Intentional Infusion of Generative AI in a Human-Machine Systems Engineering Course: Assessment with Adoptable and Adaptable Strategies
Year: 2025
Type: conference-paper
Abstract: Generative artificial intelligence (Gen AI) uses algorithms to create new content including images, computer code, audio, presentations, simulations, animations, and more.In a Human-Machine Systems Engineering (HMS) course, the use of Gen AI was discussed, addressed, and integrated with intentionality.The full infusion process in the course was gradual and measured, and is discussed in the body of this paper.The assignment allowing the most extensive use of AI was called the Expert Seminar for which students were commissioned to create a scholarly research-based presentation on a human-systems integration topic and deliver it to the class with a planned learning activity.In the multistage preparation process, students were allowed to use Gen AI for ideation, framing, locating scholarly sources, and even for helping to create the presentation script.The terms were (1) students were not allowed to read from any notes when presenting, (2) concepts must be drawn from linkable scholarly research, and (3) students were responsible for the accuracy and quality of the seminar content and delivery based on HMS course principles.Along with the assignment write-up, students were asked to outline the advantages and drawbacks of using AI for such academic work.Of the 56 respondents, there were 115 openended responses indicating the merits of using Gen AI for this type of project and 121 responses outlining the less effective and concerning aspects of its use.The primary categories of positive responses reflected how students felt AI benefited them in organizing the seminar framework and in saving time.The most common detriments noted by students related to the effect on their work creativity and ownership as well as AI's tendency to misinterpret course topics and vocabulary.The codified reflections are very telling and have enhanced the professor's understanding of AI capabilities and students' perspectives.Further, this research has informed future framing of AI use for classes and projects, providing clarity for inclusion of various AI options in future course offerings.This work can help bridge the perceived gap between students and educators on the use of Gen AI by keeping the conversation open.
Author: B. Kris Jaeger-Helton
Institution: Northeastern University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4409905285