Wednesday, November 18, 2009
In the beginning they identify the issue of low participation in computer science compounded with a substantial gender imbalance. However, they run into similar issues as we do with problems of gender difference. Trauth et. al. describe the collection of gender differences as flawed, in part as their case study identifies several women who upset the principles assumed by gender difference. Many of the approaches centering around gender differences ignore the countless women already participating in computer science and instead of focusing on improving this value they spend more time alienating the women already participating in computer science.
In interviewing women who are currently participating in the IT field they found a number of different factors that don't fall into the gender differences spectrum. For example, they found that imbalanced environments create hostile cultures for minorities. Crude jokes demeaning women and hostility are more likely to be present in male-dominated populations. Additionally, not seeing women regularly in the workplace creates false perceptions that women are somehow not qualified to participate in IT careers. Further, many of the women identified prominent female role models in their academic careers that helped to create or continue their interest in realizing that IT was an acceptable path for them.
So while we may be looking globally to operate on the US, these studies have implications globally outward as well. Many countries around the world suffer the same gender imbalances and are buried under the same gender differences suggestions that plague the United States.
Thursday, November 12, 2009
The university has fairly equal intake rates and in almost all years (with the exception of 1999/2000) examined in this study, more men failed / withdrew from the program each year.
While attrition rates may be fairly low overall, and in particular for women at the University of Malaysia, that is not the case at many U.S. universities.
In the paper Scavenger Hunt: Computer Science Retention Through Orientation by Talton et al. from the University of Illinois:
"Like many large research universities, the University of Illinois has struggled with the high attrition rate of ﬁrst-year students in computing disciplines. In the ﬁve year period prior to 2003, roughly 25% of the total number of entering freshmen have dropped out of the program by the end of their ﬁrst year (see Table 1). In particular, the attrition rate of women and minority students is quite high, averaging about 35% for the same period."
Similar situations exist even at CMU.
In a paper on W@SCS, (Women in Computer Science: The Carnegie Mellon Experience by Lenore Blum), Blum looks at retention rates of men and women in CS.
In a paper (not the book), Unlocking the Clubhouse: The Carnegie Mellon Experience, Margolis and Fisher examine the same data at CMU and show promising trends of retention of women in CS.
These graphs so something that should not be surprising, that higher percentages of women in the major seems to lead to higher retention. In Blum's paper Peter Lee, Associate Dean for Computer Science Undergraduate Education at the time is quoted as saying, "[Retention] seems unnecessarily negative to me, and at any rate seems to aim too low. The goal, it seems to me, is to take advantage of the great recruiting success and produce a crop of graduating women who will be the future leaders, world-class scientists, visionaries, and captains of industry. . . . "
Other factors which seem to raise retention rates of women in CS are discussed in IMPROVING THE PERSISTENCE OF FIRST-YEAR UNDERGRADUATE WOMEN IN COMPUTER SCIENCE by Rita Manco Powell. Powell did a study at UPenn about retention and found that there was a 50% persistence rate of women before changes were implemented compared with an 85% persistence rate after changes were implemented which is equal to the male persistence rate. Some changes include more faculty-student interaction, social gatherings for students, mentoring groups, and the organization of WICS (Women in Computer Science). These are very similar to the findings at CMU with the organization of W@SCS.
Powell also examined why women were leaving CS - why the attrition rates were so high:
"This research study found that many of the study participants began the computer science major with an inadequate background from high school in the subject, causing them to struggle to perform as well as their peers with more computer science experience. Because of this fact, which was further heightened by the women’s perception that the male students knew more than they, several women lost confidence in their ability to be successful in the major and subsequently lost interest in the major. Social isolation accompanied their gender minority status within their peer group further weakening their resolve to persist."
I am interested in examining whether women at CMU have similar reasons for leaving CS, and also examining what men's reasons are. I am currently working on coming up with interview questions for men and women who have switched out of SCS at CMU. I am also interested in looking at attrition and retention rates, because I know of 4 women in my year who have left CS (and a few in other years), but I don't believe that I know of any men who started in CS and are now in a different major.
Wednesday, November 11, 2009
However, industry is just one of the facets describing what computer science is. Another, we can find in academia. In detailing what is required to give a computer science degree we describe what computer science is. While examining different enrollment requirements across schools I learned we don't even have a common language for describing computer science. Some people where getting bachelors of science in computer science. Some can only get a bachelor's in electrical engineering with a computer science concentration. Some get a bachelor's in technology and some even get a bachelor's in computer applications. To describe some of these different facets I examined six schools describing my academic options in computer science and a couple schools internationally to see how the language varies across the schools. I also did my best to determine where in the suggested course sequence the first theory/discrete math course would be taken.
