EAGER: Impact of Generative Artificial Intelligence (GAI) on Engineering Education Practices

人工智能(AI)的进步几乎影响着工程专业的方方面面。生成式人工智能(GAI)的最新发展和Grammarly、ChatGPT、GitHub Copilot等技术的流行正在改变工程师沟通、设计、编码和教学的方式，创造了效率和潜在的新机会，特别是对于GAI技术可以降低门槛的边缘化个人。鉴于这些技术对工程专业的潜在影响，工程教育工作者必须意识到GAI，并能够有效地将其用于教学和工程教育研究。该项目将探讨GAI技术对工程研究和教学界的影响，同时开发和评估支持在研究和教学实践中采用和整合这些技术的方法和资源。通过这一项目，该项目将支持未来工程师的形成和劳动力发展。此外，鉴于GAI的使用也引发了需要解决的新的伦理挑战，这项工作还将评估工程教育工作者如何负责任地使用GAI。无论是在研究中，还是在数据分析和写作中，在想法产生中，在教学中，在计划课程或练习时。通过帮助工程教育社区以最佳方式接受GAI，该项目将允许不同的利益相关者利用GAI。这个项目的发现将被教育工作者用来改进工程教育、研究和教学，并对当前和未来工程师的准备产生更广泛的影响。通过结合文献回顾和在线数据收集和分析，该项目将确定工程教育研究和教学如何潜在地纳入基于地理信息系统的应用程序。以下具体的研究问题将指导该项目：1)GAI目前如何用于相关领域的研究和教学，如计算机和STEM教育，以及对工程教育的影响？2)目前工程教育工作者对GAI的认识与他们的研究和教学活动有关？3)哪些用例和场景可以帮助有效和负责任地将GAI用于工程教育研究和教学？为了解决这些问题，将与研究人员和教育工作者共同举办合作设计研讨会。通过这些讲习班，将开发和评估在工程教育中使用GAI的情景。下一步，研究人员和教师将被要求将这些场景纳入他们的工作流程，以便进一步评估它们的可用性和实用性。利用用户提供的反馈，该项目将创建并免费传播一套为从事工程教育研究或教授工程学的人设计的场景和指导方针。通过这个项目，社区还将受益于与在工程教育中使用GAI有关的对话和辩论的机会。这项工作将为建设社会技术基础设施奠定基础，这对促进在工程教育中有效和负责任地使用GAI至关重要。考虑到GAI塑造工程教育的潜力，这个项目可能是一个潜在更大项目的第一次迭代。最后，该项目还将通过确定GAIS和相关技术的使用障碍以及这可能如何限制更具包容性的工程教育的目标，并概述负责任和合乎道德地使用技术的指导方针来做出贡献。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Advances in Artificial Intelligence (AI) are affecting almost all aspects of the engineering profession. Recent developments in Generative AI (GAI) and the popularity of technologies like Grammarly, ChatGPT, GitHub CoPilot are changing the way that engineers communicate, design, code, and teach, creating efficiencies and potentially new opportunities, particularly for marginalized individuals for whom GAI technologies can lower barriers. Given the potential impact of these technologies on the engineering profession, it is imperative that engineering educators are both aware of GAI and able to use it productively for teaching and for engineering education research. This project will explore the impact of GAI technologies on the engineering research and teaching community while developing and evaluating methods as well as resources for supporting the adoption and integration of these technologies in research and teaching practices. Through this, the project will support the formation of future engineers and workforce development. In addition, given that the use of GAI is also giving rise to novel ethical challenges that need to be addressed, this work will also evaluate how engineering educators can use GAI responsibly. Whether in research, for data analysis and writing, and idea generation, or in teaching, for planning lessons or exercises. By helping the engineering education community embrace GAI in optimal ways this project will allow diverse stakeholders to take advantage of GAI. Findings from this project will be leveraged by educators to improve engineering education research and teaching with broader impact on the preparation of current and future engineers. Through a combination of literature review and online data collection and analysis, the project will identify how engineering education research and teaching can potentially incorporate GAI based applications. The following specific research questions will guide the project: 1) How is GAI currently being used for research and teaching in related fields, such as computing and STEM education, and what are the implications for engineering education? 2) What is the current awareness of GAI among engineering educators in relation to their research and teaching activities? 3) What use cases and scenarios can assist with effective and responsible use of GAI for engineering education research and teaching? To address these questions, collaborative co-design workshops with researchers and educators will be undertaken. Through these workshops, scenarios for the use of GAI within engineering education will be developed and evaluated. As a next step, researchers and instructors will be asked to incorporate the scenarios into their workflow so that their usability and utility can be further assessed. Using the feedback provided by the users, the project will create and freely disseminate a set of scenarios and guidelines designed for those who do engineering education research or teach engineering. Through this project, the community will also benefit through opportunities for dialogues and debates related to the use of GAI in engineering education. This work will lay the foundation for building socio-technical infrastructure essential for facilitating effective and responsible use of GAI within engineering education. Given the potential for GAI to shape engineering education, this project can be the first iteration of a potentially larger project. Finally, the project will also contribute by identifying barriers to the use of GAIs and related technology and how that might restrict the goals of more inclusive engineering education and outline guidelines for responsible and ethical use of the technology.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.