|I'M A STRANGER HERE MYSELF: A CONSIDERATION OF WOMEN IN COMPUTING
by Janet Cottrell
Computing and Information Technology
238 Waterman Building
The University of Vermont
Burlington, VT 05405-0160
Permission to copy without fee all or part of this material is
granted provided that the copies are not made or distributed for
direct commercial advantage the ACM copyright notice and the title
of the publication and its date appear, and notice is given that
copying is by permission of the Association for Computing
Machinery. To copy otherwise or to republish requires a fee and /or
specific permission. Copyright 1992 ACM.
Look at the faces of the students who use the public computing
areas at your school, and you will probably see a fairly even mix
of males and females. Looking around at your colleagues in user
services, you may see a similar mix. But poll the faculty of your
school's Computer Science or Engineering departments, and you are
likely to find few, if any, women.
In the U.S. in recent years, women earned about half of all
associate degrees in computer science, more than one-third of the
bachelor's degrees, 27% of master's degrees, and 13% of PhDs
(Spertus, 1991; Chronicle, 1992). Yet women account for only about
7% of computer science and engineering faculty, and only 3% of the
tenured professors in these fields are female (Spertus, 1991). In
other words, 92% of CS and engineering faculty -- and 97% of the
tenured faculty -- are male. And about one-third of the computer
science departments polled employ no women faculty at all. (Note 1)
What happens between undergraduate classes and final career choice?
Why are women so underrepresented among computing and engineering
faculty? And why should we in user services be concerned?
Many explanations have been put forward to account for these
discrepancies, including aptitude and expectancy, cultural factors,
lack of institutional support, and outright discrimination.
Although definitive conclusions may be beyond the scope of this
paper, it is certainly worthwhile to review the evidence on each of
these counts and examine some possible courses of action.
Aptitude and Expectancy
One of the most frequently espoused explanations for the paucity of
women in "hard" computing professions is the alleged prevalence
math anxiety and mathematical ineptitude in females. This belief
originated in studies from the 1970s indicating that boys
outperformed girls on tests of mathematical ability. Early in the
1980s, however, these same data were reexamined with startling
results: when other variables such as course experience were
factored out, gender accounted for only l% of the variance in
mathematical ability. The apparent sex differences in math ability
actually reflected differences in the number and type of math
courses taken prior to testing. Later studies confirmed this: once
math experience is partialled out, most of the sex differences
disappear. (For a review of this literature, see Clarke, 1992 or
Hornig, 1984.) And indeed, math grade point averages for boys and
girls are virtually identical (Klein, 1992).
There are differences, however, in the way students perceive their
own math and computer science abilities, with females generally
having less self-confidence and more anxiety about their skills.
This lack of confidence in young women is very specific to
themselves as individuals: they don't attribute their perceived
lack of skill to being female; rather they see it as an individual
inability or disinterest. In others words, they feel that women in
general are capable, but they are not (Kramer & Lehman, 1990). When
asked why they do not perform well in math, women cited low ability
and discouragement by others as the main reasons (Klein, 1992 ).
There appears to be some basis for this sense of being discouraged
by others. As Clarke (1992) summarizes, self-reports by teachers
show no sex differences in student computer use in class. But
students' reports and independent observations show that teachers
are more likely to call on boys to answer questions or use
computers, they respond more quickly to requests from boys, and
they are more likely to take over and complete a task in response
to girls' questions. This is not to imply that the teachers'
behavior is deliberate; in fact, it is almost certainly
unconscious. Klein (1992) reinforces these findings by citing a
study noting that boys received no negative feedback in any
activity during math lessons while girls received rather a lot.
These cases illustrate the point that low self-confidence in
females must not be confused with limited abilities.
In addition to debunking the myth that girls aren't as good as boys
at math and computing, another assumption must be examined here.
This is the strongly-held belief that computers are closely linked
to mathematics. Actually, Clarke (1992) argues, "computers are not
inherently mathematical. In fact, most work with computers involves
manipulation of information and communication with people, which
relies as much on verbal and interpersonal skills as on
mathematical abilities... For example, the primary role of a
systems analyst is to enter an organization, find out about its
organizational needs, and design a computing system that will meet
those needs." (page 72.) She continues, "To be a highly
sophisticated user, it is not essential to be a technician." (page
Bernstein (1992) takes this a step further and advocates that in
order to attract women, introductory computer science classes ought
to concentrate on applications rather than on math or programming.
"While men may be passionate about computers, women use computers
to solve problems," she writes. "When women fail to see indications
that computers are efficient tools, they may lose interest.
