Analyzing the Quality of Submissions in Online Programming Courses

Abstract

Programming education should aim to provide students with a broad range of skills that they will later use while developing software. An important aspect in this is their ability to write code that is not only correct but also of high quality. Unfortunately, this is difficult to control in the setting of a massive open online course. In this paper, we carry out an analysis of the code quality of submissions from JetBrains Academy -a platform for studying programming in an industry-like project-based setting with an embedded code quality assessment tool called Hyperstyle. We analyzed more than a million Java submissions and more than 1.3 million Python submissions, studied the most prevalent types of code quality issues and the dynamics of how students fix them. We provide several case studies of different issues, as well as an analysis of why certain issues remain unfixed even after several attempts. Also, we studied abnormally long sequences of submissions, in which students attempted to fix code quality issues after passing the task. Our results point the way towards the improvement of online courses, such as making sure that the task itself does not incentivize students to write code poorly.

Detecting Code Quality Issues in Pre-written Templates of Programming Tasks in Online Courses

“…In addition, they studied how students attempt to correct these problems over time. Similar research has been done for other languages, such as Scratch [6,27,28], C++ [8], and Python [24,25,29]. These kinds of studies can be useful both in the development of code quality detection tools and computer science courses.…”

“…(2) If a new task needs to be added to the platform, it is enough to provide the algorithm with at least one reference solution (or several with different approaches) to find code quality issues in the template and eliminate them before publishing the task. (3) When conducting research on code quality issues in student submissions, it is possible to use the algorithm to eliminate those that were not made by students, as was done in our recent work [29].…”