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Useful data (part of a draft letter to the incoming chair)

I’ve now completed the first few sections of my letter to the incoming chair. Those sections deal with the various tasks for which the chair is responsible. In this section, we turn to the many sources of data that the chair may want to (or need to) rely upon in doing their work. As always, I’ve probably missed some and will add them later.

In the course of your work as Chair, you will receive a variety of data. You will also have to go in search of some data. These data can help you do short-term and long-term departmental planning, provide evidence for departmental needs, and support you in other departmental responsibilities. I’ve listed a variety of sources. Remember that you can often ask offices on campus for data. For example, Carlie VanWilligen in the Office of Analytic Support and Institutional Research (OASIR) can provide you with most kinds of enrollment and demographic data you need and Scott Baumler in Admissions can help you with predicting student interests.

The Department Snapshot

Once per year, the Dean’s office sends us a Department Snapshot. The snapshots have been getting smaller and smaller each year. For example, the 2014-15 snapshot included a list of faculty workloads, a leave schedule, our self-study schedule, a table of accumulated MAP credits, a list of who had taught Tutorial over the past decade (and when), a list of who had taught other service courses and concentration class over the past decade (and when), a list of all courses taught by department faculty, numbers of majors, and perhaps a bit more. In contrast, the 2016-17 snapshot contains only the leave schedule. The other information comes in in dribs and drabs at other times, or you need to request it, or both.

Department Data Sheet

OASIR posts a series of department data sheets to You will need these sheets when preparing your tenure-track position proposals. If you can’t find the latest version, Carlie VanWilligen is usually happy to send it along.

The data sheets vary a bit from year to year. Some years you only get the overall numbers for the department in terms of average class sizes at each level and average numbers of advisees. In other years, you also get detailed data on enrollment in individual classes.

I see that they have not updated this site with the 2016-17 data. I wonder if they will soon.

Department Enrollments

The Dean’s office sends us enrollments for the past five years in the spring. We usually only get that sheet if we explicitly request it.

End-Of-Course Evaluations

You should read each faculty members’ End-of-Course Evaluations. These are available in electronic form from the Academic Support Assistants. The ASA’s may not have the summary sheets. In those cases, you can ask them from Carlie.

Course Rosters

If you ask nicely, Vickie Rutherford will provide you with a list of all the class rosters at the end of preregistration period. Having the list can be very useful for figuring out how we deal with the Cut, Close, Balance period. For example, it makes it easier to tell when someone is enrolled in multiple CS courses. I keep these lists because they also provide useful for confirming that students have been dropped from classes.

Major Counts

The College Directory (aka DB) is a good source of data for the number of students in each major. Due to a bug in the system, Art History majors get counted within both Art History and History, but it’s pretty easy to account for that issue. The Department Folder has a short script that gathers data from DB and puts it in a .csv file.

Lists of Courses

You can get a complete list of all classes offered by the College at Charlie may have written some scripts that help you turn that into useful spreadsheet data.

Expressed Interest of Incoming Students

I mentioned this in passing above, but it’s worth revisiting. In planning for the number of sections of CSC 151 in the fall, you should obtain information from Scott Baumler in Admissions. Scott can tell you how many students listed Computer Science as one of their interests and how many listed it as their primary interest. Scott and I agree that it’s difficult to use these data for predictive modeling, but it can still be useful to see what the data are.

Data You Create

As I noted earlier, because we now have some faculty who alternate between 4.5-course years and 5.5-course years, you need to keep track of whether people are up or down in teaching credits. [current details elided.] I’ve included those in part of my long-term planning document.

In my attempts to understand trends, I find it useful to make a list of prospective majors in various class years. For example, most of the second-year students in fall sections of CSC 207 are likely to declare CS majors. We currently have [elided] such students. Some of the second-year students in the fall sections of CSC 161 may become majors. We usually ask the person teaching those courses to ask midway through the semester. We also do informal surveys of third-year students in 300-level CS classes.

Information From Others

If you pay attention, you will find that other folks gather data that are useful to us. Here’s one that comes to mind: Shonda is working with Angela Voos (I think) on analyzing faculty workload. From what I’ve seen in the past, those data say a lot about our department.

Version 1.0 of 2017-05-27.