1st, my home institution and thus easiest to research Carnegie Mellon:
Carnegie Mellon has a very descriptive and intense description of what computer science is, in part because we know what a problem describing computer science can be. The SCS website says:
"At Carnegie Mellon, our curriculum encompasses the entire study of computation and how it can be applied to the world around us. Computer science can organize information, build smaller, faster, more secure systems, create channels of communication and delve deep into complex data sets."
with even more at http://www.scs.cmu.edu/prospectivestudents/undergraduate/index.html
Additionally, my first discrete math course was my very first semester taking the difficult concepts of mathematics which was a real crash course into what I would be studying in my years.
2nd, an institution I grew up around Arizona State University:
ASU's degree description leaves a lot to be desired, stating:
"The discipline of computer science is concerned with the design of computers, computational processes and information transfer and transformation. Examples of projects a computer scientist might work on include: design of next-generation computer systems, computer networking. biomedical information systems, gaming systems, search engines, Web browsers and computerized package distribution systems."
It's hidden in there with "information transformation" but there's nothing really shocking that tears you away from computer scientist equals programmer. Examples of projects a computer scientist might work on include: programming some stuff. More can be found at: http://engineering.asu.edu/undergraduate/cs
Additionally, ASU computer science students are tasked to get started programming early while fulfilling their gen eds. In their third semester in the suggested course sequence I was finally able to find discrete mathematical structures which I assumed to be their first discrete math course.
3rd, the Massachusettes Institute of Technology:
MIT I found interesting because their program was the only one I found explicitly coupled with electrical engineering. I think you can only obtain a bachelor's in engineering with a "computer science track" if you wish to pursue computer science. As such their "what a computer science degree is" description is less concrete and I had to settle for the learning objectives from acquiring a degree the part of which I found most noteworthy being:
"4. Students will develop an understanding of the importance of the social, business, technical, and human context in which a process or product being designed will work."
Being implicit about the social and human context in which a process is designed I think is a valuable component to the description. Computer science involves a lot of teamwork and thinking outside of the programming paradigm that also necessitates looking at the human component. More about MIT's objective is here http://www.eecs.mit.edu/ug/objectives.html
MIT's suggested course sequence wasn't easy to find in the literature I perused but I believe in the first year one of their options is for "Math for Computer Science." The name I don't feel is the most inspiring but it's very early on in the track.
Looking at a global level I also examined how Oxford University structures its CS program:
Oxford also makes the computer an explicit part of computer science stating:
"Computer Science is the study of problem-solving using computers. Digital computers and the programs they run are among the most complicated products of modern engineering. This practical discipline has its foundations in basic, curiosity-driven science. What kind of thing is a computer program? How can we create programs whilst being sure of avoiding bugs? What is the fastest way of solving certain kinds of problems? Are there problems that can be stated simply but have no simple solutions? Are there problems that cannot be solved by computers at all?"
While it does tap on computer science, but attempts to make programming an ingrained part of computer science. How do we avoid writing programs without bugs is particularly jarring in this regard and I'm not sure where they're going with that. More about Oxford's CS program is: http://www.ox.ac.uk/admissions/undergraduate_courses/courses/computer_science/computer_science.html
Additionally, the suggested course sequence expects students to take both design and anaylsis of algorithms as well as discrete mathematics, logic, and proof in their first year starting theory off early.
Finally, I looked at one of the schools in IIT, Kanpur:
IIT is very proud of its reputation as a leader in computer science and proudly expresses the fact that they were the first college in India to offer computer science. How the degree itself is described however is hard to find on the website. I was unable to find an actual description of computer science on the department website. If you would like to search their website is http://www.cse.iitk.ac.in/
One interesting thing about IIT Kanpur is students don't take any courses described as computer science until their third year. In their first two years they take only core courses while their last two years are almost exclusively computer science with their first discrete mathematics course appearing in semester 4.
Looking across all of these perspectives I don't feel comfortable describing any as optimal or the best. I lean strongest to Carnegie Mellon because it's the program I've grown out of but I expect any member of any of these institutions could critique similarly. What is very apparent however is we all have different expectations and different language for computer science. Some schools get their students in theory earlier while some get them in later. Some schools also like to market their computer science programs as very closely attached to computers while some like to describe computer science differently. These issues of language will have to be taken into account when evaluating how different cultural factors are in play.
