Harnessing the Wisdom of the Classes: Classsourcing and Machine Learning for Assessment Instrument Generation

Harnessing the Wisdom of the Classes: Classsourcing and Machine Learning for Assessment Instrument Generation
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利用课堂的智慧:用于生成评估工具的课堂外包和机器学习

DOI:
10.1145/3287324.3287504
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发表时间:
2019
期刊:
SIGCSE
影响因子:
--
通讯作者:
Tunnell Wilson, Preston
Tunnell Wilson, Preston
中科院分区:
--
文献类型:
--
作者:
Saarinen, Sam;Krishnamurthi, Shriram;Fisler, Kathi;Tunnell Wilson, Preston

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生成问题来吸引和衡量学生通常是具有挑战性的,而且很耗时。此外,由于背景、课程重点或问题或答案的模棱两可,这些问题并不总是在学生群体之间很好地转移。我们介绍了一个由机器学习促进的有贡献的学生教育学活动,它可以生成具有关联答案推理集的问题。我们称这个过程为自适应工具驱动的概念生成。已经部署了一个实现这一过程的工具,它明确地优化了对存在学生意见分歧的问题的过程。在一项涉及Java数组的研究中,这种新颖的过程:生成与专家设计的问题类似的问题,生成识别潜在学生误解的新颖问题,并提供对误解流行率的统计估计。这一过程允许以较少的专家努力产生测验和讨论问题,促进了创建概念清单的子过程,并增加了以相对较低的成本开展再生产研究的可能性。
Generating questions to engage and measure students is often challenging and time-consuming. Furthermore, these questions do not always transfer well between student populations due to differences in background, course emphasis, or ambiguity in the questions or answers. We introduce a contributing student pedagogy activity facilitated by machine learning that can generate questions with associated answer-reasoning sets. We call this process Adaptive Tool-Driven Conception Generation. A tool implementing this process has been deployed, and it explicitly optimizes the process for questions that divide student opinion. In a study involving arrays in Java, this novel process: generates questions similar to expert-designed questions, produces novel questions that identify potential student misconceptions, and provides statistical estimates of the prevalence of misconceptions. This process allows the generation of quiz and discussion questions with less expert effort, facilitates a subprocess in the creation of concept inventories, and also raises the possibility of running reproduction studies relatively cheaply.
概念清单评估工具的进展
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