Searching for a new driver for CS Education

The last couple of posts in this blog have generated some wonderful response posts.

• Alfred Thompson wrote a post about what leads to change in computing education. He makes some intriguing predictions about the future of computing education at the end of his post. (The tie to databases got me thinking.)  He agrees with me that, historically, the innovations which have taken root have grown from well-known institutions.  What I found most interesting was the back-and-forth Alfred sees (from his current post at Microsoft) between industry and academic influences on the tools of choice.
• Leigh Ann Sudol wrote a response to Alfred which reflected her frustration with the where the influences are coming from. I strongly agree with her greater goal: “We need to stop arguing about language, tools, etc. and decide what it means for the AVERAGE American to be literate in computing.” She concludes with the economic concerns she sees which limit computer science in secondary education.
• Ian Bogost’s post is in line with Leigh Ann’s, in that he decries the influences on computing education, but he goes further to see it as indicative of an illness within computer science overall. “[O]verall, computing simply doesn’t care about the development of its ideas. It fantasizes itself as a scientific or an engineering discipline, but throws the baby out with the bathwater (even the purest of sciences acknowledges that its ideas arise from the complex flows of history).”  Ian wants computing educators to engage in learning methods that recognize computing as a liberal art (an argument I agree with, and have also made, though not nearly as eloquently).

All three of these posts are, in a sense, complaining about what is driving computing education.  I wrote my original post as a reflection on what has driven change in the past — purely an historical analysis.  The response we’re reading here is, “But that’s not what should drive change in how and what we teach.” Are these influences unique to computer science?  Leigh Ann and Ian call on Biology and Mathematics, respectively, as offering alternative models.  Computing may be more driven by industry than some other fields, but I suspect that these drivers are broader than just computer science.

How do we change what influences our practice?  I’m a fan of Larry Cuban’s work, particularly, “How Scholars Trumped Teachers.”  Cuban analyzes the last 100 years of American Universities and concludes that research wins over teaching.  American universities are set-up so that research and all that goes with it (e.g., focus on funding, publication, and creation of intellectual property) will always dominate attention to education.  Change is possible, but we may have to change our underlying assumptions about what the American University is and what it means, and then change the structure to match the new beliefs.

The Economics of Computing Education

Economics is a fascinating field.  It’s psychology-of-masses, a form of psychological engineering, and the closest thing we have to Hari Selden’s psychohistory (from Asimov’s Foundation series).  It’s a study of how people make choices in order to maximize their benefit, their utility.  It is not only about money–money is just a way of measuring value, about some common sense of the potential of some consumable for providing utility.  I’ve been reading more economics this summer, and that’s got me thinking about what economic theory might have to say about computing education.

Students, especially in undergraduate education, are clearly economic decision makers.  They choose their classes.  That isn’t to say that they are our customers whose wants we must meet.  It means that we provide consumables (classes) under various rule sets, and the students seek to maximize their benefit.

What students want from higher education (that is, what utility the classes are meant to provide) these days isn’t in much doubt.  Most studies of higher education that I’ve read suggest that a big change occurred in the 1970’s, and that since then, over 90% of incoming students in higher education are attending higher education in order to get a better job and improve their socioeconomic class. There is some evidence that suggests that students, by the time they are in their fourth year, they value education for its own sake more.  Students in their first years, on the whole, make choices based on their job prospects.

We’ve talked in this blog about why a student should study computer science.  One argument is because of the value of computing as a field and the insights that it provides.  Smart students will probably recognize that learning computing for those reasons will result in greater utility over the long run.  How do we get students to see value, to receive benefit from what we know will help them more in the long run?  Is it possible to teach students new and better utility functions?  Can we help students to realize the greater utility of valuing knowledge, even from their first years in higher education?  That’s an interesting question that I have not seen any data on.

What if we simply say, “This is the way it is.  I’m teaching you this because it will be the best for you in the long run”?  Paul Romer’s work on rule sets has been describing how the rules in effect in a country or a company can encourage or discourage innovation, and encourage or discourage immigration and recruitment. He would point out that higher education is now a competitive market, and deciding to teach for what the students should value is creating a set of rules.  Students who don’t value those rules will go elsewhere.  Those students who say will probably succeed more, but the feedback loop that informs us in higher education that we’re doing the right thing doesn’t currently exist.  Instead, we simply have lower enrollments and less tuition–not the right feedback.

It’s that last part, about the feedback on teaching, that I have been specifically thinking about in economic terms.  Malcolm Gladwell wrote a fascinating New Yorker piece last December about the enormous value of having a good teacher.  What makes for a good teacher?  Maybe those who create effective rule sets, who create incentives for student success?  What provides utility for teachers?  How do we make sure that teachers receive utility for good teaching?

How do we recognize and reward success in teaching?  I listened to a podcast of a lecture by William Wulf who points out how badly we teach in engineering education.  In economic terms, that’s not surprising. I don’t know of research into what university teachers value in terms of teaching. What is the utility function for a higher-education teacher, a faculty member?  Job prospects and tenure are based on publication, not teaching, at least in research universities.  When we do evaluate teaching, how do we do it?

• By measuring learning?  We’ve already pointed out in this blog how very hard it is to do that right.  Teachers use examinations and other forms of assessment.  Are they measuring the right things?  The research that I’ve seen suggests that grades are only rough measures of learning.  If we were going to measure learning as a way of rewarding faculty to incentivize better teaching, we need some external measure of learning apart from grades, and we need that measurement to be meaningful — that it reflects what we really value in student learning.
• By measuring student pass rates?  Wulf might say, “If only!”  He points out that correcting our 50% dropout rate in engineering (and computing!) education would alone dramatically improve our enrollment numbers.  Would we be dumbing down our education offerings?  Honestly, how would we know (see previous bullet)?
• Instead, we most often just ask the students.  ”Was this a good class? Was this teacher a good teacher?”  This gets back to student as consumer, which is a step beyond decision maker.  Are they the right ones to make this determination?  Is the end of the class the right time for a student to be able to evaluate if the class was worthwhile?

