arXiv 2407.126932024-07cs.CYcs.GT

如何在工程教育中缓解对ChatGPT-4o的依赖

How to Mitigate the Dependencies of ChatGPT-4o in Engineering Education

Maoyang Xiang, T. Hui Teo

备注：: 6 pages, 1 figure, 1 table

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AI总结：

针对大型多模态模型在工程教育中引发的过度依赖问题，提出课程策略以减少对ChatGPT-4o的依赖，通过实际课程验证，有效提升学生参与度和理解力。

摘要：

大型多模态模型（LMMs）的快速发展显著影响了现代教学与学习，尤其是在计算机工程领域。虽然LMMs为增强学习提供了广泛机会，但它们也冒着削弱传统教学方法并助长对自动化解决方案过度依赖的风险。为应对这一问题，我们在课程中制定了策略，以减少对以ChatGPT-4o为代表的LMMs的依赖。这些策略包括设计鼓励动手解决问题的课程主题。所提出的策略通过实际课程实施进行了演示。初步结果显示，这些方法有效提升了学生的参与度和理解力，在技术优势与传统学习原则的保留之间取得了平衡。

英文摘要：

The rapid evolution of large multimodal models (LMMs) has significantly impacted modern teaching and learning, especially in computer engineering. While LMMs offer extensive opportunities for enhancing learning, they also risk undermining traditional teaching methods and fostering excessive reliance on automated solutions. To counter this, we have developed strategies within curriculum to reduce the dependencies on LMMs that represented by ChatGPT-4o. These include designing course topics that encourage hands-on problem-solving. The proposed strategies were demonstrated through an actual course implementation. Preliminary results show that the methods effectively enhance student engagement and understanding, balancing the benefits of technology with the preservation of traditional learning principles.

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