Gas station without pumps

2014 June 26

What you do in college may matter more than where you go

Filed under: Uncategorized — gasstationwithoutpumps @ 00:48
Tags: , , , , ,

Back in May, I read a blog post (Life in College Matters for Life After College) that pointed to the Gallup-Purdue Index Report 2014. I finally got the time to download the report and look at it.

The report has a rather ridiculous interpretation of copyright on its copyright page: “It is for your guidance only and is not to be copied, quoted, published, or divulged to others.” This is particularly ridiculous for a report that they are distributing for free—I think that they have a piece of boilerplate that they put on all their reports, written by lawyers who want to claim far more that copyright law really provides.  They’ve got deeper pockets than me though, so the threat is effective—I won’t directly quote them in my blog, but just summarize what I see as the main points.  If I mangle their message, they have only their own over-zealous lawyers to blame.

What the report is ostensibly about is whether college prepares students for an “engaging” job and a good life.  They were looking for whether students were engaged in their jobs and at five measures of well-being that Gallup has used in other studies: purpose, social, financial, community, and physical. They were also looking at how attached alumni were to their alma maters (which, of course, is primarily what Purdue was interested in, as that determines how much money they can extract from alumni).

Basically, they started with the assumption that the point of college is to get a “great job” and a “great life” (a debatable point, but a widely held belief).  They then tried to determine what produced these outcomes, by interviewing 30,000 graduates.  Note that they did not interview those who quit or were kicked out of college—they were only considered those that college thought had succeeded.  It might be interesting for them to look at the outcomes for those who dropped or failed out also, to see whether the things they think mattered in college also affected the students who left without a degree.  (I suspect that the effects would be even stronger, because of the higher variance in the outcomes, but guessing about sociology is not one of my strengths.)

Their main result was that it didn’t really matter much where people went to college (other than that results were consistently worse at for-profit schools)—what mattered is what they encountered there.  Having an inspiring professor who cared about them, excited them about learning, and encouraged them doubled the odds of their being engaged at work after college. Internships in which they applied their learning, multiple-term projects, and being extremely active in extracurricular activities also doubled the odds of their being engaged at work.

(They use the term “odds” rather than “probability” consistently, so I’m not sure if they mean the probability p or the odds ratio \frac{p}{1-p}. If p is small, these are almost the same, but the overall engagement at work for college grads was reported as 39%, so it makes a difference here.  At one point in the report they mention that 40% of students finishing in 4 years or less are engaged in their jobs compared to 34% of those who took five and a half or more years, claiming that completing in 4 years doubles the odds of engagement.  I can’t come up with any definition of “odds” that makes this more than a 30% difference.)

I think that UCSC does manage to provide some engaging faculty—most of the students I talked to in senior exit interviews had at least one faculty member who excited them about learning (but that’s fairly common—63% of graduates reported that in the Gallup-Purdue survey).  I don’t know that we do as well at providing professors who show that they care about the students or providing mentors who encourage students to pursue their dreams—those are hard to provide at scale, as they rely on matching personalities as well as having enough faculty time to spend. Indeed, in the Gallup survey only about 27% of graduates felt that professors cared about them as a person and only 22% felt they had a mentor who encouraged them, so we’re not alone in finding this difficult to supply.  I suspect that students doing senior theses get more mentoring than those doing group projects, but a lot depends on the student and whoever is supervising the work.

One thing that the Jack Baskin School of Engineering at UCSC is doing right—all the students in bioengineering, computer engineering, electrical engineering, and computer game design are required to do 2-quarter or 3-quarter-long capstone projects.  (That alone should be a 1.8× on the odds of being engaged at work, and only 32% of students in the survey reported having that experience.)  Our students do not do so well on the “extreme extracurricular activity”, though, as few engineering students feel they have time for much in the way of extracurriculars.  Internships are something that UCSC could be much better at—there is a huge industry base only 40 miles away in Silicon Valley, but students are left on their own for finding internships, and not very many do.

The two strongest predictors of engagement were not really what the college did, but what students thought about the college:  if they thought “the college prepared me well for life outside college” or that the college was “passionate about the long-term success of its students”.  These raised the odds of engagement at work by 2.6× and 2.4× respectively. Causality is not clear here, as these attitudes may have resulted from their engagement at work, rather than being causes of it.

The report is very sloppy about confounding variables:  they report that women are more engaged at work than men, and that arts, humanities, and social science majors are more engaged than science or business majors.  But they don’t seem to have done anything to determine which of the two highly correlated variables is the causal one here: gender or major.  Their sample is large enough that they should have been able to get at least a strong hint, despite the correlation.

