Posts tagged ‘NCWIT’
I get to teach our Media Computation in Python course, on Georgia Tech’s campus, in Spring 2014. I’ve had the opportunity to teach it on study abroad, and that was wonderful. I have not had the opportunity to teach it on-campus since 2007. Being gone from a course for seven years, especially a big one with an army of undergraduate TA’s behind it, is a long time. The undergraduate TA’s create all the assignments and the exams, in all of the introductory courses in the College of Computing. Bill Leahy, who is teaching it this summer semester, kindly invited me to meet with the TA’s in order to give me a sense for how the course works now.
It’s a very different course than the one that I used to teach.
- I mentioned the collage assignment, which was one of the most successful assignments in MediaComp (and shows up even today in AP CS implementations and MATLAB implementations). Not a single TA knew what I was talking about.
- The TA’s complained to me about Piazza. ”Nobody posts” and “I always forget that it’s there” and “It seems to work in CS classes, but not for the other majors.” I told them about work that Jennifer Turns and I did in 1999 that showed why Piazza and newsgroups don’t work as well as integrated computer-supported collaborative learning, and how that work led to our development of Swikis. Swikis were abandoned many years ago in MediaComp, even before the FERPA concerns.
- Sound is mostly gone. Students have to play a sound in one assignment based on turtle graphics. Students never manipulate samples in a sound anymore.
- I started to explain why we do what we do in MediaComp: Introducing iteration as set operations, favoring replicated code over abstraction in the first half of the semester, avoiding else. They thought that those were interesting ideas to consider adding to the course. I borrowed a copy of the textbook from one of them, and read them part of the preface about Ann Fleury’s work. Lesson: Just because you put it in the book and provide the citation, doesn’t mean that anybody actually reads it, even the TA’s.
It’s a relevant story because I’m presenting a paper at ICER 2013 on Monday 12 August that is a 10 year retrospective on the research on Media Computation. (I’m making a preview version of the paper available here, which I’ll take down when the ACM DL opens up the ICER 2013 papers.) It was 10 years ago that we posted our working document on creating MediaComp and our 2002 and 2003 published design papers, all of which are still available. We made explicit hypotheses about what we thought Media Computation would do. The ICER 2013 paper is a progress report. How’d we do? What don’t we know? In hindsight, some seem foolish.
- The Plagiarism Hypothesis: We thought that the creative focus of MediaComp would reduce plagiarism. We haven’t done an explicit study, but if we found a difference with statistical significance, it would be meaningless. Ten years later, still lots of academic misconduct.
- The Retention Hypothesis: Perhaps our biggest win — students are retained better in MediaComp than traditional classes, across multiple institutions. The big follow-up question: Why? Exploring that question has involved the work of multiple PhD students over the last decade, helping us understand contextualized-computing education.
- The Gender Hypothesis: We designed MediaComp based on recommendations from people like Jane Margolis and Joanne Cohoon on how to make an introductory CS course that would be successful with women. Our evidence suggests that it worked, but we don’t actually know much about men in the class.
- The Learning Hypothesis: We hoped that students would learn as much in MediaComp as in our traditional CS1 class. Answering that question led to Allison Elliott Tew’s excellent work on FCS1. The bottom line, though, is that we still don’t know.
- The More-Computing Hypothesis: We thought that non-CS majors taking MediaComp would become enlightened and take more CS classes. No, that didn’t really happen, and Mike Hewner’s work helped us understand why not.
There are two meta-level points that I try to make in this paper.
- The first is: Why did we think that curriculum could do all of this, anyway? Curriculum can only have so much effect. There are lots of other variables in student learning, and curriculum only touches some of those.
- The second is: How did we move from Marco Polo to theory-building? Most papers at SIGCSE have been classified as Marco Polo (“We went here, and we saw that.”) MediaComp’s early papers were pretty much that — with the addition of explicit hypotheses about where we thought we’d go. It’s been those explicit hypotheses that have driven much of the last 10 years of work. Understanding those hypotheses, and the results that we found in pursuit of those hypotheses, have led us to develop theory and to support a broader understanding of how students learn computing.
