While I worked as lecturer at UC Berkeley, my priorities were my students and teaching assistants, or TAs — it was what I was paid to do.
The campus administration, however, often has not shared in these priorities. From my experience within the electrical engineering and computer sciences, or EECS, department, this reality has manifested itself as the at-times-misguided actions taken in terms of funding, student enrollment and TA support.
The lack of funding to these departments has created a series of uncomfortable situations, resulting in significant enrollment cuts to the computer science major under the impacted major policy, and the creation of the data science major, where a significant percentage of the teaching is performed by other departments.
Until these issues are acknowledged, this broken system will remain broken.
The fault starts with the “Temporary Academic Support,” or TAS, budget, which is the campus’s allocated funding that pays for all lecturers and TAs. To put it into perspective, every large class on campus — and a number of smaller ones — are taught primarily through the TAS budget.
TAS funding comes from the central campus budget directly to each department, totaling $73.4 million per year. This number is not quite enough to actually provide for the student support necessary in large, TA-heavy classes or even smaller ones taught by lecturers.
As a consequence, each department needs to supplement the TAS funding with their own “unrestricted” funds — money that is given or raised by each department for their own use.
Unrestricted funds, however, are precious to department leadership. The funding can pay for other priorities, such as graduate student fellowships, resources for faculty and quality of life improvements.
The more students a department teaches, the more unrestricted funds need to be allocated to supporting TAs and lecturers. This, in turn, poses a significant financial burden for those departments actually performing the university’s stated mission. Financially, departments want — and need — to teach less.
Recently, campus announced the creation of an entirely new college: the College of Computing, Data Science and Society. The college is complete with a vice provost, an executive associate dean, three associate deans, a senior assistant dean, two assistant deans, an executive director for interdisciplinary initiatives, a chief technological advisor and a whole host of other personnel. In addition, it will receive a building with a budget of more than half a billion dollars that has already raised $320 million.
This college supports just three already existing majors: statistics, computer science and data science. It will probably graduate fewer than 800 undergraduates a year under the new impacted major policies and is unlikely to result in any net increase in students.
The EECS department used to graduate more than 1300 students per year: 528 from EECS and 850 from computer science in the College of Letters and Science. The latter would admit any Letters and Science student who showed themselves capable of handling the material by achieving a 3.3 GPA in the first three undergraduate classes of the major. However, through the high-demand major policy, this will soon no longer be the case.
Starting in fall 2024, there will instead be roughly 200 Letters and Science — soon-to-be CDSS — incoming freshmen in the major. In addition, an unspecified number of Letters and Science students will be accepted through a currently unspecified holistic review.
This drastic cut in enrollment throws any notions of supporting diversity, equity and inclusion out the window, as DEI must start by teaching all willing students. However, these cuts solve the EECS department’s problem of having to pay to teach “too many” undergraduates.
In a similar vein, the data science major was designed to provide a computer science-type degree, while easing the teaching burden of the EECS and statistics departments.
A UC Berkeley computer science degree requires taking at least nine undergraduate classes within the EECS department. On the other hand, a data science degree requires just four courses listed as data science, statistics or computer science. Even assuming that a data science student may take more data, computer science or statistics classes than the minimum, the resulting curriculum has each student within the major being educated by other departments for at least half of their required classes.
However, data science — a major that has a 2.0 rather than a 3.3 GPA threshold in the required classes and was designed to support far more students — has now been set as a restricted major, with an incoming freshman class of roughly 200.
It is bad enough for other departments to be financially punished for teaching their own majors, but it is intolerable for these same departments to take on an additional financial burden in order to teach data science majors.
Until both departmental and university leadership publicly acknowledges the problem and actually prioritizes teaching, this situation will only grow worse.
