How can we break the cycle of deadline-driven research? In computer science, there has been a growing trend in the past decade or so for researchers to publish in workshops and conferences in order to increase the length of their publication list. This situation is especially true of junior faculty, worried about getting tenure; graduate students, worried about getting job interviews; and now even undergraduates, worried about getting into graduate school. In promotions and tenure committee meetings at some schools, discussion of the number of papers can overshadow discussion of the quality and impact of the candidate’s work.
We have successfully trained deans and provosts that, in computer science, papers in premier conferences count as much as or more than papers in journals. So, the pressure to publish in conferences is even that much more intense. And presumably the more the better. To accommodate the research capacity of our field, new workshops and conferences (and journals) proliferate, resulting today in extensive Web sites maintaining double-digit rankings of conferences. It is now common practice to see the conference success rate included with each publication listed on a candidate’s résumé. (I will not repeat the cogent arguments that others have given on the subject of journals vs. conferences, published in Communications,1,,3 but they are relevant to this topic as well.)
We are now in a state where our junior faculty are mentoring graduate students with this deadline-driven approach to research. It’s the only value system they know and they are passing it onto the next generation. When one of my own graduate students, after we agreed that we would submit a journal version of our conference paper, said to me, "Jeannette, the author guidelines for Journal X don’t specify a page limit," I knew something was very wrong with our current culture in computing. We are now in a state where the common thought-chunk of research is a 12-month effort that fits in 12 pages.
We, as faculty advisors, are in a bind: Do we say to our student, "Yes, go ahead and submit to that conference [whose due date is looming]" or "No, don’t waste your time writing for that conference. Your work is not ready. Spend the time developing the work"? Do we give in to the peer pressure our students feel, making them potentially less competitive when they are on the job market? We need to promote a culture that encourages faculty and student researchers to take the time needed to work out their ideas so that when they feel ready, they can submit based on the import of their contribution.
Moreover, conservatism tends to win out in program committees, when submissions are competing for a finite number of conference slots, and in panel reviews for funding agencies, when proposals are competing for finite resources. This attitude leaves less room for the bold, creative, risk-taking, visionary ideas, especially those that are not fully fleshed out with all the i’s dotted and t’s crossed. Note that I have nothing against conferences: they are important for the expeditious exchange of technical ideas, as well as networking among researchers and between academia and industry. I have nothing against (high-quality) incremental research: some research agendas are long-term in vision, but rely on making progress step by step, building on prior research results.
The consequences of this deadline-driven research are potentially bad for the field. Our focus should be on the quality of the research we do. Our goal should be advancing the frontiers of science and engineering.
So how can we break this cycle? One place to start is with the department heads. At hiring time, among other factors, we should look for a candidate’s big idea (or two), not number of publications. In mentoring junior faculty, we need to stress the importance of quality and impact. At faculty evaluation time, we should promote and grant tenure based on quality and impact.
Hopefully, we in the community can at least start a dialogue on this topic. It is for the good of our field—to keep it healthy, exciting, and vibrant.
Reader’s comment
A key challenge that our community needs to address is how to detect, from an ocean of papers, the key innovative ones that need to be widely distributed. The new Communications is a very good step in this direction, but I think that Communications will not be sufficient and we’ll need innovative techniques to efficiently and quickly detect the most innovative papers in each CS subfield.
—Olivier Bonaventure
From Mark Guzdial’s "CS Faculty Cause Inequality"
An article in the Sept. 8, 2009 edition of the New York Times argues that "Colleges Are Failing in Graduation Rates." Specifically, the article claims "[t]he United States does a good job enrolling teenagers in college, but only half of students who enroll end up with a bachelor’s degree. Among rich countries, only Italy is worse. That’s a big reason inequality has soared, and productivity growth has slowed."
That’s a strong claim, that the failing rates in college are actually causing inequality. This isn’t the first time the Times has made this argument, though. The first time I read the claim that higher-education faculty are a significant cause of the widening gap between the haves and have-nots was in a column in 2005 by David Brooks of the New York Times. He explicitly argued that colleges, rather than being a ladder to improving one’s life, are actually reducing the opportunities for the poor. Brooks wrote:
"As you doubtless know, as the information age matures, a new sort of stratification is setting in, between those with higher education and those without. College graduates earn nearly twice as much as high school graduates, and people with professional degrees earn nearly twice as much as those with college degrees. But worse, this economic stratification is translating into social stratification. Only 28% of American adults have a college degree, but most of us in this group find ourselves in workplaces in social milieus where almost everybody has been to college… The most damning indictment of our university system is that these poorer kids are graduating from high school in greater numbers. It’s when they get to college that they begin failing and dropping out. Thomas Mortenson of the Pell Institute for the Study of Opportunity in Higher Education has collected a mountain of data on growing educational inequality. As he points out, universities have done a wonderful job educating affluent kids since 1980. But they ‘have done a terrible job of including those from the bottom half of the family income distribution. In this respect, higher education is now causing most of the growing inequality and strengthening class structure of the United States.’"
"It’s easy to pick the ‘best and brightest’ who look like us, act like us, and learn like us. The challenge is to identify the students who are even brighter and better than us, but don’t look like us, act like us, or learn like us."—Mark Guzdial
CS faculty play a role in this phenomenon. No one who looks at CS1 failure rates could argue that CS doesn’t contribute to failing grades. Richard Tapia, in his forward to Jane Margolis’ Stuck in the Shallow End, makes the argument explicitly starting from his title, "Computer Science is Widening the Education Gap." He wrote:
"Over the years, I have developed an extreme dislike for the expression ‘the best and the brightest,’ so the authors’ discussion of it in the concluding chapter particularly resonated with me. I have seen extremely talented and creative underrepresented minority undergraduate students aggressively excluded from this distinction. While serving on a National Science review panel years back, I learned that to be included in this category you had to have been doing science by the age of 10. Of course, because of lack of opportunities, few underrepresented minorities qualified."
No one is arguing that we should not seek the actual "best and the brightest." The real question is how we make that determination and how we develop those students. It’s easy to pick the "best and brightest" who look like us, act like us, and learn like us. The challenge is to identify the students who are even brighter and better than us, but don’t look like us, act like us, or learn like us. With declining enrollment and a population of computer scientists who increasingly have the same gender and represent only a few ethnic groups, we must look beyond the simple definitions, find those terrific students whom we might have missed in our first glance, and help them to develop in the ways that best suit them.
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