Thursday, November 5, 2009
The summers after my senior year in high school and after my freshman year in college, I taught at a technology summer camp called iDTech. I taught a week long programming course in Java to high school / middle school aged students. There were other tech classes taught at the camp like 2D and 3D game development, web development and flash animation, video editing shooting and editing, among many others which varied at camp locations (we didn't have LEGO robotics at Brown, but they did at MIT, for example).
And one of the things that I found was that the percentages of girls who attended these camps was astonishingly low! Some weeks would have maybe 2 girls out of 30 kids. There were weeks when we had more girls, but I don't think that we ever had more than 7 out 30. Often times we had little girls (7-10 year olds) who were too young for the programming class, but who took the web development or 2D game creation class. A lot of girls also took the video editing class. I can't quite recall the exact numbers, but I don't think I ever had more than 2 out of 8 girls in my programming class per week. Often times there was one or no girls in my class.
I guess I never stopped to think about how young kids are when this problem starts. It's not like girls and boys are equally represented at tech camps or in learning to program at a young age, and then girls get turned off to it. It's that girls are never getting introduced to this stuff. Many of my guy friends at CMU in CS started programming when they were 7 or 8. I had used computers and could help my grandmother set up her printer, but it wasn't until high school that I learned how to program. I think that graphing / programmable calculators are one of the best things that ever happened to me. I learned how to program basic stuff like the quadratic equation or a program to generate the Fibonacci numbers, but I didn't learn how to do anything with more algorithmic complexity or more applied until I joined the Robotics team and learned C.
One of the things that's being done by Women@SCS is holding TechNights for Girls which introduces middle school girls to a series of tech related topics in weekly sessions. They might learn how to make a web page or program LEGO robots or use Photoshop.
I found a few other similar programs, but had never heard of most of them. Microsoft runs one called DigiGirlz. I found the iDTech page about girls and technology and encourages girls to come to camp, though similar to a page I found about the Navy a few weeks ago, seems to target what they think girls will like.
While we’re not strictly an all girls camp, girl camp, a summer camp for pre teen girls or a summer camp for teen girls, we DO offer a variety of courses that have curriculum tailored to what girls want to do. There’s nothing holding girls back from attending our summer camps. Whether you want to learn graphic design, filmmaking, 3D modeling, gaming, or even fashion design, iD has a course for you. iD Tech Camps is a great girl summer camps option!
I found various other programs run at different college campuses aimed at getting middle school girls interested in technology, but I didn't find anything younger. Maybe we need to aim younger and target elementary school girls? While I think that it's great that there are a number of programs that aim to get middle school girls interested and engaged in technology, I think that if boys are learning to program at 7 or 8, girls need to doing the same thing.
Tuesday, November 3, 2009
Lists of powerful individuals are often devoid of much diversity. Looking at the Forbes 400 list women aren't exactly abundant. Christy and Alice Walton make the top 10 but their fortune is from "inheritance." In a list of men tagged with "self made," the first woman I can find not tagged inheritance is Oprah Winfrey waaay down at 141. How do Forbes and others make up for their lacking diversity? By creating niche rankings of course! Forbes throws on a list of 100 Most Powerful Women to let us know that yes powerful women exist. But this sentiment seems tacked on, these lists are hard to be taken seriously and seem to further the idea that there's an existing power relationship between men and women that necessitates their own list. Women wouldn't make the 100 Most Powerful List so let's create a list for them.
I'm going on a long diatribe to try to ask what happens when women can't even get on a list for women? The other day somebody pointed me to 25 Women Influencing IT Today. The list begins innocently enough with women in executive positions in Yahoo and Google. However it doesn't take long to reach a strange, if not insulting, turn. #141 Richest Woman in the World Oprah Winfrey clocks in at #10 because she has "become an online phenomenon and is the 9th most followed Tweeter on the web." Are we so lacking female role models in computing that we can't even build a list of 10 women influencing IT? Are our role models so dire that we have to list Oprah Winfrey who has as much credibility to be on the list as Britney Spears? Women have won the Turing Award 2 of the last 3 years but this list still suggests they aren't being seen as leaders in the tech industry. Modis may not be the Fortune 500 or Forbes but they do a considerable amount of IT Staffing across the country. If nothing else this points to a visibility problem in computer science and the need for more projects like The Ada Project. Women may still be getting stuck making their name on niche lists but they aren't doing the niche work. At the very least we need to be sure we're getting better female role models in computing than Oprah Winfrey.