系统课程自动评分的经验

D. Rao
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引用次数: 4

摘要

大学校园中计算机课程规模的迅速增长对教学资源和人员构成了挑战。我们开发了一个自动测试和评分软件系统,称为代码评估扩展(Code)。它与我们现有的Canvas学习管理系统(LMS)集成。本文从学生和教师的角度介绍了在初级系统课程中使用自动评分的经验,该课程着重于c++编程,并面临一些挑战,包括-①本课程是学生和教师第一次使用任何形式的自动评分,②学生对c++编程的经验有限,特别是在Linux中,③课程包括操作系统的复杂概念。多线程和网络。本文给出了3300份提交的定量结果(来自1门课程,1个学期,6个编程作业,54名学生,每个学生每次作业的多份提交),并分析了54名学生的课程结束调查。统计数据的推论有力地支持使用自动评分系统,例如CODE,来加强以编程为中心的课程的学习。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experiences With Auto-Grading in a Systems Course
Rapidly growing computing-class sizes across college campuses are challenging instructional resources and staffing. We have developed an automatic testing and grading software system called Code Assessment Extension (CODE). It is integrated with our existing Canvas Learning Management System (LMS). This paper presents experiences from both student and instructor perspectives with using auto-grading in a junior-level, systems course with a heavy emphasis on programming in C++, with several challenges, including - ① this course was the first experience for both the students and the instructor in using any form of automatic grading, ② the students have limited experience with C++ programming, particularly in Linux, and ③ the course includes complex concepts on operating systems, multithreading, and networking. The paper presents quantitative results from 3,300 submissions (from 1 course, 1 semester, 6 programming assignments, 54 students, multiple submissions per-student per-assignment) and analysis of end-of-course surveys from 54 students. The inferences from the statistics strongly support the use of automatic grading systems such as CODE to enhance learning in programming-centric courses.
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