As a blogger, I have been a failure in the last six months. I barely have enough time to tweet, let alone sit down for these extensively researched, tightly edited, and deeply insightful missives that characterize my blog. I tell you, 1005 words on finding love through optimization doesn’t just happen!
I have my excuses, of course. As the fabulous PHD Comics points out, most of us academics seem somewhat overbooked, despite the freedom to set much of our schedule. I am not alone in being congenitally unable to turn down “opportunities” when they come by. “Help hire a Norwegian professor?” Sounds fun! “Be the external examiner for a French habilitation degree?” I am sure I’ll learn a lot! “Referee another paper?” How long can that take? “Fly to Australia for a few days to do a research center review?” Count me in! And that was just four weeks in February.
All this is in addition to my day job that includes a more-than-healthy dose of academic administration. Between doing my part to run a top business school and to move along in research, not to mention family time, including picking up the leavings of a hundred pound Bernese Mountain Dog (the “Mountain” in the name comes from said leavings) and entertaining a truly remarkable nine-year-old son, my time is pretty well booked up.
And then something new comes along. For me, this newness is something I had a hand in putting together: the Tepper School’s new FlexMBA program. This program offers our flagship MBA program in a hybrid online/onsite structure. Every seven weeks or so, students in the program gather at one of CMU’s campuses (we have them in Pittsburgh, Silicon Valley, and New York, we have not yet used our Qatar campus) and spend a couple days intensively starting their new courses. This is followed by six weeks of mixed synchronous and asynchronous course material. Asynchronous material is stuff the students can do in their own time: videos, readings, assignments, and so on. The synchronous lesson is a bit more than an hour in a group, meeting via a group video conference, going over any issues in the material and working on case studies, sample problems, and so on. The course ends with exams or other evaluations back on campus before starting the next courses.
Our commitment is to offer the same program as our full-time residential MBA and our part-time in-Pittsburgh MBA. So this means, the same courses, faculty, learning objectives, and evaluations that our local students take.
We started this program last September with 29 students, and so far it has gone great. The students are highly motivated, smart, hard-working, and engaged. And the faculty have been amazing: they have put in tons of work to adapt their courses to this new structure. Fortunately, we have some top-notch staff to keep things working. Unlike some other MBA programs, we have not partnered with any outside firm on this. If we are going to offer our degree, we want it to be our degree.
I have just finished my own course in this program. I teach our “Statistical Decision Making” course. This is a core course all MBA students take and revolves around multiple regression and simulation (the interesting relationships between these topics can wait for another day). This is not the most natural course for me: my research and background is more on the optimization side, but I very much enjoy the course. And teaching this course has made clear to me the real promise of the hot phrase “business analytics”: the best of business analytics will combine the predictive analytics of statistics and machine learning with the prescriptive analytics of optimization, again a topic for another day.
My initial meeting with the students concentrated on an overview of the course and an introduction to the software through some inspiring cases. We then moved on the the six-week distance phase. Each of the six modules that make up a course is composed of four to eight topics. For instance, one of my modules on multiple regression includes the topic “Identifying and Handling Muliticollinearity”. (Briefly: multicollearity occurs when you do regression with two or more variables that can substitute for each other; imagine predicting height using both left-foot-length and right-foot-length as data). That section of the module consists of
- A reading from their textbook on the subject
- One 8 minute video from me on “identifying multicollinearity”
- One 6 minute video from me on “handling multicollinerity”
- A three minute video of me using our statistical software to show how it occurs in the software (I separate this out so we can change software without redoing the entire course)
- A question or two on the weekly assignment.
It would be better if I also had a quiz to check understanding of the topic, along with further pointers to additional readings.
So my course, which I previously thought of as 12 lectures, is now 35 or so topics, each with readings, videos, and software demonstrations. While there are some relationships between the topics, much is independent, so it would be possible, for instance, to pull out the simulation portion and replace it with other topics if desired. Or we can now repackage the material as some supplementary material for executive education courses. The possibilities are endless.
Putting all this together was a blast, and I now understand the structure of the course, how things fit together, and how to improve the course. For instance, there are topics that clearly don’t fit in this course, and would be better elsewhere in the curriculum. We can simply move those topics to other courses. And there are linkages between topics that I did not see before I broke down the course this finely.
I look forward to doing this for our more “operations research” type courses (as some of my colleagues have already done). Operations Research seems an ideal topic for this sort of structure. Due to its mathematical underpinnings and need for organized thinking, students sometimes find this subject difficult. By forcing the faculty to think about it in digestible pieces, I think we will end up doing a better job of educating students.
Creating this course was tremendously time consuming. I had not taken my own advise to get most of the course prepared before the start of the semester, so I was constantly struggling to stay ahead of the students. But next year should go easier: I can substitute out some of the videos, extend the current structure with some additional quizzes and the like, adapt to any new technologies we add to the program, and generally engage in the continuous improvement we want in all our courses.
But perhaps next year, I won’t have to take a hiatus from blogging to get my teaching done!