Experience Report: Standards-Based Grading at Scale in Algorithms

Experience Report: Standards-Based Grading at Scale in Algorithms
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经验报告:算法中基于标准的大规模分级

DOI:
10.1145/3502718.3524750
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发表时间:
2022
期刊:
27th ACM Conference on on Innovation and Technology in Computer Science Education
影响因子:
--
通讯作者:
Levet, Michael
Levet, Michael
中科院分区:
--
文献类型:
--
作者:
Chen, Lijun;Grochow, Joshua A.;Layer, Ryan;Levet, Michael

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我们报告了我们在算法课程中大规模实施基于标准的评分的经验,该课程作为我们系本科课程的终端必修CS理论课。这门课程有200-400名学生,由两名讲师、八名研究生助教授课,另外还有两名年级学生和几名本科生助教。我们强调基于标准的评分(SBG)在COVID-19大流行期间为学生提供支持方面的作用。最后,我们详细介绍了我们将对课程结构做出的成功和调整。
We report our experiences implementing standards-based grading at scale in an Algorithms course, which serves as the terminal required CS Theory course in our department's undergraduate curriculum. The course had 200-400 students, taught by two instructors, eight graduate teaching assistants, and supported by two additional graders and several undergraduate course assistants. We highlight the role of standards-based grading (SBG) in supporting our students during the COVID-19 pandemic. We conclude by detailing the successes and adjustments we would make to the course structure.
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