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UVA SEAS Resources: Teaching GenAI for Engineering Design and Analysis

This collection compiles course materials developed by UVA School of Engineering and Applied Sciences faculty to teach students how to use generative AI for engineering design and analysis. Any examples of student work are shared with students' permission.

Course and Assignment Design
Updated February 2024
Jeffrey Saucerman headshot
Jeffrey Saucerman
Professor
School of Medicine
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Leyf Starling headshot
Leyf Starling
Lecturer
Engineering Foundations
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Analyzing ChatGPT-Proposed Solutions to Sustainability-Focused Problems

Leyf Starling

This resource summarizes an activity designed to actively engage first-year engineering students in (1) evaluating and analyzing the content ChatGPT generates and (2) discussing the role ChatGPT or other generative AI tools can or should play in various parts of the engineering design process.

Headshot of Jeffrey SaucermanHeadshot of Leyf Starling
Jeffrey Saucerman, Leyf Starling

We assigned this activity in all ENGR 1010 courses in Fall 2023 and plan on using it again because it allowed for meaningful and impactful discussions with students about the use of generative AI in the engineering design process. Instructors can easily adapt this activity to their own contexts.

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We all know tools like ChatGPT can generate information and interesting arguments when given a prompt. The real question is: do you trust what ChatGPT generates? It is your responsibility to actively challenge, question, and analyze arguments AI generates in response to your prompts. This activity is aimed at intentionally making you think about, analyze, and discuss:

  • Solutions to your proposed sustainability problem (including given constraints and success criteria)

  • Using tools like ChatGPT to gain and analyze information

  • Determining accuracy of facts included in arguments generated by an AI tool like ChatGPT

  • Analyzing the efficacy and logic presented in response to your prompt

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Using Generative AI to Aid Computer Programming of Numerical Methods

Jeff Saucerman

This resource includes a lecture on using generative AI for programming in BME 2315: Computational Biomedical Engineering. It also includes the results of an anonymous evaluation for course improvement, related to how using generative AI affects coding performance and confidence.

Headshot of Jeffrey SaucermanHeadshot of Leyf Starling
Jeffrey Saucerman, Leyf Starling

By reviewing these slides, instructors can see concrete examples of how we taught students to use ChatGPT and other generative AI tools for programming and integrated generative AI into programming assignments on numerical methods in BME 2315: Computational Biomedical Engineering. The anonymous course improvement evaluation provides insight into how students experienced generative AI in the course.

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Lecture Slides on the Technical Foundations for Generative AI

Jane (Yanjun) Qi

This lecture on Large Language Models from Dr. Jane (Yanjun) Qi's Spring 2024 graduate-level course, CS 6501: GenAI Risk and Benefits, explains the technical foundations for a growing range of GenAI technologies, including ChatGPT and image generation from DALL-E 3, stable diffusion, and latent diffusion models.

Headshot of Jeffrey SaucermanHeadshot of Leyf Starling
Jeffrey Saucerman, Leyf Starling

This resource nicely complements others in this collection by illustrating how generative AI technologies are taught at a different level: in a graduate-level Computer Science course.

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