaging A+, A, or A- Grades in High School
(1971-2011)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
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20
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Women in STEM
Women in CS
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Key Findings: Self-Ratings
Self-Rating Academic Ability (2011) (% Indicating “Highest 10%”)
0.0
10.0
20.0
30.0
40.0
50.0
60.0
All CS Biology Phys Eng Math
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Self-Rating Intellectual Self-Confidence (2011) (% Indicating “Highest 10%”)
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
CS All Math Biology Phys Eng
Men
Women
Self-Rating Leadership Ability (2011) (% Indicating “Above Average” or “Highest 10%”)
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
CS Math Biology All Phys Eng
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Self-Rating Drive to Achieve (2011) (% Indicating “Above Average” or “Highest 10%”)
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
CS All Phys Math Biology Eng
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Self-Rating Emotional Health (2011) (% Indicating “Above Average” or “Highest 10%”)
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
CS Phys All Math Eng Biology
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Women’s Self-Rating Emotional Health (1985-2011) (% Indicating “Highest 10%” or “Above Average”)
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
19
85
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86
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87
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Women in STEM
Women in CS
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Self-Rating Physical Health (2011) (% Indicating “Above Average” or “Highest 10%”)
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
CS All Math Phys Biology Eng
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Women’s Self-Rating Physical Health (1985-2011) (% Indicating “Above Average” or “Highest 10%”)
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
19
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Women in STEM
Women in CS
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Self-Rating Artistic Ability (2011) (% Indicating “Highest 10%”)
0.0
2.0
4.0
6.0
8.0
10.0
12.0
Math Biology Phys Eng All CS
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Women’s Self-Rating Artistic Ability (1971-2011) (% Indicating “Highest 10%”)
0%
2%
4%
6%
8%
10%
12%
19
71
19
73
19
75
19
77
19
79
19
81
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87
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Women in STEM
Women in CS
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Key Findings: Community Orientation
Goal: Become a Community Leader (2011) (% Indicating “Essential” or “Very Important”)
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
CS Math Phys Eng Biology All
Men
Women
Goal: Become Involved in Environmental Programs (2011)
(% Indicating “Essential” or “Very Important”)
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
45.0
Math CS All Phys Eng Biology
Men
Women
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
Will Participate in Community Service or Volunteer Work (2011)
(% Indicating “Very Good Chance”)
0.0
10.0
20.0
30.0
40.0
50.0
60.0
CS All Phys Eng Math Biology
Men
Women
Key Findings: Career Aspirations
Career Aspirations of Male and Female CS Majors
21 15
11 9
68 76
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
CS Women CS Men
Other Career Undecided Career Computer Programmer
Proportion of Entering Female CS Majors Who Aspire to be Computer Programmers (1971-2011)
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
19
71
19
73
19
75
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77
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79
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83
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Women in STEM
Women in CS
Proportion of Entering Female CS Majors Who Are Undecided about their Career Aspirations
(1971-2011)
Source: Cooperative Institutional Research Program Freshman Survey, Higher Education Research Institute, UCLA
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
19
71
19
73
19
75
19
77
19
79
19
81
19
83
19
85
19
87
19
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19
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05
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07
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09
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Women in STEM
Women in CS
CS tends to attract women who… Have low ratings of their emotional and physical health
Need to understand which comes first (Chicken-egg phenomenon)
Are less committed to serving communities
How to rebrand CS to emphasize impact on society?
Are increasingly creative and artistic
Do these women stay in CS and what do they do?
Not necessarily planning on careers as programmers
What happens to these career plans over time?
Conclusion and Implications
Next Steps…
Examines strategies to promote gender and racial/ethnic diversity in undergraduate computing
Revamp intro courses
Promote interdisciplinary CS
Build community
K-12 outreach
$2.3 million in research funding
National Science Foundation, the Anita Borg Institute , Google, Facebook, Microsoft, Intel, and the Computing Research Association
Mixed-methods study:
Five-year longitudinal study of students taking introductory CS courses nationwide
Surveys of computer science faculty
Interviews with department chairs