Lots of things change over 10 years, and not always in positive directions. Good lessons and practices of the past get forgotten. Sometimes change is good and comes from lessons learned that are well worth articulating and making explicit. And sometimes, we got it plain wrong in the past — there are ideas that are worth discarding. It’s worth reflecting back occasionally and figuring out how we got to where we are.
I was sent links to the She++ documentary by several people. It’s a nicely done documentary on the issues of women in undergraduate computing at Stanford.
The Twitter account for She++ posted the video link with the comment, “Show this to your daughters!” Others in social media are suggesting that this should be seen by all girls to encourage them in CS. This is a great video for describing the students’ experience. I’m not sure it works as a recruiting tool.
In some of our GaComputes work, we found that female workshop leaders were more likely to warn the girls in their computing workshops, “Now, I know that this is hard, but you’ll be able to do something cool here.” The male leaders were more likely to just say, “This is so cool!” The female leaders tended to get declines in interest in computing — girls left the workshop saying more often, “Computing is hard” and “Girls can’t do computing.” The male leaders tended to get positive improvement in attitudes. Notice that the male leaders didn’t say it was easy. They didn’t lie. They just emphasized the benefit.
This video feels honest and heartfelt. The women interviewed say things like, “It was really difficult” and “I didn’t feel I fit in.” And when they speak to the camera, they say, “Girls, it will be hard at first, but it will get better.” I believe that the speakers are being honest, but I worry that those descriptions might trigger stereotype threat. Does telling girls about imposter syndrome make it less likely? Some pretty amazingly successful people suffer from imposter syndrome.
I recommend that the video be seen by all computer science teachers, especially teachers of undergraduates. It’s important for teachers to know about the experience of women in their classrooms. I don’t recommend it for girls that you hope to recruit into computing.
We have very few AP CS teachers in the United States — about 1 for every 12 high schools, and they’re not evenly distributed. I do get that an AP CS MOOC may make it more available to more students. Still, I’m not too excited about a MOOC to teach AP CS. AP CS is already overwhelmingly white and male. The demographic data from existing CS MOOCs is even more white and male than our face-to-face classes. I can’t see how an AP CS MOOC will improve diversity, and we have a desperate need to improve diversity.
But beyond that — Rupert Murdoch?!? Really? Why is he interested in CS education? I do note that he is starting out with a monetizing scheme. Want your questions answered? $200 per student per year. I do see how this AP CS MOOC may deal with some of the shortcomings of other MOOCs, and may even be better with diversity than existing MOOCs, because of the availability of direct support — at a price.
Now, Rupert Murdoch, the billionaire media mogul behind News Corp., wants to do something about the lack of computer science education. Murdoch’s Amplify education unit plans to launch a new advanced placement online computer science course this fall, taught by longtime high-school instructor Rebecca Dovi.
The course is described as a MOOC, short for massive open online course. It is free to high school students, though additional resources will be made available for $200 per student. It is geared toward those who want to take the computer science AP exam in 2014.
An interesting study suggesting that role models and how they’re described (in terms of their achievements, or in terms of their struggles) has an interaction with students’ stereotypes about scientists and other professionals in STEM fields. So there are not just cognitive benefits to learning from failure, but there are affective dimensions to focusing on the struggle (including failures) and not just the success.
But when the researchers exposed middle-school girls to women who were feminine and successful in STEM fields, the experience actually diminished the girls’ interest in math, depressed their plans to study math, and reduced their expectations of future success. The women’s “combination of femininity and success seemed particularly unattainable to STEM-disidentified girls,” the authors conclude, adding that “gender-neutral STEM role models,” as well as feminine women who were successful in non-STEM fields, did not have this effect.
