13-Jun-15 Gender in Computer Science

SIGCSE SIGSCE is the Special Interest Group in Computer Science Education I attend the SIGCSE annual conference each year A common theme, this year and every year, is attracting women to computer science—and keeping them There was very little new this year, so I’m just using last year’s slides (with minor modifications) Many of these same comments apply to other minorities I am very interested in this problem

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

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 good figures past 2000, but the trend is downward again At this university, the trend is definitely downward 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?

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

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

Myths III Myth: 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

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

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 But: Males generally have more access to computers Knowledge of what CS is all about

More gender NON-differences Estimate of how many hours computer scientists work But: There are 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 than in most other, non-technical fields 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

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

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% Especially interesting: High-scoring female CS students vs. low-scoring male non-CS students

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

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

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”

Job prospects The information sector has the second highest projected job growth rate. Publishing, the Internet, and telecommunications should see real output climb to $1.6 trillion by A fifth of this will be Internet-related. With real growth in the information services sector targeted to be "an aggressive 8.5 average annual percent," this part of the economy can anticipate a jobs boom. If you're technologically-inclined, your career prospects are bright. The highest projected job growth rate is “home health aide” New data show students' interest in the discipline is in a free fall. The number of newly declared computer-science majors declined 32 percent from the fall of 2000 to the fall of 2004, according to a report released this month by the Computing Research Association, which represents computer scientists in industry and academe. Another survey, from the Higher Education Research Institute at the University of California at Los Angeles, shows that the number of incoming freshmen who expressed an interest in majoring in computer science has plummeted by 59 percent in the last four years.

Conclusions These studies suggest that women lose interest in computer science because of: The misperception that they are not as capable as other (especially male) students The misperception that job prospects are declining 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

One more thing... This is a bit of personal advice, based on anecdotal evidence, rather than on research results: If you are a woman, you are likely to have a much harder time if you are the first and only woman in their research or IT department Mostly for guys: If you think men are inherently better at computer stuff than women, get over it If a woman joins the company where you work, do not assume it is her job to make the coffee

The End The scientists measured the size and strength of claws of both male and female crayfish, and then monitored how they performed in competitive bouts. They found crayfish use claw size to determine the winners of the most aggressive disputes. For female crayfish the size of the claw was an honest indication of how strong they were. However, claw size of males was not a good indicator of their strength. Males were routinely bluffing their opponents with weak claws to achieve dominance. They used claws more for intimidation than actual strength. --