Contribution: The design of an operating system (OS) experiment course with a gentle learning curve is proposed and a scalable OS experiment platform supporting learning behavior analysis is presented. Background: In the teaching practice of the OS experiment course, several problems were faced. First, the learning curve for the students is too steep. Second, the OS experiment is hard to scale to a large number of students. Finally, it is difficult to track the learning behaviors of the students and to provide feedback to the teaching plan. Intended Outcomes: By smoothing the learning curve and providing targeted and rapid feedback, students using the system can more effectively master the knowledge of the OS by completing experimental tasks. Application Design: A large number of students can log in to the experiment system and complete multiple labs online. In addition to using automated testing to provide fast feedback, the lab system also collects learning behavior data of the students, enabling the teachers to analyze the data and adjust their teaching plan accordingly. Findings: The performance and learning-behavior data of the students from 2015 to 2018 showed that the OS experiment is effective to scale to a large number of students with satisfiable teaching effectiveness.

中文翻译：

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支持学习行为分析的可扩展操作系统实验平台

贡献： 提出了具有平缓学习曲线的操作系统（OS）实验课程的设计，并提出了支持学习行为分析的可扩展操作系统实验平台。背景：在OS实验课的教学实践中，遇到了几个问题。首先，学生的学习曲线太陡峭。其次，OS 实验很难扩展到大量学生。最后，很难跟踪学生的学习行为并为教学计划提供反馈。预期成果：通过平滑学习曲线并提供有针对性的快速反馈，使用该系统的学生可以通过完成实验任务更有效地掌握操作系统知识。应用设计：大量学生可以登录实验系统，在线完成多个实验。除了使用自动化测试提供快速反馈外，实验室系统还收集学生的学习行为数据，使教师能够分析数据并相应地调整教学计划。结果：2015年至2018年学生的表现和学习行为数据表明，OS实验可有效扩展到大量学生，教学效果令人满意。