One unsurprising result: those who took out large loans as students were much less likely to be thriving in all 5 areas of well-being than those who took out small loans or no loans. Since financial well-being is one of the areas, and large loans make it difficult to achieve financial well-being, this is hardly a surprising result.  It would have been more interesting if they had reported differences in just the other four areas—did the large loans have any effects other than the obvious financial one?  They’ve got the data, but they didn’t do the analysis (or they’re not sharing it in the free report, which seems more likely—I’m sure they’ll share it for a hefty consulting fee).

Given that there was almost no difference in well-being based on public vs. private or selective vs. non-selective colleges, the big negative correlation of large loans with well-being sounds like a strong argument to go to a college you can afford, rather than taking out large loans. (Again, the report did not attempt to look at confounding variables for the for-profit schools—how much of their poor performance was due to the large loans they encouraged their students to take out?)

The results for alumni attachment were much stronger than for well-being or job engagement, probably because the background level of alumni attachment was fairly low—only about 18% of college graduates were emotionally attached to their colleges by the criteria used in the poll.  The biggest drivers for emotional attachment were whether they felt the college had prepared them well and whether they felt it was passionate about the long term success of the students.  Again, I question the causality here—it seems likely that those who are emotionally attached are more likely to hold these beliefs, irrespective of what the college actually did.

I’m also confused by their “odds” again, where they report 48% of a group being emotionally attached as 6.1× the odds of another group where 2% are emotionally attached.  I don’t see how they computing their “odds”—it is a very odd computation indeed! Update: perhaps the odds they mean are \frac{p(x | y)}{p(x | \neg y)}, in which case they are comparing the 48% to some unprovided number, probably a little lower than the background 18%.  I’m still having a hard time making that 6.1.  Maybe \frac{p(x | y)(1-p(x|\neg y))}{(1-p(x|y))p(x | \neg y)}?  I can’t seem to make anything match their numbers.

Although the basic conclusion of the study seem reasonable to me (that what happens to you in college is more important than where you go to college, and that large loans make you miserable), the survey seems rather sloppily done, confusing correlation with causality, not attempting to disentangle confounding variables, and doing some sort of arithmetic that seems completely inconsistent so that the “odds” they report are incomprehensible. Also, they asked few questions and every question they asked seemed to have about the same effect on the odds, so I don’t know whether the survey was actually measuring anything (no negative controls).

I’d hesitate to invest money or make academic planning decisions based on this report.  I think that Purdue wasted a lot of money on a load of crap (unless they got a private report with a lot better data and analysis).

 

2014 March 13

Suggestions for changes to biomed training

Filed under: Uncategorized — gasstationwithoutpumps @ 09:56
Tags: , , , , ,

Yesterday I attended a a discussion lead by Henry Bourne (retired from UCSF) about problems in the training system for biologists in the US.  His points are summarized fairly well in his article A fair deal for PhD students and postdocs and the two articles it cites that preceded it:

In a recent essay I drew attention to five axioms that have helped to make the biomedical research enterprise unsustainable in the US (Bourne, 2013a). This essay tackles, in detail, the dangerous consequences of one of these axioms: that the biomedical laboratory workforce should be largely made up of PhD students and postdoctoral researchers, mostly supported by research project grants, with a relatively small number of principal investigators leading ever larger research groups. This axiom—trainees equal research workforce—drives a powerful feedback loop that undermines the sustainability of both training and research. Indeed, unless biomedical scientists, research institutions and the National Institutes of Health (NIH) act boldly to reform the biomedical research enterprise in the US, it is likely to destroy itself (Bourne, 2013b).

I’m basically in agreement with him that very long PhD+postdoc training current in biology in the US is fundamentally broken, and that the postdoc “holding tank” is not a sustainable system.

I also agree with him that one of the biggest problems in the system is paying for education through research grants. Grad student support should be provided directly, either as fellowships or training grants (I prefer individual fellowships like the NSF fellowships, he prefers training grants). By separating support for PhD training from research support, we can effectively eliminate the conflict of interest in which students are kept as cheap labor rather than being properly trained to become independent scientists (or encouraged to find a field that better fits their talents). By limiting the number of PhD students we can stop pumping more people into the postdoc holding tank faster than we can drain the tank by finding the postdocs real jobs.

