2026 ASEE Annual Conference & Exposition

The standard workflow of 3d printing is an elaborate process which starts with developing a 3d model all the way to developing a final G-code that can be processed by a 3D printer. It requires proficiency in 3D modeling which can be a barrier for emerging professionals in manufacturing. The emergence of generative AI in manufacturing simplifies this process to some extent for the users who have access to the software with LLM support can develop G-codes from natural language. While this lowers the restrictions, the paid access to these software products still presents a barrier. With researchers being able to leverage LLM’s capabilities to directly generate G-codes using Retrieval Augmented Generation (RAG) prompting, the avenue of using LLM should be extended in education too. This study presents a workshop approach to teaching prompt engineering to engineering students for developing G-Codes as a manufacturing skill. The workshop design uses the ICAP framework to ensure maximum cognitive engagement. The workshop opens with an introduction to LLMs and standard workflow of 3d printing. This is followed by a structured dialogue exploring the avenues of skipping 3D modeling steps, and then a hands-on prompt generating activity. As a proof of concept, the presenter generates G-Code for a cube with their initial using RAG-based prompting, without software. This approach positions G-code generation using prompt engineering as a teachable workforce skill, improving access to learners without software background. Future works can pilot this workshop and assess the learning outcomes in AI literacy and manufacturing workforce skilling.