Toward AI-assisted Exercise Creation for First Course in Programming through Adversarial Examples of AI Models

William Chan, Y. T. Yu, J. Keung, Victor C.S. Lee
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Abstract

We propose a new methodology, the Exercise Creation Methodology (ECM), that leverages recent AI technology advancements to create ChatGPT-assisted programming exercises for beginners. ECM takes an existing exercise as input and mutates it by removing some contents into semantically equivalent but syntactically different versions. The pair of versions are labeled as answered correctly and misleadingly by ChatGPT. The removed contents are re-inserted incrementally with further mutation, ensuring the labels remain unchanged. Using the version with the misleading answer and the ChatGPT elaboration on the other version, we construct a ChatGPT-assisted exercise. The latter version may also serve as a solution. We illustrate ECM using a case study.
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通过人工智能模型的对抗性示例,探讨人工智能辅助编程第一课程的习题创建
我们提出了一种新的方法,即练习创建方法(ECM),该方法利用最近的人工智能技术进步为初学者创建chatgpt辅助编程练习。ECM将现有练习作为输入,并通过将一些内容删除为语义等效但语法不同的版本来对其进行修改。这两个版本被ChatGPT标记为正确答案和误导性答案。移除的内容将随着进一步的突变逐渐重新插入,以确保标签保持不变。使用具有误导性答案的版本和ChatGPT对另一个版本的阐述,我们构建了一个ChatGPT辅助练习。后一个版本也可以作为一种解决方案。我们用一个案例来说明ECM。
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