The story in the blog post connects to my previous blog post about CS faculty arguing against doing something other than lectures in their classes. Here the authority figures are preventing the rest from considering evidence. What a weird place for a scientific meeting to be at, but we really do listen to authority more than evidence.
On the scientific side, the meeting brought together a number of thought leaders detailing how different components of the scientific community perform. For instance, we learned that peer-review is quite capable of weeding out obviously weak research proposals, but in establishing a ranking order among the non-flawed proposals, it is rarely better than chance. We learned that gender and institution biases are rampant in reviewers and that many rankings are devoid of any empirical basis. …The emerging picture was clear: we have quite a good empirical grasp of which approaches are and in particular which are not working. Importantly, as a community we have plenty of reasonable and realistic ideas of how to remedy the non-working components. However, whenever a particular piece of evidence was presented, one of the science leaders got up and proclaimed “In my experience, this does not happen” or “I cannot see this bias”, or “I have overseen a good 600 grant reviews in my career and these reviews worked just fine”. Looking back, an all too common scheme of this meeting for me was one of scientists presenting data and evidence, only to be countered by a prominent ex-scientist with a “I disagree without evidence”. It appeared quite obvious that we do not seem to suffer from a lack of insight, but rather from a lack of implementation.
Nathan Ensmenger has not only written a fascinating book about how computing became so male (see book link here), he also maintains a blog that updates the story. The quote and picture below is from a recent post about a recently discovered source that describes women in computing from the 1960’s, back when women were considered better programmers than men. The rhetoric about women being more “sensitive” reminds me of Karen Ashcraft’s plenary talk at NCWIT which I highly recommend (see link here). The story about the Miss USA winner who became a computer programmer is particularly striking.
The Bodony story is not an isolated incident. The book is full of stories from women, and in fact includes an entire chapter devoted to women in computing (“The Equal Sex”). Seligsohn goes so far as to suggest that female programmers are not only equal in ability to men, but superior:
Given a complex customer problem, a female analyst/programmer will often handle the problem better than would her male colleagues with equivalent experience and ability. Not because businessmen are more lenient or show favoritism toward the female of the species, but because the female is often more sensitive to the nuances of a problem and to the complex interpersonal relations that may be part of the problem. In a very real sense, every computer problem with a customer is also a customer relations problem, and this is where feminine tact, insight, and intuition, combining with solid programming and analytical ability, can really pay off for the girl programmer.
Google has just released a new report on K-12 CS Education. It’s linked at the bottom. I’m going to quote from a new Wired article that describes one of the big bottomlines.
In a big survey conducted with Gallup and released today, Google found a range of dysfunctional reasons more K-12 students aren’t learning computer science skills. Perhaps the most surprising: schools don’t think the demand from parents and students is there.
Google and Gallup spent a year and a half surveying thousands of students, parents, teachers, principals, and superintendents across the US. And it’s not that parents don’t want computer science for their kids. A full nine in ten parents surveyed viewed computer science education as a good use of school resources. It’s the gap between actual and perceived demand that appears to be the problem.
Searching for Computer Science: Access and Barriers in U.S. K-12 Education
To understand perceptions of computer science and associated opportunities, participation, and barriers, we worked with Gallup, Inc. to survey over 1,600 students, 1,600 parents, 1,000 teachers, 9,600 principals, and 1,800 superintendents. We found:
Exposure to computer technology is vital to building student confidence for computer science learning.
Opportunities to learn computer science at schools is limited for most students. When available, courses are not comprehensive.
Demand for CS in schools is high amongst students and parents, but school and district administrators underestimate this interest.
Barriers to offering computer science in schools include testing requirements for other subjects and limited availability and budget for qualified teachers.
Terrific insight from my colleague Charles Isbell. Since school rankings matter so much in faculty hiring, you only have to change things at a few schools to change the field. We could broaden participation in CS PhD’s much more easily than you might think.
