The Design of Extended Exercises

One of the highlights of the TeachScheme! method is to create Extended Exercises. Several of these pepper How to Design Programs, and even more have been created since to deal with a variety of interesting problem scenarios (e.g., illustrating graphics via t-shirt design, explaining networking by having machines play roles in a theatrical play, demonstrating communication with foreign sites by processing data from a microfinance institution, etc). Through an Extended Exercise a student learns about how computer science connects to domains, develops practice building programs incrementally, learns to build earlier assignments that later assignments can depend on, and so forth.

Here is a preliminary articulation of some principles that I think govern a good Extended Exercise, with an emphasis on their “form factor”.

• Pick a domain. Whether the domain looks inward (a computing activity such as networking) or outward (such as social networking) doesn't matter. If it does look inward, try to make it more applicable through the judicious use of data (the same exercise can look very dry or very applied depending on what data you choose). For instance, our networking exercises is presented in terms of Shakespeare's Hamlet.
• If necessary, write a Teachpack. A domain almost certainly needs a Teachpack to reduce the programming burden on students. For instance, the microfinance exercise uses a Teachpack to hide the ugly details of screen-scraping (which in turn need to be constantly updated by a vigilant maintainer).
• Try to provide a non-trivial dataset in the Teachpack. Good data can make an assignment more enjoyable—e.g., our networking example provides an excerpt from Act 2, Scene 2 of Hamlet (“What a piece of work is man!”)—and in cases where the exercise depends on connecting to an external site (e.g., the microfinance example), the data may be essential.
• Structure the assignment to have five to eight questions: not much fewer (too few steps) nor much more (too much to grasp).
• Try to decompose the problem using good principles of stepwise refinment, using your own wisdom in these matters. By showing students several such examples, we hope for them to build up an intuition for the process. Your decomposition may not be strictly linear; that's okay. But it should be progressive.
• Perhaps the most important point: At every step, try to have a full, working application. That means the Teachpack may need to export several interfaces, each one taking more parameters and accepting more functionality than the previous one. Otherwise the student needs to have all the parts working before they can understand whether even one works in context, leading to a frustrating learning experience and encouraging wanton hacking as they try (and invariably fail) to quickly get to a working system.
• Design interfaces carefully to make judicious use of first-class functions. It is inevitable that students will need to provide functions (not just flat data) to what your Teachpack exports. Show them the invocations of your Teachpack in terms of named functions (that they define).
• Try to provide a few extra-credit routes for ambitious students. Options include letting students peel back even more of the Teachpack, or adding interesting features.