Why programming for non-CS students is different

There is a lot of literature in the CS community about the reasons students drop-out of introductory programming courses. There are two streams of students: those who will go on to immersive careers in computer science (e.g. software engineering), and those who will use programming as a tool in their discipline, maybe to analyze process data. The latter includes fields like finance, physics, and bioinformatics. They are two vastly different groups of people, and it is almost impossible to create one course that suits everyone. Teaching a course based on a language such as C or C++, which requires knowledge of low level concepts such as memory management, will alienate non-CS students. Spend too much time on high-level use of a language, and the CS-majors will miss critical information on low-level concepts.

Often it comes down to difficulties associated with the programming language being used to teach programming concepts. For example, non-CS students don’t really need to know about object-oriented programming – it often just complicates things from the perspective of building programs. Game developer John Carmack once said “Sometimes, the elegant implementation is just a function. Not a method. Not a class. Not a framework. Just a function“. They also don’t need to know that much about memory, and certainly not to the complexities of dynamic memory, or indeed complex ways of coding things to make a program more efficient, e.g. vectorization.

So what to teach a non-CS student in the way of learning to program?

  1. How programs can be used to solve real-world problems. This often involves the use of real-data, e.g. digital images. Computer-centric examples are often irrelevant for non-CS individuals.
  2. Focus on problem solving.
  3. How to formulate a problem as an algorithm. For example if the problem is  removing random noise from a monochromatic photograph – how do we do this?
  4. Learning the basic constructs of programming – making decisions, repeating things, how to store data (from a high-level perspective).
  5. Writing the programs to implement the the algorithms
  6. How to test programs.

Choice of language is extremely important, and from that perspective Julia is a perfect language to teach novice programmers who don’t want to make a career of it, but want the skills to help them in their disciplines. Teaching programming can also be moved to a more experiential process, whereby languages syntax is introduced as they are used in the problem solving context.


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