However, when men and women use computers as tools to solve
problems, both groups perform equally well and like using computers
equally." (page 87.) A discussion about whether this is "really"
computer science is beyond the scope of this paper, but interested
readers may consult Bernstein (1992) and Frenkel (1990). (Note 2)
Some authors suggest that computers tend to be associated with
surroundings or attitudes that women may find uncomfortable or
foreign. Kiesler, et al (1985) describe this as an alien culture
for girls, a culture that makes them less likely to get involved in
the new technology:
Even in preschool, males dominate the school computers.
In one preschool, the boys literally took over the
computer, creating a computer club and refusing to let
the girls either join the computer club or have access to
the computer. As a result, the girls spent very little
time on the computer. When the teachers intervened and
set up a time schedule for sharing computer access, the
girls spent as much time on the computer as the boys....
Apparently, girls can enjoy the computer and do like to
use it, but not if they have to fight with boys in order
to get a turn. (page 254)
Computer games tend to perpetuate the competitive image of
computing, with themes of wars, battles, crimes, destruction, and
male-oriented sports. When Kiesler et al examined the covers of
computer games in a typical store, they found 28 men and 4 women
illustrated there. As they rather wryly note, "The women were on
the covers of Monopoly (2 men and 2 women playing the game), Palace
in Thunderland ( 1 very fat queen), and Wizard and the Princess (l
wizard standing, 1 princess in supplicating position on floor)."
Educational software is not immune from gender bias. When a group
of educators with software design experience was asked to design
software specifically for boys or for girls, they tended to design
learning tools for the girls and games for the boys. When they were
asked to design software for generic "students," they again
designed games -- exactly as though the students were boys (Huff
and Cooper, 1987).
And when students are made to use software designed for the
opposite gender, interesting results occur: the students report
more stress than when using gender-appropriate software, but only
when the gender-inappropriate software is used in public settings.
Thus, the presence of an audience affects stress levels (Huff,
Fleming, and Cooper, 1992).
In fact, additional research reviewed by Huff et al indicates that
women report higher levels of situational stress and perform less
well in the presence of another person than when they do the same
task in private. In direct contrast to this, men perform better and
report less stress when they perform in public rather than in
private. Both of these effects occur only in novice computer users;
experts were unaffected by the presence of other persons. Further
research indicates that these results are closely linked to
expectancy: when users expect to succeed, they perform better in
public than in private. When they expect to fail, they perform
worse in public.
Although many of the situations described here apply primarily to
children or novice students, similar factors affect girls and women
of all ages. Indeed, a study of PhD students in a world-renowned
computer science department (CMU, as a matter of fact), found that
male and female students performed equally well, but the women
reported feeling much less comfortable, confident, and successful
than did the men (Burton, 1987, as reported in Pearl, et al, 1990).
It seems likely that cultural factors like those described here may
be in part responsible for this difference .
The use of pornographic images as background screens on computers
in offices and public labs, for example, is likely to be perceived
much differently by women than by the men displaying the images.
Constructive responses to situations like this are possible (as
described in CMU, 1989), and indeed laudable -- but the need to
confront such situations bound to affect one's perception of the
educational or work experience. (Note 3)
And with the shortage of female role models in academic computer
science, there are few women to provide tips on dealing with the
cultural and sociological barriers (Clarke, 1992). Research tells
us that this lack of role modeling affects female graduate
students' satisfaction (Gilbert et al, 1983); common sense tells us
that it affects younger students and women in the workforce as
well. "Ultimately," Pearl et al ( 1990) conclude, "everything
hinges on increasing the number of women in the field." (page 56)
Nonsupport and outright discrimination
As Spertus (1991) emphasizes, "for the most part, people are not
consciously trying to discourage women from science and
engineering. Instead, people's behavior is often subconsciously
influenced by stereotypes that they may not even realize they
have....While perhaps it is comforting to know that no conspiracy
exists against female computer scientists, it also means that the
problem is harder to fight. The negative influences are ... varied
and decentralized." (page 75)
"Varied and decentralized" though they may be, some of these
influences are indicative of the nature of the institutions in
which they exist. If a school does nothing to deter patronizing or
suggestive behavior, that behavior appears to be countenanced. If
a school does nothing to provide a supportive environment for
women, it may in fact appear hostile to them.
This, in addition to the expectancy and cultural factors described
above, further examples of negative influences may include:
* invisibility, where women in educational or professional
settings may be ignored, interrupted, not looked in the eye, or
simply not consulted for professional opinions.
* patronizing behavior, including "talking down" to women,
over tasks they have started, or extravagantly praising their
* suggestive or obscene behavior that is unwelcome or viewed as
inappropriate by the woman to whom it is directed.
Sandler (1986), Frenkel (1990), and Spertus (1991) all provide
numerous examples of such behavior. Most women in technological
settings can probably provide their own.