Does this mean that we have to give up our most illustrious role models? There is a way to gain inspiration from truly exceptional individuals: attend to their failures as well as their successes. This was demonstrated in a study by Huang-Yao Hong of National Chengchi University in Taiwan and Xiaodong Lin-Siegler of Columbia University.
The researchers gave a group of physics students information about the theories of Galileo Galilei, Issac Newton and Albert Einstein. A second group received readings praising the achievements of these scientists. And a third group was given a text that described the thinkers’ struggles. The students who learned about scientists’ struggles developed less-stereotyped images of scientists, became more interested in science, remembered the material better, and did better at complex open-ended problem-solving tasks related to the lesson—while the students who read the achievement-based text actually developed more stereotypical images of scientists.
A fascinating set of studies! (Follow the link below to see the description of the second one.) It reminds me of our GaComputes findings about the importance of early computing experiences for minority students. Just taking a single CS class changed the women’s definitions of what a computer scientist is. I’ve written on Blog@CACM about how under-represented minorities were more likely than majority students to have had some CS experience in middle or high school that influenced them. These studies together support the argument that having some CS in K12 will likely have a significant impact on later attitudes towards computing.
First, they asked undergraduates from the UW and Stanford University to describe computer science majors.
They found students who were not computer science majors believed computer scientists to be intelligent but with poor social skills; they also perceived them as liking science fiction and spending hours playing video games. Some participants went so far as to describe computer scientists as thin, pale (from being inside all the time), and having poor hygiene.
“We were surprised to see the extent to which students were willing to say stereotypical things, and give us very specific descriptions. One student said computer science majors play ‘World of Warcraft’ all day long. And that’s a very specific, and inaccurate, thing to say about a very large group of people,” Cheryan said.
However, women who had taken at least one computer science class were less likely to mention a stereotypical characteristic. There was no difference in men’s descriptions, whether or not they had taken a computer science class.
I am on the Royal Society’s side here. Absolutely, there is a solid moral argument that women should have every opportunity to be in STEM fields and that bias should be identified and eliminated. But it’s also a good idea to learn more about gender diversity and to explore whether a business case for gender diversity exists — can we prove that science works better if there if there is gender diversity? Why not ask these questions?
MPs have launched a formal parliamentary inquiry into whether British science is institutionally sexist. Concern at the high numbers of women scientists abandoning their careers has prompted the House of Commons Science and Technology Committee to look into why Britain is failing to stop females dropping out of science.
The Royal Society, which advises the Government on science, has launched a separate investigation into whether greater gender diversity would lead to better science. Such is the sensitivity around the issue that the study’s announcement provoked a public spat when a critic claimed the research would result in the need to make a business case for equality when solid moral arguments already existed.
I read this piece as an explanation for a computing culture that leads to “Donglegate” and a thousand paper cuts. Hostile, uncommunicative, arrogant, impolite, eccentric — none of those are impediments to getting hired. That’s what we have to change to broaden participation in computing. We have to change the culture.
Snowden’s lack of formal education—no high school diploma—wouldn’t have bothered me. The ideal was a person who was sharp, independent, systematic, and very careful. The top tech programs—at places such as MIT, Caltech, Carnegie Mellon, Stanford, UC–Berkeley, and the Ivies— produced many strong candidates, but a computer science degree from most other universities was less of a positive indicator. People with nontraditional educations sometimes did just as well. They usually had some gaps in their knowledge of algorithms and data structures, but I cut them slack, because teaching yourself is harder than being taught, and often more valuable. If you could run the gauntlet of five or six whiteboard coding tests, you stood a good chance of being hired. Sometimes an applicant would be too hostile or uncommunicative, but for me at least, technical skill was the deciding factor the vast majority of the time. There are a nontrivial number of techies who are smart but literally impossible to work with because they are incapable of compromise or politeness. When eccentricity is the norm, it’s hard to have a litmus test for what acceptable eccentricity is.
Nice letter, nailing the critical issue: The tech industry needs women, not the other way around. We have to figure out how to engage women and under-represented minorities.
