This sessions was dedicated to the very important issues of gender and diversity. The opening talk in this session was “A Historical Examination of the Social Factors Affecting Female Participation in Computing”, presented by Elizabeth Patitsas (@patitsel). This paper was a literature review of the history of the social factors affecting the old professional association of the word “computer” with female arithmeticians to today’s very male computing culture. The review spanned 73 papers, 5 books, 2 PhD theses and a Computing Educators Oral History project. The mix of sources was pretty diverse. The two big caveats were that it only looked at North America (which means that the sources tend to focus on Research Intensive universities and white people) and that this is a big picture talk, looking at social forces rather than individual experiences. This means that, of course, individuals may have had different experiences.
The story begins in the 19th Century, when computer was a job and this was someone who did computations, for scientists, labs, or for government. Even after first wave feminism, female education wasn’t universally available and the women in education tended to be women of privilege. After the end of the 19th century, women started to enter traditional universities to attempt to study PhDs (although often receiving a Bachelors for this work) but had few job opportunities on graduation, except teaching or being a computer. Whatever work was undertaken was inherently short-term as women were expected to leave the work force on marriage, to focus on motherhood.
During the early 20th Century, quantitative work was seen to be feminine and qualitative work required the rigour of a man – things have changed in perceptions, haven’t they! The women’s work was grunt work: calculating, microscopy. Then there’s men’s work: designing and analysing. The Wars of the 20th Century changed this by removing men and women stepping into the roles of men. Notably, women were stereotyped as being better coders in this role because of their computer background. Coding was clerical, performed by a woman under the direction of a male supervisor. This became male typed over time. As programming became more developed over the 50s and 60s and the perception of it as a dark art started to form a culture of asociality. Random hiring processes started to hurt female participation, because if you are hiring anyone then (quitting the speaker) if you could hire a man, why hire a woman? (Sound of grinding teeth from across the auditorium as we’re all being reminded of stupid thinking, presented very well for our examination by Elizabeth.)
CS itself stared being taught elsewhere but became its own school-discipline in the 60s and 70s, with enrolment and graduation of women matching that of physics very closely. The development of the PC and its adoption in the 80s changed CS enrolments in the 80s and CS1 became a weeder course to keep the ‘under qualified’ from going on to further studies in Computer Science. This then led to fewer non-traditional CS students, especially women, as simple changes like requiring mathematics immediately restricted people without full access to high quality education at school level.
In the 90s, we all went mad and developed hacker culture based around the gamer culture, which we already know has had a strongly negative impact on female participation – let’s face it, you don’t want to be considered part of a club that you don’t like and goes to effort to say it doesn’t welcome you. This led to some serious organisation of women’s groups in CS: Anita Borg Institute, CRA-W and the Grace Hopper Celebration.
Enrolments kept cycling. We say an enrolment boom and bust (including greater percentage of women) that matched the dot-com bubble. At the peak, female enrolment got as high as 30% and female faculty also increased. More women in academia corresponded to more investigation of the representation of women in Computer Science. It took quite a long time to get serious discussions and evidence identifying how systematic the under-representation is.
Over these different decades, women had very different experiences. The first generation had a perception that they had to give up family, be tough cookies and had a pretty horrible experience. The second generation of STEM, in 80s/90s, had female classmates and wanted to be in science AND to have families. However, first generation advisers were often very harsh on their second generation mentees as their experiences were so dissimilar. The second generation in CS doesn’t match neatly that of science and biology due to the cycles and the negative nerd perception is far, far stronger for CS than other disciplines.
Now to the third generation, starting in the 00s, outperforming their male peers in many cases and entering a University with female role models. They also share household duties with their partners, even when both are working and family are involved, which is a pretty radical change in the right direction.
If you’re running a mentoring program for incoming women, their experience may be very. very different from those of the staff that you have to mentor them. Finally, learning from history is essential. We are seeing more students coming in than, for a number of reasons, we may be able to teach. How will we handle increasing enrolments without putting on restrictions that disproportionately hurt our under-represented groups? We have to accept that most of our restrictions actually don’t apply in a uniform sense and that this cannot be allowed to continue. It’s wrong to get your restrictions in enrolment at a greater expense on one group when there’s no good reason to attack one group over another.
One of the things mentioned is that if you ask people to do something because of they are from group X, and make this clear, then they are less likely to get involved. Important note: don’t ask women to do something because they’re women, even if you have the intention to address under-representation.
The second paper, “Cultural Appropriation of Computational Thinking Acquisition Research: Seeding Fields of Diversity”, presented by Martha Serra, who is from Brazil and good luck to them in the World Cup tonight! Brazil adapted scalable game design to local educational needs, with the development of a web-ased system “PoliFacets”, seeding the reflection of IT and Educational researchers.