I disagreed with one of his suggestions, though. He wants to see the PhD shrunk to an average of 4.5 years, followed by a 2–4-year postdoc. I’d rather keep the PhD at 6.5 years and eliminate the postdoc holding tank entirely. In engineering fields, researchers are hired into permanent positions immediately after their PhDs—postdoc positions are rare.  It is mainly because NIH makes hiring postdocs so very, very “cost-effective” that the huge postdoc holding tank has grown. If NIH changed their policies to eliminate support for postdocs on research grants, allowing only permanent staff to be paid, that would help quite a bit.

Draining the postdoc holding tank would probably take a decade or more even with rational policies, but current policies of universities and industry (only hiring people in bio after 6 years or more of postdoc) and of the NIH (providing generous funding for postdocs but little for permanent researchers) make the postdoc holding tank likely to grow rather than shrink.

He pointed out that NIH used to spend a much larger fraction of their funding on training students than they do now—they’ve practically abandoned education, in favor of a low-pay, no-job-security research workforce (grad students and postdocs).

A big part of the problem is that research groups have changed from being a professor working with a handful of students to huge groups with one PI and dozens of postdocs and grad students. Under the huge-group model, one PI needs to have many grants to keep the group going, so competition for research grant money is much fiercer, and there is much less diversity of research than under a small-group model.

The large-group model necessitates few PIs and many underlings, making it difficult for postdocs to move up to becoming independent scientists (there are few PI positions around), as well as making it difficult for new faculty to compete with grant-writing machines maintained by the large groups.

A simple solution would be for NIH to institute a policy that they will not fund any PI with more than 3 grants at time, and study sections should be told how much funding each PI has from grants, so that they can compare productivity to cost (they should also be told when grants expire, so that they can help PIs avoid gaps in funding that can shut down research).  The large groups would dissolve in a few years, as universities raced to create more PIs to keep the overhead money coming in.  The new positions would help drain the postdoc holding tank and increase the diversity of research being pursued.

Of course, the new positions would have to be real ones, not “soft-money” positions that have no more job security than a postdoc. NIH could help there too, by refusing to pay more than 30% of a PI’s salary out of Federal funds.

Of course, any rational way of spending the no-longer-growing NIH budget will result in some of the bloated research groups collapsing (mainly in med schools, which have become addicted to easy money and have built empires on “soft-money” positions).

I think that biology has been over-producing PhDs for decades—more than there are permanent positions for in industry and academia combined. That combined with the dubious quality of much of the PhD training (which has often been just indentured servitude in one lab, with no training in teaching or in subjects outside a very narrow focus on the needs of the PhD adviser’s lab), has resulted in a situation where a PhD in biology is not worth much—necessitating further training before the scientist is employable and providing a huge pool of postdoc “trainees”, many of whom will never become independent scientists.

Tightening the standards for admission to PhD programs and providing more rigorous coursework in the first two years of PhD training (rather than immediately shoving them into some PI’s lab) would help a lot in increasing the value of the PhD.

Unfortunately, I see our department going in the opposite direction—moving away from the engineering model of training people to be independent immediately after the PhD and towards a model where they are little more than hands in the PI’s labs (decreasing the required coursework, shrinking the lab rotations, and getting people into PI labs after only 2 quarters). I gave up being grad director for our department, because I was not willing to supervise this damage to the program, nor could I explain to students policies that I did not agree with.

One thing we are trying to do that I think is good is increasing the MS program, so that there is a pool of trained individuals able to take on important research tasks as permanent employees, rather than as long-term PhDs or postdocs. Again, the engineering fields have developed a much better model than the biomedical fields, with the working degree for most positions being the BS or MS, with only a few PhDs needed for academic positions and cutting-edge industrial research. Note that a PhD often has less actual coursework than an MS—PhD students have been expected to learn by floundering around in someone’s lab for an extra 5 years taking no courses and often not even going to research seminars, which is a rather slow way of developing skills and deadly to gaining a breadth of knowledge. Biotech companies would probably do well to stop hiring PhDs and postdocs for routine positions, and start hiring those with an MS in bioengineering instead.

2014 March 11

Why few women in engineering?

