Using Context-Free Grammars to Scaffold and Automate Feedback in Precise Mathematical Writing

Using Context-Free Grammars to Scaffold and Automate Feedback in Precise Mathematical Writing
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使用上下文无关语法来构建和自动化精确数学写作中的反馈

DOI:
10.1145/3545945.3569728
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发表时间:
2023
期刊:
SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education
影响因子:
--
通讯作者:
Zilles, Craig
Zilles, Craig
中科院分区:
--
文献类型:
--
作者:
Xia, Jason;Zilles, Craig

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在技术写作中,某些陈述必须非常仔细地写,以便清晰准确地传达一个想法。学生们经常被要求写这些陈述来回应一个开放式的提示,这使得他们很难用传统的方法自动评分。我们提出了我们认为是一种新的方法,通过限制学生提交一个预定义的上下文无关的语法(由教师配置),这些语句自动分级。此外,我们的工具提供即时反馈,帮助学生提高他们的写作,并通过减少学生必须做出的选择的数量相比,自由形式的写作构建一个声明的过程支架。我们评估我们的工具部署在一个本科算法课程的作业。作业包含使用该工具的五个问题,之前是前测,之后是后测。我们观察到从前测试到后测试的统计学显著改善,平均得分从7.2/12增加到9.2/12。
In technical writing, certain statements must be written very carefully in order to clearly and precisely communicate an idea. Students are often asked to write these statements in response to an open-ended prompt, making them difficult to autograde with traditional methods. We present what we believe to be a novel approach for autograding these statements by restricting students' submissions to a pre-defined context-free grammar (configured by the instructor). In addition, our tool provides instantaneous feedback that helps students improve their writing, and it scaffolds the process of constructing a statement by reducing the number of choices students have to make compared to free-form writing. We evaluated our tool by deploying it on an assignment in an undergraduate algorithms course. The assignment contained five questions that used the tool, preceded by a pre-test and followed by a post-test. We observed a statistically significant improvement from the pre-test to the post-test, with the mean score increasing from 7.2/12 to 9.2/12.
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