Girls of the world, the tech industry is waiting for you. The skills you learn in your math and sciences classes today are the foundation for building technology that will touch nearly every aspect of our lives in the future — your future. If you invest in learning technical skills, soon you won’t just be consuming technology, you’ll be defining it, creating it and sharing it with people all over the world.
The tech industry is growing faster than nearly all other industries today. In fact, computer programming jobs are growing at two times the U.S. national average. And it’s still very early days. Google, for example, is only in its teenage years. The opportunities for a career in technology will only continue to grow as an additional 5 billion people around the world come online.
Yet despite being a ripe career field, the tech industry is losing women. In the United States, according to one report: “young women earned 37% of computer science degrees in 1985; today, the number has plummeted to 18%. Some 22% of software engineers at tech companies are women.” It’s a deficiency we see mirrored around the world.
Kevin Karplus recently wrote a post (on his highly-recommended Gas Station without Pumps blog) about why funding the new AP CS:Principles (AP CS:P) is such a bad idea, mentioning my positive comments on the news. I actually agree with many of the Gas Station points, but I have a more optimistic take on them.
CS:P was never meant to give credit towards a computing degree. The attestation effort showed that many schools do offer some kind of course like what’s in CS:P. It’s true at UCSC, too:
My own campus has several intro programming courses, some at the level of the AP CSP course. I suspect that our campus would offer credit in these low-level courses for the AP CSP exam. These lowest-level courses do not count towards any major, though—they provide elective credit for what should be high-school level courses. The intent (as is apparently the intent for AP CSP) is to provide an extremely low barrier to entry into the field.
That’s really the main point. We need more CS education in high schools. When there’s only 1 AP CS teacher for every 12 high schools, there is very little computer science education out there. AP courses is a big lever to get low barrier courses out there.
Gas Station then points out that courses like these may not actually have much of an impact downstream.
I don’t know how well the low barrier to entry works, though. I’ve not seen much evidence on our campus that the lowest level courses produce many students who continue to take higher level CS courses…We still have appallingly low numbers of women finishing in CS (and the new game-design major within CS is even more heavily male), so I can’t say that the lower-level intro courses have done much to address the gender imbalance.
That’s a fair point. We don’t know that it will work to get more students into computing. I just did a Blog@CACM post that suggests that the evidence we have is promising in terms of impact on careers, especially for under-represented minorities. You can’t really use a single campus to test the idea though. The game is at the level of thousands of high schools where there is no computer science at all.
I share the Gas Station concern over the professional development challenge.
The success of CSP also depends on thousands of high schools suddenly deciding to teach the course and getting training for their teachers to do this. I (along with many others) have grave doubts that the schools have the desire or the ability to do this. It is true that the CSP course should be a bit easier to train people for than the current AP CS A course (if only because Java syntax, the core of CS A, is so deadly dull).
The question that we need answered is: how important the “Advanced Placement” lever is? Is it so important (big payoff) that having a more accessible AP course in CS (thus, lower cost to adopt) changes the balance for schools? I just had an all-day meeting with folks from the Georgia Department of Education two weeks ago, and they are building AP CS:P into their curriculum plans because it’s now AP. That designator matters. Does it matter enough to draw more teachers into professional development, to get more schools to hire CS teachers? I’m optimistic, but I share the Gas Station concern.
We should also be clear that there really isn’t a single “CS:Principles” course yet. There have been several pilots, and some assessment questions tested, but there is no well-defined curriculum yet and no exemplar test. I have exactly the same question as Gas Station:
The new CSP exam is not supposed to be so language-dependent, which may allow for better pedagogy. Of course, I’m curious how the exam will be written to be language-independent, and whether it will be able to make any meaningful measurements of what the students have learned.
The plan is to use a portfolio approach, like what’s being used in art AP exams now. I really don’t know if it’ll work. I trust that the people working on it, but do see it as an unsolved problem.
