A Methodological Framework for Modernizing Engineering Course Content with Large Language Models
Year: 2026
Type: conference-paper
Abstract: The rapid evolution of technology presents challenges for engineering educators. While the core engineering methods often remain relevant over time, course materials rapidly become outdated in presentation and pedagogical approach. This paper presents a methodological framework for using large-language models (LLMs) to modernize engineering course content with a case study in an advanced technical analysis course. The methodology follows a phased approach that is designed to be repeatable and verify the accuracy and completeness of course content. During the first phase, an LLM is used to map outdated text-heavy content to a modern format using a LaTeX template. The second phase involves introducing the LLM to the entrepreneurial mindset developed by the Kern Entrepreneurial Engineering Network (KEEN), emphasizing curiosity, making connections, and creating value, and asking it to relate the modernized content to various engineering disciplines. The final phase involves human-in-the-loop review by the instructor to ensure that (1) all content has been successfully mapped, (2) the content is accurate, and (3) the connections are accurate and relevant. This study demonstrates a repeatable process for content transformation that can be applied to modernize the wealth of legacy engineering content that exists in order to promote engagement with students. The process is presented as a systematic workflow with sample prompts to serve as a blueprint for other educators. In addition, a case study for an advance technical analysis course demonstrates that the framework successfully translates complex technical content and code.
DOI: 10.18260/1-2--59000
Institution: Old Dominion University
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: green
Funder: Purdue University
OpenAlex ID: W7203893765