Grading at scale in earsketch

Avneesh Sarwate, Creston Brunch, Jason Freeman, S. Siva
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引用次数: 5

Abstract

This paper explores some of the challenges posed by automated grading of programming assignments in a STEAM (Science, Technology, Engineering, Art, and Math) based curriculum, as well as how these challenges are addressed in the automatic grading processes used in EarSketch, a music-based educational programming environment developed at Georgia Tech. This work-in-progress paper reviews common strategies for grading programming assignments at scale and discusses how they are combined in EarSketch to evaluate open ended STEAM-focused assignments.
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本文探讨了基于STEAM(科学、技术、工程、艺术和数学)课程的编程作业自动评分所带来的一些挑战,以及如何在EarSketch中使用的自动评分过程中解决这些挑战。这是佐治亚理工学院开发的一种基于音乐的教育编程环境。这篇正在进行中的论文回顾了大规模评分编程作业的常用策略,并讨论了如何在EarSketch中组合它们来评估开放式的以steam为重点的作业。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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