在线编程课程中提交材料的质量分析

Maria Tigina, Anastasiia Birillo, Yaroslav Golubev, H. Keuning, Nikolay Vyahhi, T. Bryksin
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引用次数: 1

摘要

编程教育的目标应该是为学生提供广泛的技能,以便他们以后在开发软件时使用。其中一个重要的方面是他们编写代码的能力,不仅正确而且质量高。不幸的是,这在大规模的在线开放课程中是很难控制的。在本文中,我们对JetBrains Academy提交的代码质量进行了分析。JetBrains Academy是一个用于在类似于行业的基于项目的环境中研究编程的平台,它带有一个名为Hyperstyle的嵌入式代码质量评估工具。我们分析了100多万份Java提交和130多万份Python提交,研究了最普遍的代码质量问题类型以及学生如何修复它们的动态。我们提供了几个不同问题的案例研究,以及为什么某些问题在多次尝试后仍未解决的分析。此外,我们还研究了异常长的提交序列,其中学生在通过任务后试图修复代码质量问题。我们的研究结果为在线课程的改进指明了方向,比如确保任务本身不会激励学生写出糟糕的代码。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analyzing the Quality of Submissions in Online Programming Courses
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.
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