从本科的角度来看,生成人工智能工具在塑造机械工程教育中的作用
Harshal Akolekar1,2, Piyush Jhamnani1, Vikash Kumar1
1Department of Mechanical Engineering, Indian Institute of Technology, Jodhpur, 342030, India.
Scientific reports
|March 18, 2025
概括
像Copilot,Gemini和ChatGPT这样的生成人工智能工具在工程教育中表现有前途,但在复杂的数值问题上扎. 负责任的整合和适应的评估是人工智能辅助学习的关键.
科学领域:
- 工程教育 工程教育教育
- 人工智能应用程序 人工智能应用程序
背景情况:
- 生成性人工智能在高等教育中越来越普遍.
- 它在机械工程等专业领域的有效性需要彻底评估.
研究的目的:
- 评估ChatGPT,Gemini和Copilot在本科机械工程教育中的表现.
- 了解学生和教育工作者对AI整合的看法.
主要方法:
- 混合方法方法评估AI工具在七个核心机械工程学科的800个问题上.
- 量化绩效分析补充了学生调查 (n=172) 和采访 (n=20) 的定性数据.
主要成果:
- 所有的人工智能工具在基于理论的问题上表现良好,但在数值问题解决上却失败了.
- 在准确度方面,Copilot (60.38%) 的表现优于Gemini (57.13%) 和ChatGPT (46.63%).
- 学生的反强调了人们对AI在数值任务中的可靠性以及对批判性思维的潜在影响的担忧.
结论:
- 人工智能工具可以支持工程教育,但数值任务的局限性需要仔细整合课程.
- 为负责任地采用人工智能和调整评估策略提供了建议.
- 需要进一步的研究来优化AI在培养未来工程师中的作用.
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