I’ve been eagerly awaiting the follow-up course to Rice University’s An Introduction to Interactive Programming in Python. While that course offered a playful introduction to computer science and programming through building a number of successively more complicated games, Principles of Computing attempted to improve your programming skills by embedding discrete mathematics problems and basic algorithms into, again, assignments that consisted of writing a number of games. Unlike the predecessor course, you didn’t have to bother with GUI code, but could instead fully focus on the underlying game logic.

On the mathematical side, Principles of Computing covered arithmetic sums, basic functions in order to describe growth rates, basic probability and a bit of combinatorics. Some assignments focused on algorithms, including standard topics like searching and sorting. Breadth-first search was covered in a rather amusing assignment where you had to write logic for ‘humans’ that would make them avoid slowly moving ‘zombies’. Further, minimax was covered in a disappointingly short assignment that was merely a variation of a previous one, an AI for Tic-Tac-Toe. The assignments themselves were the highlight of the course, though, covering the logic behind games such as 2048, Cookie Clicker, Yahtzee, the just mentioned Tic-Tac-Toe (Monte Carlo and tree search), and the 15-puzzle. Overall, they helped solidify the concepts.

While I thought that An Introduction to Interactive Programming in Python, which I took when it was offered the first time, was very polished, the same can’t unfortunately be said for Principles of Computing. Let’s me preface my subsequent criticism by stating that Principles of Computing is an excellent course, and easily comparable to the kind of course you would take at a brick-and-mortar university. While it isn’t as polished as its predecessor, it is nonetheless, in my opinion, one of the best-designed MOOCs in computer science you can take.

The video presentations are engaging. Production values seem to have increased over An Introduction to Interactive Programming in Python, which had videos that were seemingly captured by a webcam. Overall, the course material is presented very well. Some may find that the videos are moving a bit too slowly at times, but I prefer that approach over lecturers who rush through the material or even omit key concepts. Further, there was a lot of support available, such as in the form of relatively extensive notes on key topics. The discussion forums were not overly active, but it seemed that basically any question got answered quickly, either by other students or by the instructors themselves.

What stood out negatively, though, was a certain sloppiness in the presentation. In particular, the descriptions of the assignments were often lacking. There were several instances were parts of the assignment texts had to be revised by the instructors, after students posted that they were ambiguous or left out important information. In one assignment there were several typos. In others, important information was missing, or given in a rather misleading way. This was arguably one of the reasons for the tremendous rate of attrition. To quantify this impression: the first two assignments led to 19 pages of discussions, while the last few only had five or six pages.

The teaching language of this course was Python. Unfortunately, almost all starting templates prescribed OOP, and due to the way your programs were tested, you couldn’t deviate from that paradigm. In many cases a functional solution would have been much more straightforward, but that’s probably a general statement of OOP vs. FP. While I think that Python is a fine language for budding programmers, I don’t think it’s the best choice when writing more complex programs. For Principles of Computing, Python worked well, apart from the very last assignment, a solver for the 15-puzzle, which was several hundred lines long.

Due to the missing type system of Python that task felt like building a house of cards. You’re forced to write assertions and tests for basically anything. In a statically typed language you could have done with a fraction of the tests, and even with a rudimentary type system like Java’s, you would have been better off, with the downside that its lack of tuple assignment would have blown up the code by a factor of two or so. I’m curious to find out how long an implementation in Haskell would be. You could probably do it in half as many lines, and with just a few property-based tests, instead of a myriad of unit tests.

One last problem, which was voiced repeatedly on the forum, was that in the assignment description students were repeatedly told that, “once you’re confident that your methods are correct, use [the online unit test suite for this course], to confirm that they are correct.” Unfortunately, the unit tests provided did not cover all corner cases, so you certainly couldn’t confirm that your code is correct. If you were unlucky, you discovered that the very first method you’ve written, a check of a basic invariant, was actually incorrect, as you were working on the very last method, which called the various solvers depending on the state of the board. Some students made the spurious argument that those missing unit tests were “probably intended to make us write our own tests”. I didn’t find this very convincing. If that had really been the case, then state that the provided unit tests are lacking, but don’t tell students that they can use the provided unit tests to confirm the correctness (!) of their code, when that’s simply not possible.

Principles of Computing offers two kinds of statements: a regular one, and one “with distinction”. For the latter, you would have to average 90% over the entire course, and get 70% on the last assignment. As indicated by the description above, that assignment, the solver for the 15-puzzle, was rather complex, and a worthy criterion for a statement of achievement with distinction. Please note that your program is expected to solve this problem in full generality, meaning that it should be able to process any m * n puzzle. It is indeed a lot more involved than it might look.

Apart from a few minor problems, I found Principles of Computing to be tremendously enjoyable, and I warmly recommend it. The few issues I pointed out will most likely be eradicated in the second iteration, assuming that the same assignments will be used.