Gender in Computer Science

1. Gender in Computer Science

2. SIGCSE • SIGSCE is the Special Interest Group in Computer Science Education • I’ve just returned from the annual conference • A common theme, this year and every year, is attracting women to computer science--and keeping them • Many of these same comments apply to other minorities • I am very interested in this problem

3. What I can do • Not much :( • Most losses occur during the second year • I can give you: • some facts and figures • some research results • some opinions

4. Figures • Enrollment in computer science programs reached a peak in 1986, then declined until 1996 • There has been an upward trend from 1996 to 2000 • We don’t have figures past 2000 • In 1986, female enrollment reached a peak of 40% • During the period 1986 to 1996: • Men majoring in computer science dropped by 33% • Women majoring in computer science dropped by 55% • Other minorities also dropped by larger amounts than white males • Why?

5. Myths • Both men and women incorrectly believe that men in CS have higher GPAs than women • Fact: There is no difference in GPAs • Fact: In my MCIT program, there is no gender difference in GREs of admitted students • Women who succeed in CS are often viewed as “exceptional” • Fact: Women and men are equally capable • Both groups do equally well on assignments • Both groups do equally well on examinations • Fact: Women do not have to be “better than men” to succeed

6. Myths II • Myth: Some people just have a “computer gene” • Fact: From a biological standpoint, it’s obvious that there is no such thing • Fact: As with anything, there are individual differences in ability • It is commonly believed (among teachers) that anyone can be taught to program • Fact: If you work hard, you will succeed • No one is born with these skills • Fact: Many computer “hotshots” aren’t really very good • My belief: There is a positive feedback loop between enjoying an activity and being good at it

7. Myths III • Computer programming is for “loners” and is basically an antisocial (or at least nonsocial) activity • Fact: Prospective employers shun loners and look for people who work well with others • Fact: Large programs are group efforts • Fact: Most programming methodologies are about how to best organize the programming team • Fact: In an educational setting, we typically insist on individual effort, mostly in an attempt to grade fairly--but this does not reflect “real world” practice

8. Stereotypes • Stereotype: Computer science majors are intelligent but lack interpersonal skills • Fact: Like all stereotypes, there are individuals who fit the stereotype--but most do not • Stereotype: Successful computer science majors “don’t have a life” but spend all their time at the computer • Fact: Almost all computer scientists do have a life • Fact: However, CS majors do spend significantly more time on schoolwork than non-CS majors • In my personal experience: Obsessive programmers are less likely to succeed

9. Gender NON-differences • Research results show no significant differences between men and women in: • College GPA • ACT math, science, and composite scores • Interest in majoring in CS • Belief that CS is a worthwhile major • Number of hours per week spent on schoolwork • But: CS majors spend more time than non-majors • Age of first computer use • Knowledge of what CS is all about

10. More gender NON-differences • Estimate of how many hours computer scientists work • But: Differences in estimated compensation • Fact: Women are, on average, not as well paid as men • Fact: The difference is much less in the computer field • Importance placed on having a family • Belief that family life and career would be compatible for women • Stress level • Support and encouragement from others • Self esteem

11. Real gender differences • Research results show these statistically significant differences • Men have higher educational aspirations • Men value extrinsic rewards (e.g. money) more • Men are higher in aggressiveness and dominance • But: No difference in kindness or nurturing • Biggest difference: Men are more confident of their own ability

12. Especially interesting: High-scoring female CS students vs. low-scoring male non-CS students Confidence • Confidence in ability to write a computer program: • Students with high math ACT scores • Male CS majors: 63% • Male non-CS majors: 60% • Female CS majors: 48% • Female non-CS majors: 44% • Students with low math ACT scores • Male CS majors: 53% • Male non-CS majors: 49% • Female CS majors: 37% • Female non-CS majors: 34%

13. Why women drop out • According to one study, females suffer a loss of interest in the field, preceded by a loss of self-confidence • Probable causes of loss of confidence: • Inaccurate belief that women have lower ability • Lack of awareness of excellent income opportunities • Conflict between a woman’s view of herself and (inaccurate) stereotype of “computer nerds” • “Stereotype threat”: Fear of confirming the stereotype • Less playful and relaxed attitude toward computers

14. Factors undermining self confidence • (Note: These are opinions, not research results) • Computer science is hard--everyone has difficulty • Men are less willing than women to admit to having difficulties, hence often appear more capable than they really are • The field is wide as well as deep: “You’re a computer science major and you don’t know that?” • In programming, virtually all your mistakes are stupid ones--everyone’s mistakes are stupid ones--and it’s easy to mistake this for a personal failing

15. Interesting tidbits • Percentage of women earning a bachelor’s degree is significantly lower if the CS department is in the College of Engineering rather than in the College of Arts and Sciences • Under-representation of women in CS appears to be a cultural problem • Not true in historically black colleges and universities • Not true in Greece, Turkey, France, Italy • In one study, 30% of self-rated “code warriors” failed an assignment, compared to 15% of“code-a-phobes”

16. Conclusions • These studies suggest that women lose interest in computer science because of: • The mis-perception that they are not as capable as other (especially male) students • The (accurate) perception that they do not conform to the (mostly inaccurate) stereotype of computer “nerds” • The foregoing is presented in the hope that having some actual information on gender differences will help some of you in your college careers

17. The End