Sometimes, negative influences in an institution may cross the line
from offensive-but-non-actionable to outright harassment or
discrimination. Even within the last decade, cases have been
reported of women's grad school applications being tossed on a
corner table (Hornig, 1984) or of women being told by the planner
of a university-sponsored summer technical meeting that the host
would prefer female attendees to wear two-piece swimsuits (MIT,
1983). For examples of merit-based promotion problems, see Spertus
(1991). Whether unintentional, deliberately offensive, or downright
illegal, influences like these may combine so that "women
administrators, faculty, and graduate students face a chillier
professional climate than their male colleagues. " (Sandler, 1986)
Other difficulties may be more closely tied to the structure and
operation of the institution itself. In academia, for example, the
tenure track often poses conflicts for women with, or planning to
have, children. In fields where there are few women support and
understanding during this time are often not forthcoming, and
efforts to balance professional and domestic responsibilities may
be resented. Employer-provided child care and parental leave
policies may help ease the problem, but as Pearl et al (1990)
emphasize, tenure tracking often assumes a "helpmate-in-the-
background" model of life which is inappropriate for today's
Finally, there is the bottom-line question of financial
compensation. Women in programming tend to be better paid than
women in other occupations, and there is less income inequality in
programming: female programmers earn about 70% of their male
counterparts' wages, compared to women in other occupations, who
earn about 62% as much as their male counterparts do. However,
women in highly-paid and specialized computing jobs (including
management) earn less relative to men than those in lower-paid
To some extent, women's lower pay can be accounted for by lower
educational level, fewer years of experience, and other variables.
A study based on 1980 Census Bureau data found that women computer
specialists earn only 72% as much as their male counterparts, with
an average difference of $6,450. Variables other than sex can be
factored out mathematically, accounting for 40% of the difference
in wages. But 60% of the wage gap in this study cannot be explained
by factors other than gender (Donato and Roos, 1987). Part of the
remaining wage gap may be attributable to differences in
occupational category not defined in the study, but the remainder
is attributable to differences in the way women and men are
compensated for equal levels of education, experience, and other
variables. "This part of the gap, often labeled discrimination, is
more difficult to change," the authors note with wonderful
insouciance. "Changing it relies not on the characteristics of
individual workers, but on altering the way labor market
institutions reward workers. Such changes must be accomplished
before the computer field offers women opportunities equal to
men's." (p. 312)
I take it for granted, as Spertus (1991) says, that readers
consider harassment and discrimination to be offensive and harmful,
so I will not belabor these points.
In addition to whatever moral or legal stands we might wish to
assume, there are other reasons for concern. The declining student
population means that total enrollment in science and engineering
will drop dramatically. Unlikely though it may seem in these
recessionary times, the demand for trained professionals will
increase in time, certainly within the next decade, and it makes no
sense to exclude, or at least discourage, half the population of
prospective applicants. (Hornig, 1984; Frenkel, 1990, Pearl et al,
Furthermore, as discussed in the section on Aptitude and
Expectancy, it is possible that women may bring with them specific
skills and approaches that actually enhance the field of computing.
Ought not these skills be welcomed? After all, as Frenkel (1990)
notes, "The field is young and flexible enough to modify itself."
WHERE DO WE GO FROM HERE?
The research cited here has implications for those of us working in
user services. Some are specifically related to computer services,
others are applicable at the institutional level.
As you consider how this research might apply to computer labs,
software support, and other aspects of user services, consider the
following questions and ideas:
* Are your computing facilities physically safe? Are the walkways,
entrances, and facilities themselves well-lit? Is a phone
available? Can your campus provide a secure escort service for
those frequently-required late-night programming sessions?
* Are women well-represented in your student and permanent
consulting staff? When a women enters the facility, will she
quickly see that other women are frequently present?
* Are women who ask questions in the lab answered with the same
level of professionalism as men are?
* Are pornographic images ever used as background screens on
computers in offices or public labs? Do you have any policies about
* Are the public labs so crowded that students must frequently
compete for computer time? If so, are any time-limits imposed, or
does the most aggressive student get the next available computer?
* Are self-paced online or video training tools available? Can a
student who may be uncomfortable in a large class find
individualized learning resources?
As you consider wider application of this research to your college
or university as a whole, keep in mind the recommendations from
Pearl et al (1990) reprinted elsewhere in this article. Some of
these ideas may be outside your own sphere of influence, but many
-- including outreach programs, mentoring, and increased awareness
-- can be started on some scale in your own department.
Keep your eyes and ears open. To read more about some of the issues
described here, try the two articles (Frenkel, 1990 and Pearl et
al, 1990) included in the special November, 1990 issue of the
Communications of the ACM on Women and Computing, or the MIT report
by Spertus (1991) available through anonymous FTP. Listen to the
stories of your colleagues and friends, your children and their
Finally, remember the closing advice of Frenkel's CACM article: If
the issues discussed here are not addressed, everyone stands to
lose. The profession could find itself asking uncomfortable
questions too late in the game. As it is, one wonders how many
ideas that could have been contributed by female talent will never
surface to enrich academic computer science. More broadly, what are
the repercussions to our increasingly computer-oriented society, if
women -- about half the population and professional workforce --
are not as prepared in this discipline as are men? Perhaps we will
not have to find out. (Frenkel, 1990, page 45.)