Filed under: Uncategorized — gasstationwithoutpumps @ 11:33
Tags: , , ,
The Washington Post recently published an opinion piece by Catherine Rampell with a somewhat unusual, but plausible explanation why some fields end up with more men than women (as most of the engineering fields do). The theory is that women are more discouraged by a B in an entry-level course than men are (she cites some data from econ courses that support that theory, though it is only correlation, not necessarily causation).
Plenty has been written about whether hostility toward female students or a lack of female faculty members might be pushing women out of male-dominated majors such as computer science. Arcidiacono’s research, while preliminary, suggests that women might also value high grades more than men do and sort themselves into fields where grading curves are more lenient.
As parents and teachers we encourage children to pursue fields that they enjoy, that they are good at, and that can support them later in life. It may be that girls are getting the “that they are good at” message more strongly than boys are, or that enjoyment is more related to grades for girls. These habits of thought can become firmly set by the time students become men and women in college, so minor setbacks (like getting a B in an intro CS course) may have a larger effect on women than on men.
I’m a little wary of putting too much faith in this theory, though, as the author exhibits some naiveté:
But I fear that women are dropping out of fields such as math and computer science not because they’ve discovered passions elsewhere but because they fear delivering imperfection in the “hard” fields that they (and potential employers) genuinely love. Remember, on net, many more women enter college intending to major in STEM or economics than exit with a degree in those fields. If women were changing their majors because they discovered new intellectual appetites, you’d expect to see greater flows into STEM fields, too.
It is very difficult for students, male or female, to transfer into STEM majors late—the number of required courses and prerequisite chains are too long.  As long as the humanities majors have few, unchained requirements and STEM majors have many, chained requirements, the transfer out of STEM will be far larger than the transfer into STEM. Expecting equal flow in both directions is naive.
But there is, I believe, a greater proportional loss of women from STEM fields in college than men, and most of the interventions trying to reduce that loss have not been very effective.  (Harvey Mudd has had some success, attributed to various causes.) If the theory put forth by Rampell is valid, what interventions might be useful? Here are a few I thought of:
  • Higher grades in beginning classes. Engineering courses generally average 0.4 or 0.5 grade points lower than the massively inflated grades in humanities courses. I doubt, somehow, that many engineering faculty will be comfortable with the humanities approach of giving anyone who shows up an A, no matter how bad their work. So I don’t think that this idea has any merit.
  • Lower entry points. One of the things that Harvey Mudd did was to require every freshman to take CS and to introduce a lower-level CS course for those who did not have previous programming. By having some lower-level courses, students could get high grades in their first course without teachers having to water down existing classes or engage in grade inflation. By requiring the course of all students, students who avoided the subject for fear of not being able to compete are given a chance to discover an interest in the field (and, apparently, many women at Harvey Mudd do discover an interest in CS as a result of the required course).
  • Extra tutoring help for B students in entry-level courses. Almost all the “help” resources at the University seem to be aimed at getting students from failing to passing—but the students who are barely passing after massive help do not make good engineering majors, and are likely to fail out of the major later on. It would be far more productive to try to turn the Bs into As, retaining more women (and minorities) in the field. Of course, this means that the assistance has to be at a higher level than it often is now—the tutors need to know the material extremely well and be able to assist others to achieve that expertise.  Basic study skills and generic group help may be good for getting from failing to passing, but may not be enough to get from B to A.
  • More information to students about the feasibility and desirability of continuing with a B. This sort of encouragement probably has to happen one-on-one from highly trusted people (more likely peers than adults).

These ideas are definitely half-baked—I’m not even fully convinced that the theory behind them is valid, much less that they would have the desired effect. I welcome comments and suggestions from my readers.

2014 January 25

NSF Idea Labs in STEM Education

Filed under: Uncategorized — gasstationwithoutpumps @ 15:27
Tags: , , ,

Mark Guzdial recently copied a NSF announcement about a new program that sounded interesting to me: NSF Dear Colleague Letter on new Idea Labs in STEM Education:

DEAR COLLEAGUE LETTER

Preparing Applications to Participate in Phase I Ideas Labs on Undergraduate STEM Education

NSF 14-033

The Directorate for Education and Human Resources has implemented a new program for “Improving Undergraduate STEM Education” (IUSE) through its Division of Undergraduate Education (EHR/DUE). The IUSE program description [PD 14-7513] outlines a broad funding opportunity to support projects that address immediate challenges and opportunities facing undergraduate science, technology, engineering, and math (STEM) education, as well as those that anticipate new structures and function of the undergraduate STEM learning and teaching enterprise. The IUSE program description creates an opportunity to submit unsolicited proposals across all topics and fields affecting undergraduate STEM education. It also includes an opportunity to participate in the first phase of three different Ideas Labs aimed at incubating innovative approaches for advancing undergraduate STEM education in three disciplines (biology, engineering, and the geosciences). These “IUSE Phase I Ideas Labs” will bring together relevant disciplinary and education research expertise to produce research agendas that address discipline-specific workforce development needs. The purpose of this Dear Colleague Letter is to provide additional information regarding the focus of the three Phase I Ideas Labs and guidance on preparing applications for community members seeking to participate in them.

