On Learning Programming and Math at Coursera

Coursera, Udacity, MIT Open Courseware, and other such sites are useful to me because they decouple the desire to learn college-level material from the expense and regulations of earning (another) diploma. The latter isn't compelling to me today, but the former certainly is.

I've now taken three Coursera courses: Functional Programming Principles in Scala, Social Network Analysis, and Coding the Matrix: Linear Algebra Through Computer Science Applications. I also tried to take Calculus: Single Variable, but found that the workload was higher than I could manage with home and work obligations. I had varying degrees of experience with these subjects before beginning the courses; Functional Programming was largely review for me, Social Network Analysis was mostly new to me, and Linear Algebra was somewhere in between.

First, I found all three courses to be an effective way for me to learn the material presented.  This is mostly because all three professors did an excellent job of selecting the exercises to complete for the course. Most of what I learned in all three courses came from completing the exercises. The quality of the lectures and the availability of written materials for offline study varied from course to course. But it's hard to be too critical considering that the courses are free. For someone like me who cares much more about increasing my knowledge than receiving credit or some sort of official certificate, it almost seems foolish not to take at least one course at any given time.

Completing the courses gave me a chance to practice with some programming languages I don't use in my professional work right now, like Scala, Python 3, and R.

Perhaps surprisingly, given that all three courses use Coursera's services, the means of submitting assignments was wildly different from class to class.

For the Scala course, assignments were submitted via sbt, and graded by unit tests on the server. These tests were occasionally fallible; when the server was especially loaded, it could decide that a submission was experiencing infinite recursion (a real hazard in functional programming) when, in fact, it was simply executing the code slowly. At most other times, however, the tests were accurate and the feedback was pretty reasonable.

For the Social Network Analysis course, the programming assignments were an optional add-on. You had to attach the homework via Coursera's site, and it would be graded somehow. It's not clear to me what the mechanism was, but it always accepted my submissions. The final programming assignment was graded using a peer review system where three other students would rate your submission, and you would evaluate the submissions of three more students. I really appreciated the feedback I got on this; it seems that the other students put real effort into their feedback.

In the Linear Algebra course, the programming assignments were all in Python. You submit them using a custom Python script which analyzes your code using regular expressions and unit tests on the client and server. This system was the buggiest of the three; the client and server code were occasionally out of sync, and frequently rejected correct code. These issues were fixed as the course went on, but it made for some very frustrating hours.

The use of instructor-supplied unit testing varied from class to class, as well. Unit tests were always included in the Scala class assignments, although the grader would run additional tests on your code. The Linear Algebra class assignments occasionally included unit tests, but mostly did not. The grader always ran unit tests, but they were not usable by the students. This deficit was made up for by other students who would post reasonable unit tests to the class forum. The Social Network Analysis class never included any unit tests in the assignments at all.

My biggest disappointment with all of these courses, however, is non-technical. Coursera, like nearly everyone in academia, has an honor code which forbids sharing work. This stands in stark contrast to most other collaborative systems for learning programming, like Exercism, Project Euler, 4Clojure (and arguably GitHub) where you are expected to first solve a problem yourself, and then work with other developers to refine your solution into the best possible implementation. You learn how to do the work well, not just how to make tests pass.

With Coursera (with the sole exception of the Social Network Analysis final problem), you just can't do that at all. There are forums, where you are allowed to opaquely discuss the assignment and your approach to it, but you cannot show any actual code for the assignment itself. In a real college course, you could review your work privately with a TA, so you'd at least get some feedback beyond pass/fail. There is no such option at Coursera. For me, this is the biggest barrier to real learning in Coursera, and it seems unnecessary, given that "cheating" on a zero-credit course you take for fun robs only yourself.

There are other areas in which I think Coursera could profit by deviating from the way things are done in college. It's not clear to me why a fixed schedule is required for these classes. Why not give students the option of "auditing" a course on their own time? Since the lectures are pre-recorded and the assignments are, for the most part, graded mechanically, it seems like this should be possible. Having a more flexible schedule would allow students who cannot commit the roughly 6 through 16 hours per week that most of the classes seem to require.

These criticisms aside, however, the big picture is that all of the classes I have taken so far have been good because the professors did an excellent job of designing the courses. As long as Coursera continues to recruit such qualified teachers, I think their classes will be a good investment of my time.