I don’t share the Gas Station concern about “Gresham’s Law for pedagogy” (which I’d not heard of previously):
I suspect that the easier AP CSP will replace AP CS A at many high schools, and that CS A will disappear the way that CS AB did in May 2009 (Gresham’s Law for pedagogy: easier courses drive out harder ones). Whether this is a good or bad outcome depends on how good the AP CSP course turns out to be.
The fact that there already are CS:P-like courses on many campuses, co-existing with CS1’s (intro CS for majors) is evidence that easier courses don’t always drive out harder ones. On our campus, we offer three CS1’s. The MediaComp course would probably be easier for Engineering students than the challenging MATLAB-based on that they currently require, but the Engineering faculty have not been eager to swap it out. The existence of “Physics for Poets” and Calculus aimed at different kinds of students is more evidence that Gresham’s Law doesn’t always hold for classes.
There are lots of challenges to CS:P. AP CS Level A is doing better these days, and I’m glad for that. I want both to succeed. I want a lot of CS in lots high schools. Will the new AP CS:P lead to more CS majors and more people in computing careers? I don’t know — I think so, but I’m not really worried about it. I believe in “computing for everyone” and that lots of people (even non-IT professionals) need to know more about computer science, so having more access to computing education in more schools is a positive end-goal for me.
Fascinating study – not surprising, but worthwhile noting. This work was done in Chemistry, so it bears replication in other STEM disciplines. Some on the SIGCSE-Members list were wondering, “Is this just for research-oriented universities? Or for teaching-oriented universities, too?” In our work interviewing faculty as part of our work in GaComputes and DCCE, we heard surprisingly similar concerns at both kinds of institutions. The faculty at schools with a teaching mission told us that their tenure was based on research publications, and they felt similar levels of stress.
Young women scientists leave academia in far greater numbers than men for three reasons. During their time as PhD candidates, large numbers of women conclude that (i) the characteristics of academic careers are unappealing, (ii) the impediments they will encounter are disproportionate, and (iii) the sacrifices they will have to make are great.
Andy Kessler of the Wall Street Journal (linked below) misunderstands why we have a computing labor shortage. MOOCs definitely make “computing education” (in general) accessible to more people. But that doesn’t mean that we’ll shrink the computing labor shortage, as described by Code.org. Undergraduate computing education is “accessible” to everyone on campus, but rarely draws more than 15% women. We have to go from “accessible” to “engaging.” Unless we draw in women and under-represented minorities, we can’t close the jobs-graduates gap. We have to change how we teach to draw more women and under-represented minorities, and MOOCs don’t teach that way.
Anyone who cares about Americas shortage of computer-science experts should cheer the recent news out of Georgia Tech. The Atlanta university is making major waves in business and higher education with its May 14 announcement that the college will offer the first online masters degree in computer science—and that the degree can be had for a quarter of the cost of a typical on-campus degree. Many other universities are experimenting with open online courses, or MOOCs, but Georgia Techs move raises the bar significantly by offering full credit in a graduate program.It comes just in time. A shortfall of computer-science graduates is a constant refrain in Silicon Valley, and by 2020 some one million high-tech job openings will remain unfilled, according to the Commerce Department.
The latest Freakonomics podcast is on tipping and whether it should be banned, i.e., made illegal. One of the arguments for banning tipping is that it’s discriminatory. White servers get more than Black servers, for example. Professor Michael Lynn cited a Supreme Court case that I found described below. If a neutral practice disproportionately affects minorities or women in an adverse manner, then the practice is illegal.
I’ve raised the question here before, whether CS departments could be forced to change their teaching practices in order to comply with Title IX provisions so that more women might participate. One of the arguments I got in response was that no one adopted any practices to explicitly exclude women. This ruling says that the motivation for the practice doesn’t matter — even if it’s a “neutral” practice, if the effect is discriminatory, it has to go. We certainly have evidence that implicit bias exists in computing classrooms and that CS teachers allow their classrooms to develop a defensive climate. Further, we know a lot about how to improve women’s participation in computing. If we have a legal requirement to make computing education available to women, my guess is that we could be required to make change. For example, could we be forced to give up MOOCs as a discriminatory practice, since MOOCs have a measurable discriminatory effect?