There were two of the “Ideas Labs” that sounded relevant to me in my role as undergrad director and curriculum designer for the bioengineering program and as a bioinformatics teacher and researcher:

Biology

The biological sciences workforce for the future, including graduates of two-year schools, four-year institutions, and graduate programs, will need mathematical and computational skills beyond those of its predecessors. These tools also are required across the wide spectrum of biological sub-disciplines. …

Engineering

Social inequality in engineering education and practice is a durable problem, one that has resisted perennial efforts to “broaden participation,” “increase diversity,” or “improve recruitment and retention of women, minorities, and people with disabilities.” While a great deal of previous and ongoing work has focused on fostering the ability of individuals to access and persist in the engineering education system, this Ideas Lab will focus on changing the system itself. …

A five-day workshop with other people struggling with these problems might be interesting (though I don’t know how I could take a week off from teaching for an unknown week: one of March 3-7; March 17-21; March 31-April 4—they haven’t yet figured out which workshop will be which week).  Of those, only March 17–21 is at all feasible: missing the last day of class and exam week for this quarter. With a day of travel needed on each end, the ideas labs would take a full 7-day week.

I find writing proposals rather painful, and this one wouldn’t even result in any funding, so I re-read the letter more carefully to see if it really was something I wanted to do.

Page one of the “project description” seemed reasonable:

  • Provide a brief summary of your professional background (100 words maximum). Please note that if you are selected as a participant, information provided in answer to this question will be made available to the other participants, to facilitate networking at the Ideas Lab.
  • Describe your experience and interest in working across disciplines (100 words maximum).
  • Describe your key contribution(s) to addressing the specific STEM workforce development theme of this Ideas Lab (see above) through novel and potentially transformative approaches (no more than half a page).
  • Indicate your ability or inability to participate during any of the scheduled Ideas Lab dates (March 3-7; March 17-21; March 31-April 4).

But I found page 2 a bit difficult even to think about:

Please spend some time considering your answers to the following questions. Your responses should demonstrate that you have suitable skills and aptitude to participate in the Ideas Lab (unrelated to your research track record).

  • What is your approach to working in teams? (100 words maximum)
  • How would you describe your ability to engage non-experts or people with a different perspective to yours on this topic? (100 words maximum)
  • The Ideas Lab encourages a free exchange of ideas: enjoying the sharing, shaping and building ideas over an intensive 5-day setting, working as an equal with individuals you may not know.  How do you see yourself suited for this type of interaction?  If possible, describe any comparable experience you have had.  (150 words maximum).

I was also a little bothered by the description at the end of the engineering workshop:

In the Engineering Phase I Ideas Lab, engineers and social scientists will face head on the systems and structures that reproduce social inequality in engineering education and in the engineering workforce. A complete and direct discussion is not afraid to examine manifestations of racism, sexism, and ableism in engineering, and to also consider classism, heteronormativity, ageism, and obstacles faced by Veterans and other non-traditional groups. The Engineering Phase I Ideas Lab will generate new framings and new strategies to move the nation toward greater inclusion of marginalized groups in engineering.

In both places it seems clear that they have already decided precisely how to frame the question to get the answers they want to hear based on the jargon they use to describe the problem, and that they are not interested in hearing from any one who might disagree.  They seem to be trying to create a panel to rubber stamp some plan they have already devised, and are looking for a committee of yes-men to staff the panel.

I’m afraid I’m too much of a curmudgeon to be able to help them with that—I also have extreme doubts that they are going to succeed at anything with this plan but spending a lot of money on the pet ideas of the social scientists who came up with the plan, with no positive effect on engineering education or the “durable problem” of under-representation of women, blacks, Hispanics, and people with disabilities in engineering fields.

“Changing the system itself” sounds a lot like the MOOC advocates rallying call, as does the list of parameters they are proposing to modify:

Many prior efforts for inclusion have been hampered by a presumption that certain parameters can’t be changed (for example, eligibility criteria, narrow definitions of what counts in or as engineering, limited roles for 2-year institutions, or a four year degree model).

