I was surprised to see the numbers quoted below. PhD unemployment is that high? Aman Yadav just pointed me to an article in The Atlantic, with even more depressing news about the number of years to PhD, the debt after PhD, and the percentage of unemployment — see here.
CS is grouped into Engineering, so I tried to find the stats just on CS PhD’s. The 2014 Taulbee survey (see link here) says “The unemployment rate for new Ph.D.s again this year was below one percent.” But goes on to say, “The fraction of new Ph.D.s whose employment status was unknown was 19.7 percent in 2013-14; in 2012-13 it was 20.8 percent. It is possible that the lack of information about the employment of more than one in six graduates skews the real overall percentages for certain employment categories.” It’s not clear that we know what happens to new CS PhD’s, and what the real unemployment rate is.
Percent of Doctorate Recipients With Job or Postdoc Commitments, by Field of Study
Field 2004 2009 2014
All 70.0% 69.5% 61.4%
Life sciences 71.2% 66.8% 57.9%
Physical sciences 71.5% 72.1% 63.8%
Social sciences 71.3% 72.9% 68.8%
Engineering 63.6% 66.8% 57.0
Education 74.6% 71.6% 64.6%
Humanities 63.4% 63.3% 54.3%
So what does convince people about a need to change? Stories? Personal experiences? Poking around on the Web, you can find lots of pages about motivating change and salesmanship, but I’m more interested in the question of how do we get people to recognize the Platonic cave. What they think is true is measurably and provably not true.
Now, a new study published by the Proceedings of the National Academy of Science (PNAS) shows another level of bias: Many men don’t believe this is happening.When shown empirical evidence of gender bias against women in the STEM fields, men were far less likely to find the studies convincing or important, according to researchers from Montana State University (MSU), the University of North Florida, and Skidmore College.
I’ve raised the concern before that the CS for All effort might mean “CS for only the rich” (see post here). Our data from Georgia suggest that few students are actually getting access to CS education, even if there is a CS teacher in the school (see post here). Kathi Fisler, Shriram Krishnamurthi, and Emmanuel Schanzer offer a Blog@CACM post where they consider how we make sure that #CS4All is equitable.
Mandating every child take a computing class is a great way to ensure everyone takes CS, but very few states, cities, or even school districts are in a position to hire enough dedicated CS teachers or offer dedicated CS classes to reach every child. Recent declarations from several major districts that “every child will learn to code” often place impossible burdens on schools. Similarly, few schools can afford to offer CS programs that require cutting-edge computers, expensive consumables, or technology that requires significant maintenance.
To truly achieve CS4All Students in a sustainable way, equity and scale are issues that must be built in by design. Similarly, initiatives have to think about differently-abled users from scratch, not just bolt them on as an afterthought. Accessibility needs to be designed into software, curriculum, and pedagogy from the earliest stages.
The “move fast and break things” culture of computing is no help here. Right now, computing education has enormous attention. That day will pass. By the time we get around to focusing on equity, we may have depleted the energy left to overhaul computing curricula. Instead, we have to think this through at the very outset. Another computing principle is that products typically get one shot at gaining users’ attention. For the foreseeable future, this is that one shot for computing education.
The ICER 2016 Doctoral Consortium provides an opportunity for doctoral students studying computing education to explore and develop their research interests in a supportive workshop environment with a panel of established researchers. We invite students to apply for this opportunity to share their work with students in a similar situation as well as senior researchers in the field.
Applicants to the Doctoral Consortium should have begun their research, but should not have completed it. We want people who have questions to raise with their peers and the more senior mentors, and who still have time to respond to and use the feedback in their research.
DC Co-Chairs for 2016:
Anthony Robins, University of Otago, New Zealand
Ben Shapiro, University of Colorado, USA
Contact us at: firstname.lastname@example.org
The DC has the following objectives:
- Provide participants a supportive setting for feedback on their research
- Offer participants comments and fresh perspectives from outside their own institution
- Promote the development of a supportive community of scholars
- Support a new generation of researchers with information and advice on research and academic career paths
- Contribute to the conference goals through interaction with other researchers and conference events
The DC will be held on Thursday, September 8, 2016 (prior to the main ICER conference, in Melbourne, Australia). Students at any stage of their doctoral studies are welcome to apply and attend. The number of participants is limited to 15. Applicants who are selected will receive a limited partial reimbursement of travel, accommodation and subsistence (i.e., food) expenses of $600 (USD). An extra $200 may be available for participants with travel expenses greatly exceeding the standard support.
- Friday 20th May – initial submission
- Friday 3rd June – notification of acceptance
- Friday 17th June – camera ready copy due
You can find more information on applying athttps://icer.hosting.acm.org/icer-2016/doctoral-consortium/
Top business leaders, 27 governors, urge Congress to boost computer science education – The Washington Post
I saw on Facebook that Hadi Partovi was at Congress. Now I see why — there’s an effort underway to get Congress to fund more in CS education. I’m wondering what they want to get funded. Incentives for teachers? Professional development? Pre-service education? Does someone know the details?