Brazil is the B in BRICS, with nearly 200 million people and the 5th largest country in the World. Bigger than Australia! (But we try harder.) Brazil is very regionally diverse: rain forest, wetlands, drought, poverty, Megacities, industry, agriculture and, unsurprisingly, it’s very hard to deal with such diversity. 80% of youth population failed to complete basic education. Only 26% of the adult population reach full functional literacy. (My jaw just dropped.)
Scalable Game Design (SGD) is a program from the University of Colorado in Boulder, to motivate all students in Computer Science through game design. The approach uses AgentSheets and AgentsCubes as visual programming environments. (The image shown was of a very visual programming language that seemed reminiscent of Scratch, not surprising as it is accepted that Scratch picked up some characteristics from AgentSheets.)
The SGD program started as an after-school program in 2010 with a public middle school, using a Geography teacher as the program leader. In the following year, with the same school, a 12-week program ran with a Biology teacher in charge. Some of the students who had done it before had, unfortunately, forgotten things by the next year. The next year, a workshop for teachers was introduced and the PoliFacets site. The next year introduced more schools, with the first school now considered autonomous, and the teacher workshops were continued. Overall, a very positive development of sustainable change.
Learners need stimulation but teachers need training if we’re going to introduce technology – very similar to what we learned in our experience with digital technologies.
The PolFacets systems is a live documentation web-based system used to assist with the process. Live demo not available as the Brazilian corner of internet seems to be full of football. It’s always interesting to look at a system that was developed in a different era – it makes you aware how much refactoring goes into the IDEs of modern systems to stop them looking like refugees from a previous decade. (Perhaps the less said about the “Mexican Frogger” game the better…)
The final talk (for both this session and the day) was “Apps for Social Justice: Motivating Computer Science Learning with Design and Real-World Problem Solving”, presented by Sarah Van Wart. Starting with motivation, tech has diversity issues, with differential access and exposure to CS across race and gender lines. Tech industry has similar problems with recruiting and retaining more diverse candidates but there are also some really large structural issues that shadow the whole issue.
Structurally, white families have 18-20 times the wealth of Latino and African-American people, while jail population is skewed the opposite way. The schools start with the composition of the community and are supposed to solve these distribution issues, but instead they continue to reflect the composition that they inherited. US schools are highly tracked and White and Asian students tend to track into Advanced Placement, where Black and Latino students track into different (and possibly remedial) programs.
Some people are categorically under-represented and this means that certain perspectives are being categorically excluded – this is to our detriment.
The first aspect of the theoretical prestige is Conceptions of Equity. Looking at Jaime Escalante, and his work with students to do better at the AP calculus exam. His idea of equity was access, access to a high-value test that could facilitate college access and thus more highly paid careers. The next aspect of this was Funds of Knowledge, Gonzalez et al, where focusing on a white context reduces aspects of other communities and diminishes one community’s privilege. The third part, Relational Equity (Jo Boaler), reduced streaming and tracking, focusing on group work, where each student was responsible for each student’s success. Finally,Rico Gutstein takes a socio-political approach with Social Justice Pedagogy to provide authentic learning frameworks and using statistics to show up the problems.
The next parts of the theoretical perspective was Computer Science Education, and Learning Sciences (socio-cultrual perspective on learning, who you are and what it means to be ‘smart’)
In terms of learning science, Nasir and Hand, 2006, discussed Practice-linked Identities, with access to the domain (students know what CS people do), integral roles (there are many ways to contribute to a CS project) and self-expression and feeling competent (students can bring themselves to their CS practice).
The authors produced a short course for a small group of students to develop a small application. The outcome was BAYP (Bay Area Youth Programme), an App Inventor application that queried a remote database to answer user queries on local after-school program services.
How do we understand this in terms of an equity intervention? Let’s go back to Nasir and Hand.
- Access to the domain: Design and data used together is part of what CS people do, bridging students’ concepts and providing an intuitive way of connecting design to the world. When we have data, we can get categories, then schemas and so on. (This matters to CS people, if you’re not one. 🙂 )
- Integral Roles: Students got to see the importance of design, sketching things out, planning, coding, and seeing a segue from non-technical approaches to technical ones. However, one other very important aspect is that the oft-derided “liberal arts” skills may actually be useful or may be a good basis to put coding upon, as long as you understand what programming is and how you can get access to it.
- Making a unique contribution: The students felt that what they were doing was valuable and let them see what they could do.
Take-aways? CS can appeal to so many peopleif we think about how to do it. There are many pathways to help people. We have to think about what we can be doing to help people. Designing for their own community is going to be empowering for people.