Higher education teaching will probably improve once we figure out how to give reasonable feedback on teaching quality which could then impact teachers’ perception of benefit or utility.  As Gladwell and Wulf point out, getting it right would have a dramatic improvement on student quality and enrollment.

Looking for Excuses to Do Something Good

David Klappholz sent me a link to an article in Sunday’s New York Times (early enough that I was able to purchase that issue and read it on my Kindle — cool!) on how the grants system in cancer research favors incremental progress over revolutionary process. David suggested that perhaps NSF is a target for similar complaints, like in those I was responding to in a recent blog post.  I think the NYT article is pointing out a different set of problems than those I was responding to earlier, and I do think that the NYT points are well-taken.  The NYT article points to general problems of how research and higher-education work today.

My colleague, Blair MacIntyre, stopped me yesterday to tell me about a cool new class he wants to build.  He wants to create a class that becomes an excuse for students to do something good.  He doesn’t want the class to have explicit learning objectives or a set curriculum.  Rather, it’s a commitment for a student to produce a great game (in this particular case) to add to their portfolio.  It’s too easy to give up a cool idea when things get hard.  Blair’s idea is for students to sign up for this course, and then have to complete the course (i.e., build the game that she committed to building) despite the midterms and pressures from other courses that arise.

Blair’s idea brought to mind a message that I got from Alan Kay (to whom I still owe a complete response — sorry, Alan!) asking (paraphrased), “This new computing education organization — will it actually lead to computing education reform?  Will it lead to something really good?”  And my response was (paraphrased), “Probably not.”  The new computing education organization is important in terms of gathering momentum in a common direction and developing infrastructure, which are good things.  The new organization is not going to lead to transformative new ideas in curriculum, or to new kinds of tools that build on how students understand and need to understand computing.

And that brings me back to David’s article.  Higher education is an ecosystem, if not a business.  Money needs to keep pumping through to keep the system running, and it’s important to keep the system running.  The demands to bring money into this system via grants are increasing.  I’m personally dealing with the expectation from my School that I bring in four months of my own salary from grants each year, and the NSF new rule that they will only pay two months of salary for any faculty member, thus requiring me to find new sources of funding.  There are lots of faculty seeking grant money for similar reasons.  Thus, with more people requesting money, and increasing need for that money, the tendency is to become more and more conservative — greater demands from review panels for proof that the project will be successful, which leads to smaller increments of “success.”  It’s pretty hard to assure a review panel that something transformative or revolutionary will really work.

So, when do university researchers get the chance to do good work, the work that might cure cancer or find new ways to improve student understanding of computing?  There’s more demand to get grants, and the grant process does prefer incremental success rather than transformative.  Faculty are expected to also be involved in the committees and infrastructure work which address issues of students and policy.  How do we create the excuses to do something good?  They’re probably not going to come from the grants process.  The projects in which I’ve been involved that I think are the most successful were pretty much all unfunded at their start.  These were things that were worth doing, and we decided that they were worth getting into trouble by not doing the things that we were expected to be doing.  That’s risky and harder to do as pressures for faculty productivity increase.  We need to find ways of creating excuses for doing good work.

Computing For Evil! Isn’t Education a “Good”?

Georgia Tech’s College of Computing offers a course “Computing for Good.”  Students in this class take on social activist projects, like creating kiosks to support Liberians in capturing video testimony after their civil war and creating web sites to help monitor blood supply quality.  These are terrific projects, and the context of social activism inspires student learning.  This class is part a global movement to include more activism in computing classes, like the Humanitarian Free and Open Source Software effort.

The title of this effort “Technology + Activism = Computing for Good” sends the wrong message.  Activism is taking direct (Wordnet says “militant”) action to cause social and political change.  That’s not the only kind of good that there is in a University, or even in a computer science department.

The point of a University is to be a common good.  The University serves to advance the interests of people.  Education is inherently about bettering people, which is good. Sometimes the service provided is longterm.  Knowing how to make systems more reliable or more easily maintained does people good, even if it is not about social or political change. A long term good is still “good.”

I am working with a student, Brian Landry, who is finishing up his dissertation this Summer.  Brian has been developing a tool to help people tell stories (not just chronological slide-shows) with their digital pictures.  I’m loving reading the quotes from the people creating and viewing these stories.  Authors talk about their reflections about their lives, and how the process of creating these stories changes how they think about their experiences. Viewers talk about getting new insights into the authors.  I am no philosopher, so my view may be naive or ill-informed. I think getting people to come to new understandings of themselves and others is inherently “good,” but is probably not considered “activism.”

I worry about the message this “Computing for Good” sends to students.  I hear bits and pieces of talk from students getting involved in these projects and those who are considering other projects.  Work in “education” is not typically considered part of the “for Good” effort.  It’s not activism, it doesn’t result in immediate and dramatic impacts, and it rarely gets picked up on CNN or in the New York Times.  Universities (and its students) should not give up on long-term value in favor of short term press coverage.

One of my colleagues has taken on the Twitter monicker “computing4evil.”  If we’re not “good,” then are we “evil”?  We’re thinking about making up t-shirts, “The League of Evil Computationalists.”  Of course, this is all tongue-in-cheek.  The project “Computing for Good” is doing great good for people who can use the help.  Putting labels on projects that some are “good,” however, is dangerous.  Everything at a University should wear that label, or something is wrong with our notion of the University.

The Public Perception of the University

A mismatch between the public’s view of faculty and the faculty’s view of themselves.