This work in computing education research builds foundation for a new activity type and approach to learning principles of programming. Our aim is to improve learning through increased reflection, self-explanation, and a gentle push towards deeper learning. Below we outline the articles and future work that this research project is producing.
From this paper: "a student with a program that works is not the same as a student who understands why and how the program works". After learner has created a program, we propose that questions about the properties and behaviour of their program can be automatically generated. We discuss what kind of reflection and other effects could follow when such questions are posed to the learner after they created a program. Furthermore, we discuss how such system could be created.
This article defines the Qustions About Learners' Code (QLCs) and discusses the possible opportunities and challenges. On the right, we include a recording of the article presentation at the conference.
This early study identifies a potential in the QLCs approach. We used open-ended questions that were geared to target specifics of the learner's own program. This article adds to the evidence that some learners struggle to explain their own functionally correct program code. In addition, correct explanations did correlate with increased course success and retention.
First QLC experiments were conducted in Spring 2021. In the autumn, we collect more data on students working on QLC tasks. We plan both qualitative and quantitative analysis on how these tasks are experienced and answered.