1. By comparison, women earned about half of the bachelor's and
master's degrees and about 36% of the doctorates conferred in all
fields in 1989-90. Over all disciplines, about 73% of faculty
members are male, about 27% are female. (Chronicle, 1992)
2. This interpretation of computer as tools, along with the
reliance on organizational and communication skills, may help
account for the number of women in user services.
3. The term "pornographic" is used here is a very loose sense.
images which most of us would be unwilling to label pornographic
might still be inappropriate as background screens. The questions
of what is pornographic (or inappropriate) and who decides what is
pornographic (or inappropriate) are central to policy formation,
but are, as they say, beyond the scope of this paper.
Bernstein, Danielle R. 1992. A new introduction to computer
science. In Search of Gender Free Paradigms for Computer Science
Education, edited by C. Dianne Martin and Eric Murchie-Beyma.
Eugene OR: International Society for Technology in Education.
Burton, M. D. 1987. Gender differences in professional
socialization: A study of women and men becoming computer
scientists. Tech Report, Carnegie-Mellon University, Pittsburgh,
PA, June 1987. Committee on Social Science Research in Computing,
Social and Decision Sciences Department.
Chronicle, 1992. The Chronicle of Higher Education Almanac, Vol.
XXXIX, No. 1, August 26,1992.
Clarke, Valerie. 1992. Strategies for involving girls in computer
science. In Search of Gender Free Paradigms for Computer Science
Education, edited by C. Dianne Martin and Eric Murchie-Beyma.
Eugene OR: International Society for Technology in Education .
CMU Computer Science Graduate Students and Staff, 1989. Dealing
with pornography in Academia: Report on a Grassroots action. July
Donato, Katharine and Roos, Patricia. 1987. Gender and earnings
inequality among computer specialists. In Women, Work, and
Technology, edited by Barbara Drygulski Wright, et al. Ann Arbor:
The University of Michigan Press.
Frenkel, Karen A. 1990. Women & Computing. Communications of the
ACM 33(11): 34-46.
Gilbert, Lucia; Gallessich, June; and Evans, Sherri. 1983. Sex of
faculty role model and students self-perceptions of competency. Sex
Roles 9(5): 597-607. Hornig, Lilli S. 1984. Women in Science and
Engineering: Why so few? Technology Review, November/December,
Huff, Charles and Cooper, Joel. 1987. Sex bias in educational
software: The effect of designers' stereotypes on the software they
design. Journal of Applied Social Psychology 17 (6); 519-532.
Huff, Charles W., Fleming, John H.; and Cooper Joel. 1992. Gender
differences in human-computer interaction. In Search of Gender Free
Paradigms for Computer Science Education, edited by C. Dianne
Martin and Eric Murchie-Beyma. Eugene OR: International Society for
Technology in Education.
Kiesler, Sara; Sproull, Lee; and Eccles, Jacquelynne. 1985. Pool
halls, chips, and war games: Women in the culture of computing.
Psychology of Women Quarterly 9: 451-462.
Klein, Lesley. 1992. Female students' underachievement in computer
science and mathematics: Reasons and recommendations. In Search of
Gender Free Paradigms for Computer Science Education, edited by C.
Dianne Martin and Eric Murchie-Beyma. Eugene OR: International
Society for Technology in Education.
Kramer, Pamela E. and Lehman, Sheila. 1990. Mismeasuring Women: A
critique of research on computer ability and avoidance. Signs:
Journal of Women in Culture and Society 16 (11):158-172. Autumn,
MIT, 1983. Barriers to Equality in Academia: Women in Computer
Science at MIT. Feb. 1983. The Laboratory for Computer Science and
The Artificial Intelligence Laboratory,
Pearl, Amy; Pollack, Martha; Riskin, Eve; Thomas, Becky; Wolf,
Elizabeth; and Wu, Alice. 1990. Becoming a computer scientist.
Communications of the ACM 33(11): 47-57.
Sandler, Bernice R. 1986. The Campus Climate Revisited: Chilly for
Women Faculty, Administrators, and Graduate Students. A publication
of the Project on the Status and Education of Women, Association of
American Colleges, 1818 R. St. NW, Washington, DC.
Spertus, Ellen. 1991. Why are There So Few Female Computer
Scientists? Cambridge, MA: MIT Artificial Intelligence Laboratory.
Available via anonymous FTP from ftp.ai.mit.edu, as womcs*.ps in
the pub/ellens directory.