Strategy-based feedback in a programming tutor

Abstract

More and more people take up learning how to program: in schools and universities, in large open online courses or by learning it by themselves. A large number of tools have been developed over the years to support learners with the difficult task of building programs. Many of these tools focus on the resulting program and not on the process: they fail to help the student to take the necessary steps towards the final program. We have developed a prototype of a programming tutor to help students with feedback and hints to progress towards a solution for an introductory imperative programming problem. We draw upon the ideas of a similar tutor for functional programming and translate these ideas to a different paradigm. Our tutor is based on model solutions from which a programming strategy is derived, capturing the different paths to these solutions. We allow for variation by expanding the strategy with alternatives and using program transformations. The instructor is able to adapt the behaviour of the tutor by annotating the model solutions. We show a tutoring session to demonstrate that a student can arrive at a solution by following the generated hints. We have found that we can recognise between 33% and 75% of student solutions to three programming exercises that are similar to a model solution, which we can increase by incorporating more variations.