Sarah finished on some great questions. How will they handle scaling it up? Apprenticeship is really hard to scale up but we can think about it. Does this make students want to take CS? Will this lead to AP? Can it be inter-leaved with a project course? Could this be integrated into a humanities or social science context? Lots to think about but it’s obvious that there’s been a lot of good work that has gone into this.
What a great session! Really thought-provoking and, while it was a reminder for many of us how far we have left to go, there were probably people present who had heard things like this for the first time.
Mark Guzdial has put out some excellent posts recently on Barbara Ericson’s ongoing work on analysing AP CS exam attempts and results across the US. Unsurprisingly, to those of us who see the classrooms on a day-to-day basis, women are grossly underrepresented. In this interview, Barbara is quoted:
Barbara Ericson, director of computing outreach at Georgia Tech, has made a startling claim. She said not one female student in three states – Mississippi, Montana and Wyoming — took the Advanced Placement exam in computer science last year.
Ericson appeared on Weekend Express to discuss the gender gap and explains why more women aren’t interested in computer science.
Now, I’m not going to rehash all of these posts but I did want to pick on one blogger who took the AP data and then, as far as I’m concerned, not only got it wrong by making some fundamental interpretational errors but managed to do so in a way that so heavily reeked of privilege that I’m going to call it out.
I hesitate to link to the article on the Huffington Post but it’s only fair that you should read it to see what you think, even though it will generate traffic. The article is called “Memo to Chicken Little: Female Scientists Do Roam Among Us, and Gasp! Some Even Wear Lipstick”. So before we’ve even started, we’ve got one good stereotype going in the title.
Look, I’m not planning to drag apart the whole article but I will pick on one point that the author makes because it really irritates me. Here’s the paragraph:
As a woman who likes science as a bystander but chose not to pursue it professionally, I’ve got a couple of problems with all this handwringing. Mostly, well-intentioned as it is, it implies that women need “help” choosing a field of study. High school girls are exposed to exactly the same science and math courses they need to graduate as boys are, but in the eyes of the handwringers, girls are either too shallow or simple to choose for themselves, or need to be socially engineered into the correct balance of male vs. female, regardless of their choices. I appreciate your concern, but frankly, it’s pretty demeaning.
Frankly, I’ve never seen a more disingenuous interpretation of attempts to undo and reverse the systematic anti-female bias that is built into our culture. I’ve never seen anyone who is trying to address this problem directly or indirectly label girls as shallow or too simple to choose – this is a very unpleasant strawman, constructed to make those of us who are trying to address a bias look like we’re the ones with the attitude problem. We don’t need to socially engineer girls into the correct balance, we need to engineer society to restore the balance and articles like this, which make it appear that women are deliberately choosing to avoid STEM, are unwelcome, unnecessary and unfair to the many young women who are being told that the way that our society works is the way that it should work.
Need I remind people of stereotype threat? The PNAS study that shows that women are as automatically likely to harshly judge women and lessen their rewards as their male colleagues? Looking at the AP attendance and performance doesn’t show equality, it shows the outcome of a systematically biased system.
To say that “High school girls are exposed to exactly the same science and math courses they need to graduate as boys are” is a difficult statement. Yes, women rack up roughly the same number of course credits but on the critical measurement of whether they choose to go on and pursue a profession? No, something breaks here. The AP test is a great measure because it is an Advanced Placement exam and your intention is to use this to go further. Is there clear evidence of far fewer women, as a percentage, going on from high school to college in STEM despite scoring the same kinds of grades? Yes. Is there evidence that some of these problems (anxiety about maths, for example) can start with perceptions of teachers in primary school? Yes. Is there a problem?
And the question is always, if your previous exposure has not been fair, then is it reasonable to pick an arbitrary level of course that would be fair to people who haven’t been discriminated against? For years, racism was justified by culturally-based testing that could not be performed at the same level by people outside the culture – which was then used to restrict their access to the culture.
To me, that statement about exposure summarises everything that is wrong with glib arguments about constructing equal opportunity. If we’re going for a big job and there’s a corporate ‘interview dinner’ for 20 people, then we’ll all be on our best behaviour at dinner. For someone to lose the job because nobody showed them how to use a finger bowl or because their family uses a knife in the ‘other’ way, is to provide an equal exposure in the present that is blatantly unfair because it doesn’t take into account the redress of previous bias to bring people up to the point where it is really equal opportunity.
I think history supports me in the statement that we have been proved wrong every other time we’ve tried to segregate human ability and talent based on fixed physical abilities that were assigned at birth. Isn’t it about time we started investing all of our effort into producing truly equal opportunity for everyone?