Despite this groundswell, three-quarters of U.S. schools do not offer meaningful computer science courses. At a time when every industry in every state is impacted by advances in computer technology, our schools should give all students the opportunity to understand how this technology works, to learn how to be creators, coders, and makers — not just consumers. Instead, what is increasingly a basic skill is only available to the lucky few, leaving most students behind, particularly students of color and girls.
How is this acceptable? America leads the world in technology. We invented the personal computer, the Internet, e-commerce, social networking, and the smartphone. This is our chance to position the next generation to participate in the new American Dream.
I enjoy reading “Gas station without pumps,” and the below-quoted post was one I wanted to respond to.
Two of the popular memes of education researchers, “transferability is an illusion” and “the growth mindset”, are almost in direct opposition, and I don’t know how to reconcile them.
One possibility is that few students actually attempt to learn the general problem-solving skills that math, CS, and engineering design are rich domains for. Most are content to learn one tiny skill at a time, in complete isolation from other skills and ideas. Students who are particularly good at memory work often choose this route, memorizing pages of trigonometric identities, for example, rather than learning how to derive them at need from a few basics. If students don’t make an attempt to learn transferable skills, then they probably won’t. This is roughly equivalent to claiming that most students have a fixed mindset with respect to transferable skills, and suggests that transferability is possible, even if it is not currently being learned.
Teaching and testing techniques are often designed to foster an isolation of ideas, focusing on one idea at a time to reduce student confusion. Unfortunately, transferable learning comes not from practice of ideas in isolation, but from learning to retrieve and combine ideas—from doing multi-step problems that are not scaffolded by the teacher.
The problem with “transferability” is that it’s an ill-defined term. Certainly, there is transfer of skill between domains. Sharon Carver showed a long time ago that she could teach debugging Logo programs, and students would transfer that debugging process to instructions on a map (mentioned in post here). That’s transferring a skill or a procedure. We probably do transfer big, high-level heuristics like “divide-and-conquer” or “isolate the problem.” One issue is whether we can teach them. John Sweller says that we can’t — we must learn them (it’s a necessary survival skill), but they’re learned from abstracting experience (see Neil Brown’s nice summary of Sweller’s SIGCSE keynote).
Whether we can teach them or not, what we do know is that higher-order thinking is built on lots of content knowledge. Novices are unlikely to transfer until they know a lot of stuff, a lot of examples, a lot of situations. For example, novice designers often have “design fixation.” They decide that the first thing they think of must be the right answer. We can insist that novice designers generate more designs, but they’re not going to generate more good designs until they know more designs. Transfer happens pretty easily when you know a lot of content and have seen a lot of situations, and you recognize that one situation is actually like another.
Everybody starts out learning one tiny skill at a time. If you know a lot of skills (maybe because you have lots of prior experience, maybe because you have thought about these skills a lot and have recognized the general principles), you can start chunking these skills and learning whole schema and higher-level skills. But you can’t do that until you know lots of skills. Students who want to learn one tiny skill at a time may actually need to still learn one tiny skill at a time. People abstract (e.g., able to derive a solution rather than memorize it) when they know enough content that it’s useful and possible for them to abstract over it. I completely agree that students have to try to abstract. They have to learn a lot of stuff, and then they have to be in a situation where it’s useful for them to abstract.
“Growth mindset” is a necessity for any of this to work. Students have to believe that content is worth knowing and that they can learn it. If students believe that content is useless, or that they just “don’t do math” or “am not a computer person” (both of which I’ve heard in just the last week), they are unlikely to learn content, they are unlikely to see patterns in it, and they are unlikely to abstract over it.
Kevin is probably right that we don’t teach problem solving in engineering or computing well. I blogged on this theme for CACM last month — laboratory experiments work better for a wider range students than classroom studies. Maybe we teach better in labs than in classrooms? The worked examples effect suggests that we may be asking students to problem solve too much. We should show students more completely worked out problems. As Sweller said at SIGCSE, we can’t expect students to solve novel problems. We have to expect students to match new problems to solutions that they have already seen. We do want students to solve problems, too, and not just review example solutions. Trafton and Reiser showed that these should be interleaved: Example, Problem, Example, Problem… (see this page for a summary of some of the worked examples research, including Trafton & Reiser).
When I used to do Engineering Education research, one of my largest projects was a complete flop. We had all this prior work showing the benefits of a particular collaborative learning technology and technique, then we took it into the engineering classroom and…poof! Nothing happened. In response, we started a project to figure out why it failed so badly. One of our findings was that “learned helplessness” was rampant in our classes, which is a symptom of a fixed mindset. “I know that I’m wrong, and there’s nothing that I can do about it. Collaboration just puts my errors on display for everyone,” was the kind of response we’ve got. (See here for one of our papers on this work.)
