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Assessing the Impact of Artificial Intelligence on CS Education

$49,900FY2023EDUNSF

University Of California-Riverside, Riverside CA

Investigators

Abstract

This project aims to serve the national interest by hosting a workshop attended by leading computing education thinkers to discuss the role of Artificial Intelligence (AI) in education. AI will dramatically affect both students and instructors in the coming years. As with any new technology, the effects will include both negative and positive ones. AI has burst into the spotlight as having a large potential impact on education. Large language models (LLMs) gained tremendous attention upon the release of ChatGPT 3.5 in early 2023, leading to perhaps the fastest user-base growth curves in the history of the internet. The purpose of this workshop is to provide the computing education community with the opportunity to discuss how to best plan for the inevitable incorporation of AI into the lives of students and instructors. The goal of this workshop is to identify opportunities to minimize the negative effects of AI while enhancing the positive. This workshop will gather 10-15 of the nation's leading CS education thinkers to discuss AI's role in computing education. Attendees will lay out the roles that AI may play, positive and negative, for students and instructors. Attendees will summarize ideas within those roles, such as how AI might provide step-by-step programming guidance, or might auto-grade student work. Attendees will also call out pitfalls that the community should watch out for and lay out challenges that AI poses. The result will be a white paper highlighting the workshop's findings, and potentially a position paper submitted to a computing education conference. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. 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.

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