Professor Charles Isbell of Georgia Tech delivered an “aha moment” for me. More than 60 percent of the faculty at the top 4, 10, 20, and 25 computer science programs are graduates of one of these same programs. The ranking of one’s PhD institution is a huge factor in hiring—departments hire at their own rank or higher. This is common knowledge, but Charles connected it to diversity. If the very top programs would make a truly concerted effort to increase the participation of women and minorities in PhD programs, the effect would propagate throughout the entire computer science field. Only a few people, those who lead and serve on the PhD admissions committees, can make it happen.
I posted a few weeks about our two Georgia Tech papers at the first ever RESPECT conference (post on Miranda Parker’s paper and post on Barbara Ericson’s paper). The conference itself was great — I expect to see a lot more good things coming out of that conference. (The papers should show up in the IEEE Xplore library soon.)
What I liked about RESPECT was that the focus just on broadening participation in computing issues allowed for greater depth and nuance than at ICER or SIGCSE. The first paper of the day was Representation of Women in Postsecondary Computing 1990-2013: Disciplines, Institutional, and Individual Characteristics Matter by Stuart Zweben and Betsy Bizot. They dove into the differences between women in Computer Science vs. Computer Engineering vs. Software Engineering vs… They all have a depressing downward trend — except for one. Interdisciplinary degrees (like our Computational Media major) are the ones in which representation of women is increasing. (The slide they presented with this graphic was easier to read than the one in the paper, but my picture of the slide is less clear.)
I also found fascinating the paper by Hodari, Ong, Ko, and Smith, Enabling Courage: Agentic Strategies of Women of Color in Computing. They pointed out differences in the experiences of women of color. I was quite surprised at how different they are. (The below graph isn’t in the paper, so you’ll have to make do with my picture of the slide.) That relatively flat red line at the bottom is the percentage of Hispanic or Latina Females in computer science. I found the flatness of that line encouraging. In the last few years, we’ve had a massive rise in enrollment. The fact that the Hispanic/Latina women line is pretty steady means that we must have had a commensurate rise in the numbers of Hispanic/Latina women in CS.
There were a bunch of short papers and lightning talks that left me wanting more detail — which is exactly what they’re supposed to do. The paper Encouraging Online Contributions in Underrepresented Populations by Nacu, Martin, Sandherr, and Pinkard got me thinking about the importance of co-design (involving the target student populations involved in the creation of the classes, like the participatory design methods that Betsy DiSalvo uses) to get buy-in and to insure that the interventions are culturally appropriate.
The RESPECT panels didn’t work as well for me — and I admit to being on one of the two panels. They were more like a bunch of short presentations, and went on too long with little discussion. It’s hard to get panels to work in a research conference. Everybody wants to talk about their thing. Panels work best when there is some disagreement on the panel, and the discussion can help everyone to gain a new perspective.
RESPECT was popular which led to a minor problem. The exemplary paper sessions were packed with all the RESPECT attendees and all the co-located STARS attendees who wanted to hear the great research results! They’re going to need a bigger space next year. That’s a good problem to have for a first time conference.
My Blog@CACM post this month makes a concrete proposal (quoted and linked below). We (all academic computing programs) should incentivize faculty to use active learning methods by evaluating teaching statements for hiring, tenure, and promotion more highly that reference active learning and avoid lecture.
On my Facebook page, I linked to the article and tagged our Dean of Engineering, the Vice-Provost for Undergraduate Education, and the RPT Chair for our College, and asked, “Can we do this at Georgia Tech?” The pushback on my Facebook page was the longest thread I’ve ever been part of on Facebook.
The issues raised were interesting and worth discussing:
- Would implementing this put at a disadvantage new PhD’s who have no teaching experience and don’t learn about active teaching? Yes, but that incentivizes those PhD programs to change.
- My blog post title is “Be It Resolved: Teaching Statements must embrace Active Learning and eschew Lecture.” I chose the word “eschew” deliberately. It doesn’t mean “ban.” It means “deliberately avoid using” which is what I meant. Lecture has its place — I wrote a blog post defending lecture which still gets viewed pretty regularly. The empirical evidence suggests that we should use active learning more than lecture for undergraduate STEM education.