I believe that all the things Kevin sees going wrong in his classes really are happening. I believe he’s not seeing transfer that he might reasonably expect to see. I believe that he doesn’t see students trying to abstract across lower-level skills. But I suspect that the problem is the lack of a growth mindset. In our work, we saw Engineering students simply give up. They felt like they couldn’t learn, they couldn’t keep up, so they just memorized. I don’t know that that’s the cause of the problems that Kevin is seeing. In my work, I’ve often found that motivation and incentive are key to engagement and learning.
At the end of LaTICE 2016, the Vice-Rector of Al-Baha University in Saudi Arabia (see information here) welcomed attendees to LaTICE 2017. After the presentation about Al-Baha University, Sahana Murthy of IIT-Bombay stood up and asked, “Can I come to LaTICE 2017 dressed as I am right now, in Indian clothes?” The Vice-Rector replied, “No.” All women, including foreigners, will be required to cover their hair at LaTICE 2017.
That exchange was a central topic of conversation for the rest of the conference and in social media for me. I heard some female computing education researchers say that they would attend anyway. Many I heard from expressed outrage. Several were angry that the organizing committee for LaTICE would even place the conference in Saudi Arabia under these restrictions.
I spoke to Neena Thota about LaTICE 2017 (seen below after my keynote). She was one of the Chairs for LaTICE 2016 (faculty at Uppsala University and University of St. Joseph in Macau) who went to Saudi Arabia in preparation for the conference. She felt respected there and taken seriously as a scholar, but she did have to cover-up. Neena doesn’t expect that the rules for women in Saudi Arabia (see the Wikipedia page here about them) will change for a long time. Do we simply ignore the scholars there and ostracize them, for rules over which they may have no control? As in Qatar, computer science students in Saudi Arabia are majority female.
The question is no longer rhetorical for me. I was invited to attend the Program Committee meeting at LaTICE 2016 as a non-voting observer, and I have been invited to serve on the PC for LaTICE 2017. I have already had several people warn me that I should not participate. They urged me to shun the conference publicly, in order to send a clear message against the treatment of women in Saudi Arabia.
I’ve been thinking about this, and discussing it with women in my life (my wife, my daughters, and my colleagues). I’m not female, and I can’t fully understand my own biases as a male, so I sought advice from women in my life and very much appreciate all the comments I received. I’ve decided that I will serve on the LaTICE 2017 program committee.
I understand the reasons of anyone who chooses not to participate. Those who choose not to review are sending a message that LaTICE should never have gone to a place that restricts the rights of women. I can understand why women, especially from the West, might choose not to attend. I don’t think foreign women should go there, unless they’re willing to abide by the laws and customs of the place they’re visiting.
Here are my reasons for thinking it worthwhile to engage in LaTICE 2017:
- The female Computing students and faculty in Saudi Arabia might not otherwise be able to attend a conference like LaTICE. Unless LaTICE goes there, they do not get the opportunity to hear other perspectives, to share their practices, and to participate in a community of education scholars. By participating in the PC, I get to share what I know about computing education with the community of scholars in Saudi Arabia, both female and male.
- As an education researcher, I know that learning and change occurs from active dialogue, not from passive silence. I doubt that I can change much in Saudi Arabia, either by my engagement or my public refusal to engage. This semester our seminar on Learning Sciences and Technologies at Georgia Tech read Paulo Freire’s Pedagogy of the Oppressed. Freire points out that privileged people can’t solve the problems of the less-privileged, nor can the privileged even “help” the less-privileged. All that any of us can do is to create dialogue which creates opportunities for learning for everyone. Freire explicitly includes teachers in that everyone. Teachers ought to aim to learn from students. Dialogue requires engagement. Reading papers and responding to them with my comments creates dialogue.
- Finally, I want to be engaged because of what I will learn. I’m curious. I learned more about India from attending LaTICE 2016 (see the first and second blog posts in this series). I would like to learn more about Saudi Arabia. It makes me a more informed and effective researcher when I am more aware of other contexts.
Neeti Pathak, one of the students with whom I work, pointed out that there is interplay between religion and culture in Saudi Arabia. I also look to my own faith in thinking about LaTICE 2017. Pope Francis, the leading figure in my faith, recently made a proclamation encouraging the Church to be more welcoming, even to those that the Church may have once ostracized (see NYTimes piece). That’s a proclamation that relates to LaTICE 2017. Everyone gains by engaging, even with those whose activities and rules we might not like.
I’m not willing to ostracize a whole country, even if they have rules and customs that I think are wrong. I’m not confident that I understand the issues in Saudi Arabia. I’m not confident that my views on them are more than my Western biases interpreting customs and values I don’t understand. I don’t feel justified in making a statement against LaTICE 2017. I see value in engaging in dialogue.
I shared earlier versions of this post with several colleagues, who are angry with me for the stance I’m taking. These are complicated issues. I am sure that there are many more perspectives that I have not yet considered. I welcome further discussion in the comments, including telling me why I’m wrong.