Conference Session

Generative AI and Its Role in Industrial Engineering

Collection

2025 ASEE Annual Conference & Exposition

Authors

THOMAS AMING'A OMWANDO, Simpson University; Adel Alhalawani, Rose-Hulman Institute of Technology; Ashutosh Khandha, University of Delaware; Bhavana Kotla, The Ohio State University

Tagged Topics

Diversity

Tagged Divisions

Industrial Engineering Division (IED)

[10], [13].Ethical concerns also emerge with the use of GenAI in assessments. Misuse of these tools canlead to academic dishonesty and reduce student accountability [11], [17]. Maintaining academicintegrity is critical, as it ensures students engage meaningfully with assessment criteria [5], [18].Transparency in the role of GenAI in grading processes is essential to build trust among studentsand educators [16].Bias and validity present further challenges. AI tools require extensive training to avoid biasesand ensure fairness across diverse student populations [1], [3]. Unfortunately, biases present inthe training data of GenAI models can result in inconsistencies and fairness concerns in grading[6], [13]. Additionally, rubrics designed with

Conference Session

Bridging Education and Real-World Impact: Training, Career Development, and Urban Systems

Collection

2025 ASEE Annual Conference & Exposition

Authors

Hayley N. Nielsen, University of Michigan; Vibhavari Vempala, University of Michigan; Berenice Alejandra Cabrera, University of Michigan; Lisa R. Lattuca, University of Michigan; Erika A Mosyjowski, University of Michigan; Joi-Lynn Mondisa, University of Michigan; Shanna R. Daly, University of Michigan

Tagged Topics

Diversity

Tagged Divisions

Industrial Engineering Division (IED)

students viewsocial and contextual skills and knowledge as central to careers in IE and their reflections on howtheir required coursework has prepared them for their future careers. Implications for futureresearch and practice are discussed.IntroductionEngineering is increasingly recognized as a discipline that requires attention not only to thetechnical work aspects but also to the social contexts in which the work occurs and the broaderimpacts of engineering on communities and society [1] - [4]. The social and contextual nature ofengineering work has been recognized by the Accreditation Board for Engineering andTechnology (ABET), which outlines student outcomes that recognize the importance ofconsidering the social, cultural, ethical, and

Conference Session

Generative AI and Its Role in Industrial Engineering

Collection

2025 ASEE Annual Conference & Exposition

Authors

Edward James Isoghie, University of Louisville; Jason J Saleem, University of Louisville; Thomas Tretter, University of Louisville; Jeffrey Lloyd Hieb, University of Louisville

Tagged Divisions

Industrial Engineering Division (IED)

varying results for identical questions. Wang [32]examined the application of OpenAI's GPT models (GPT-3.5, GPT-4.0, and GPT-4o) inanswering semi-structured interview questions related to the impact of generative AI on riskmanagement. The study found that GPT models are effective in generating realistic interviewresponses, enabling researchers to refine questions and methodologies before engaging humanparticipants.Despite the benefits of generative AI, its use presents several challenges, including hallucination,sensitivity to prompt phrasing, algorithmic bias, and ethical concerns. Nonetheless, most studieshave utilized it to respond to interview questions, identify themes in qualitative analysis, andcompare its performance to human-generated

Conference Session

Generative AI and Its Role in Industrial Engineering

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nadiye O. Erdil, University of New Haven

Tagged Topics

Diversity

Tagged Divisions

Industrial Engineering Division (IED)

evaluatewhether students’ collaboration with generative AI tools reflects their proficiency in the technicaldomain and provide further insights into how to best prepare students for the rapidly evolvingworkplace.Lastly, it is important to acknowledge the concerns and risks associated with using generative AI,which were a limitation in this study. Some issues were taken into consideration; for example,students were expected to critically examine the responses and refine them based on keyprinciples and concepts of the technical field to eliminate any inaccuracies or oversights.However, other aspects, such as ethical use, bias, and data privacy, were beyond the scope of thispaper. These elements should also be addressed as part of student training on