- Should such a requirement for teaching statements emerge from faculty talking about it, or should it be done by administrative fiat? I lean toward the latter. As I’ve pointed out, CS faculty tend to respond to authority more than evidence. The administration should do the right thing, and deal with educating teachers (e.g., what are active learning methods first? how do we use them? even in large classes?) later. Faculty will learn the active learning methods in order to create those teaching statements. The incentive comes first.
- Lots of respondents thought I was saying that we should require all teaching to be active learning. I wasn’t, and I don’t know how to enforce that anyway. By evaluating teaching statements more heavily that emphasize active learning, we create an incentive, not a requirement.
- Some faculty pushed back, “How about students that like lecture? Tough luck for them?” Since we know that active learning is better, even for students who like lecture — yes.
- Several respondents suggested that active learning is just too hard, that faculty are over-stressed as it is. Faculty are over-stressed, but active learning isn’t that hard. In fact, it’s hard for faculty because they have to be quiet and listen in class more. It is hard to make change, but that’s the point of incentives. We start somewhere.
- The biggest theme in the thread is that we should first aim to get faculty to care about teaching and to take active steps to improve their teaching. I don’t think that’s enough. Libertarian paternalism (see Wikipedia page) suggests that we set the incentive at the minimal acceptable level (use of active learning) then encourage choice above that (choosing among the wide variety of active learning methods). We don’t want people to choose options that won’t be in the best interests of the largest number of people.
The discussion went on for four days (and hasn’t quite petered out yet). I do wonder if active learning methods will be forced upon faculty if we don’t willingly pick them up. The research evidence is overwhelming, with articles in Nature and hundreds of studies reviewed in the Proceedings of the National Academy of Sciences. How long before we get sued for teaching but not using the best teaching methods? One of the quotes in the blog post says, “At this point it is unethical to teach any other way.” We should take concrete steps towards doing the right thing, because it’s the right thing to do.
Here is something concrete that we in academia can do. We can change the way we select teachers for computer science and how we reward faculty.
All teaching statements for faculty hiring, promotion, and tenure should include a description of how the candidate uses active learning methods and explicitly reduces lecture.
We create the incentive to teach better. We might simply add a phrase to our job ads and promotion and tenure policies like, “Teaching statements will be more valued that describe how the candidate uses active learning methods and seeks to reduce lecture.”
NYTimes recently had a series of op-ed articles about the role of technology in our world, specifically, “Is Silicon Valley Saving the World, or Just Making Money?” The piece by Melinda Gates (quoted below) caught my attention because she’s invoking the desire to meet students’ “different learning styles” (see blog post on this theme, and why it leads to worse learning).
There’s an important issue here (beyond me critiquing Melinda Gates, who does important work that I admire). It’s not all technology. We need other disciplines as well. Educational psychologists should be informing these developers at Facebook to tell them, “Stop. That’s a bad idea.”
I was at a workshop last year at Stanford about how to grow more CS Education Research in the United States. Andrew Ng spoke to us about the research going on at Coursera. He was clearly not previously informed about the focus of the workshop. When asked, “Would you want to hire more PhD’s in CS Education?” he answered (my paraphrase), “Sure, but we just hire CS PhD’s, and they’re smart enough to pick up anything on-the-fly.” No, that’s wrong. CS is not a superset of all other disciplines. That belief is exactly the problem I see in the below quoted piece. Scholars in other areas do know things that CS PhD’s don’t, and they bring something unique to the table. Believing that it’s all technology is exactly why Silicon Valley gets accused of being more interested in money than having actual positive impact.
One of the biggest problems in American education is that teachers have to teach 30 students with different learning styles at the same time. Developers at Facebook, however, have built an online system that gives teachers the information and tools they need to design individualized lessons. The result is that teachers can spend their time doing what they’re best at: inspiring kids.