Graduate Tuition Support at NSF

One thing that I didn’t know, before I came to NSF in 2014 was that support for graduate student research assistants as part of regular research grants includes tuition support that is not capped. According to this NSF FAQ:

Tuition remission is generally treated as part of an organization’s fringe benefit rate or as a direct cost. NSF’s policy is that colleges and universities should budget tuition remission consistent with its established indirect cost rate methodology and negotiated rate agreement. If tuition remission is budgeted as a direct cost, it should be listed in the “Other” category of the Budget under “Other Direct Costs.

Note that there is nothing about a cap in the above guidance.

In contrast, NIH does cap tuition support for graduate research assistants at around $16K. Here is the relevant NIH policy:

Undergraduate and Predoctoral Trainees and Fellows:  For institutional training grants (T32, T34, T35, T90, TL1, TL4) and individual fellowships (F30, F31), an amount per predoctoral trainee equal to 60% of the level requested by the applicant institution, up to $16,000 per year, will be provided.

This difference between the two science agencies is trivial for a lot of cases, were graduate students are paying in-state tuition at a public university. You can find some of the relevant data from the College Board here. However, in the case of some of the private research universities, this can be a very large amount of money. Here is the relevant tuition information for Princeton. And here in the same for Boston University. Even for public institutions, the out-of-state tuition can be very large in comparison to $16K (Rackham graduate school, University of Michigan).

Taken to its logical conclusion, NSF risks becoming a tuition-support agency instead of a science agency as tuition costs continue to rise across the country. This makes no sense. NSF should cap tuition support just like NIH does.

Chinese Super-Science

Robert Samuelson has an op ed piece in today’s WAPO on how China has become a science superpower. The piece was timed with the release of NSF’s Science Indicators annual report (currently unavailable due to the government shutdown). I was last in China six years ago and it was clear even then that the Chinese were aiming, not just to become a peer of the US, but to exceed it in all areas of science and technology. Since that visit, we have seen the Chinese leap forward in Astronomy (the largest radio telescope), quantum computing (the world’s only satellite-based quantum encryption system), biomedical research (clinical studies that have statistical power far beyond those in the west) and even ecology (with their distributed environmental sensor network).

At the same time, US investments in science and technology have been quite stagnant. For Fiscal Year 2018, President Trump proposed an 11% cut to the NSF. He proposed an even larger cut of 22% for the NIH. These proposed cuts follow years of essentially flat funding during the Obama administration.  From a GDP perspective it’s even worse! Countries like South Korea, Germany and Japan made larger investments in science relative to their economy size.

If this trend continues, China will become the essential nation from a science perspective. And the geo-political consequences of that could be dire. Leading in science historically has led to non-incremental advances that create strategic surprise (e.g. nuclear weapons, the Internet, lasers). Imagine a US President being told that our spy satellites have been hacked leaving us blind to missile launches. Or that the location of our nuclear submarines was now available in real time to our global competitors?

What can be done? For one thing, it’s useful to remember that in the process of creating a budget, the President proposes, but Congress disposes. It is essential to reach out to members of Congress and let them know how important science is to the security of this country. But even more importantly, it’s time to open the channels of communication between those who are skeptical of the value of science investment and science advocates (including practitioners). In a recent conversation with one of this country’s most prominent science advocates, it became clear to me that science has taken on a political label that is not helpful. Science should not be political. Otherwise, it will become just another special interest in the eyes of its stakeholders. And the future of science is too important for that fate.

Tracking investments in graduate education

During my time leading the Biological Sciences Directorate at NSF, I learned that the agency spends around a billion dollars a year on graduate education—the training that is required after the undergraduate degree to turn an aspiring scientist into a true discoverer. Of that money, roughly 15% is spent on NSF’s flagship graduate research fellowships—a fantastic program that’s been around since the 1950’s and has played a central role in the early careers of many of the US science superstars. These are folks who have gone on to win Nobel prizes and the like. Winning these fellowships involves an intense competition of ideas and is peer-reviewed by the science community. I’m pleased that NSF tracks the career trajectory of these trainees pretty carefully. There is hard evidence that the graduate research fellowship program works.

Another 5% of the total is spent on trainee grants—the current version of these are the National Research Traineeships. These are training awards that go to universities which then award the support to graduate students that they select. I was trained under such a program (although it was NIH funded) when I was at the University of Michigan training in neuroscience. These are excellent funding programs and once again those folks who are supported in this way are tracked pretty carefully (I still get contacted regularly by the NIH asking what I’m up to).

But the vast majority, 75%, of what the NSF invests in graduate education is untracked. These embedded in the dollars that go to research grants of scientists at US universities who then hire graduate student research assistants to actually do the work. We don’t know what happens to these trainees. There simply is no easy way at getting at the data.

In strikes me as unwise to make such a large investment without getting feedback on how things are going. In particular, I am concerned that those graduate students are being inadequately mentored in some pretty substantive ways. For example, I fear that they are too often treated as an extra pair of hands rather than a future professional colleague. Time spent teaching these students about career options or how to effectively teach undergraduate students is time away from the laboratory bench.

There are ways of tracking such students. One such mechanism is the orcid id system. There are others. If all students supported by the NSF were required to be registered in such a system, then it would be possible to track their career easily (as long as they stayed in science). But success on that front requires one other thing: that journal publishers and data repository sites require that a person’s id be attached as meta-data to every single piece of scientific data from the results of a single bench top experiment or a field observation all the way to a finished journal article.

This is not impossible. I think it is important to move this direction because it will allow for evidence based decisions about how to optimize NSF’s graduate student support in the future.