In Griggs v. Duke Power Co., the Supreme Court decides that where an employer uses a neutral policy or rule, or utilizes a neutral test, and this policy or test disproportionately affects minorities or women in an adverse manner, then the employer must justify the neutral rule or test by proving it is justified by business necessity. The Court reasons that Congress directed the thrust of Title VII to the consequences of employment practices, not simply the motivation. This decision paves the way for EEOC and charging parties to challenge employment practices that shut out groups if the employer cannot show the policy is justified by business necessity.
Of course, I love a blog post on computing students with so much data and graphs that it could be a conference paper! Nice piece from Monica McGill on where gaming students are coming from, and what the implications are for future game designs.
Even in 2005, the IGDA report on its diversity survey found that the typical game development professional is “white, male, heterosexual, not disabled, […] and agrees that workforce diversity is important to the future success of the game industry” (pp. 9-10). The report goes on to state that “… it is reasonable to believe that diversity does have an impact on the game industry and the products we create – either via broader markets and/or a means to attract future talent” (p. 22).
Ah, attracting future talent. That phrase certainly begs the question: what future talent are we attracting? And does the prospective talent pool differ in its composition than current game industry employees? Or are we attracting more of the same, trapped in a cycle like the one Anna Anthropy describes as “straight white developers [who] make games that straight white reviewers market to straight white players, who may eventually be recruited to become the new straight white developers and reviewers” (Anthropy 2012)?
A nice piece making the argument that we can’t fix the computing employment shortage without diversifying our labor pool.
I found this quote (further along from the quote and link below): ”Geeks often have a hostile relationship to formal education. Rather than sit through a pre-programmed curriculum with problems and solutions laid out in advance, geeks like to tinker and hack to solve new problems and innovate.” If that’s true (and I believe it is), why are geeks advancing MOOCs, which are as formal and pre-programmed as you can get?
Despite a deserved reputation for progressiveness, the tech sector is highly exclusionary to those who don’t fit the geek stereotype–and this tendency is getting worse, especially in Silicon Valley. You might have heard, based on 2011 numbers, that only 25 percent of the U.S. high tech workforce is female, and the percentages have been in steady decline since the nineties. The numbers for minority women are even more dismal. Hispanic women represent 1 percent of the high tech workforce, and African-American women don’t fare much better, at 3 percent. The better the jobs, the lower the proportions are of women and non-Asian minorities. Despite the diversity of the population of the region, Silicon Valley, which boasts the highest salaries among tech regions, fares much worse than the national numbers.
Diana Franklin has just published a new book with Morgan & Claypool, A Practical Guide to Gender Diversity for Computer Science Faculty. This is exciting to see. I can’t recommend it yet, just because I haven’t read it. What’s great is that it’s a book on how to teach computing — and there are just far too few of those. Other than the Logo books and the Guide to Teaching CS (from Orit Hazzan et al.), there’s not much to help new CS teachers. So glad that Diana has written this book!
Computer science faces a continuing crisis in the lack of females pursuing and succeeding in the field. Companies may suffer due to reduced product quality, students suffer because educators have failed to adjust to diverse populations, and future generations suffer due to a lack of role models and continued challenges in the environment. In this book, we draw on the latest research in sociology, psychology, and education to first identify why we should be striving for gender diversity (beyond social justice), refuting misconceptions about the differing potentials between females and males. We then provide a set of practical types (with brief motivations) for improving your work with undergraduates taking your courses. This is followed by in-depth discussion of the research behind the tips, presenting obstacles that females face in a number of areas. Finally, we provide tips for advising undergraduate independent projects or graduate students, supporting female faculty, and initiatives requiring action at the institutional level (department or above).