While I believe that ABET has been too narrow in some fields in their accreditation standards for engineering programs, I’m not convinced that throwing away what makes engineering a useful discipline is going to accomplish any socially useful goals. Applying the grade inflation and lowered expectations of other disciplines to engineering may indeed produce more diversity of graduates, but would probably make industry start insisting on higher qualifications, increasing the time and expense of meaningful engineering education, and shrinking rather than increasing diversity in the workforce.

The biology Ideas Lab has a more solvable problem:

The Biology Phase I Ideas Lab will consider strategies to integrate these critical competencies in quantitative literacy into a biology core curriculum and to study their effectiveness and/or impact to generate knowledge that will inform their broader implementation.

but I’m a little worried about the precise “quantitative literacies” that they have identified:

Specifically, these are “the ability to use quantitative reasoning” and “the ability to use modeling and simulation”, to gain a deeper understanding of the dynamics and complexity of biological systems. In addition, many areas of biology, from molecular, organismal through ecosystems studies, are reliant on large databases. Biologists of the future will require the mathematical and theoretical foundations necessary to abstract systems-level knowledge from complex data sets.  These skills will be important also for proper database management, preservation of the data collected, and effective use of the information they contain.

The emphasis on biologists needing to learn how to manage data and how to use large data sets is important, but the fact that they mention “mathematical” rather than “statistical” skills, and stress “modeling and simulation” implies to me that they are still stuck in the physicists’ mindset of differential equation modeling, which is not that compatible with the data biologists have available and the modeling that biologists need.  There is no mention of bioinformatics or statistics in this call, so I think that they are likely to be going in totally the wrong direction.

But their call for yes-men makes it clear that opinions like mine would not be welcomed—even if I could take off a week to sit around chewing the fat in Washington DC.  So I won’t be wasting my time trying to fill out the proposal forms by the Feb 4 deadline (the letter was only cleared for release on Jan 23, so it is clear they only want people who they had quietly hinted to ahead of time applying).

Oh well, politics as usual in Washington, DC.

2014 January 23

Academic Workforce Data Center

Filed under: Uncategorized — gasstationwithoutpumps @ 09:08
Tags: , ,

The Modern Language Association (the main professional organization for humanities faculty) has an  Academic Workforce Data Center that let’s you look up what fraction of the faculty on a campus are tenured, tenure-track, full-time non-tenure, and part-time non-tenure.  They split off medical faculty from the rest, as many medical faculty are “clinical appointments”, where the majority of the faculty income comes from doing medicine, not teaching or research.

The data is from the 2009 surveys conducted by the US Department of Education’s Integrated Postsecondary Education System (IPEDS), so is not completely current. They also have data from the 1995 IPEDS survey, but I did not copy that here.

I looked up the schools my son is applying to (excluding med school faculty) sorted by the % tenured or on the tenure track:

school % tenured % tenured or tenure-track % full-time non-tenure % part-time non-tenure
Harvey Mudd 64 81 7 12
UCSB 64.9 75.8 9.6 14.6
UCSD 56.4 72.0 33.0 19.7
Stanford 54.7 71 22.3 6.7
MIT 52.6 68.2 16.4 15.4
Brown 51.7 67.4 17.8 14.8
UCB 51.9 63.4 10.8 25.8
CMU 33.9 46.9 45.7 7.4

Of these, CMU relies the most heavily on non-tenured faculty, and UCB the most on part-timers.  Harvey Mudd seems to be the most traditional, relying on full-time tenure-track faculty.

I’ve also extracted the data for all the UC campuses (except UCSF, which is a med school only):

school % tenured % tenured or tenure-track % full-time non-tenure % part-time non-tenure
UCSB 64.9 75.8 9.6 14.6
UCD 59.6 74.5 27.5 13.5
UCR 52.0 72.3 11.1 16.6
UCI 54.7 72.1 8.5 19.4
UCSD 56.4 72.0 33.0 19.7
UCLA 54.8 64.7 13.0 22.3
UCB 51.9 63.4 10.8 25.8
UCSC 47.5 62.6 6.1 31.3
UCM 20.9 53.6 30.4 15.9

Merced is somewhat understandably at the bottom, because they are a new campus that has not yet managed to grow its faculty to a reasonable level. But UCSC has no excuse for relying on so many part-time faculty—we’re probably the most understaffed UC campus for full-time faculty (tenure-track or not).

Next Page »

The Rubric Theme. Blog at WordPress.com.

Follow

Get every new post delivered to your Inbox.

Join 268 other followers

%d bloggers like this: