Conference Session

AI in the Engineering Management Classroom

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nahid Vesali, The Citadel

Tagged Divisions

Engineering Management Division (EMD)

Paper ID #49017Developing Critical Thinking in Engineering Management through AI-BasedScheduling Assignments: A Study of Copilot, ChatGPT, Gemini and PMIInfinityDr. Nahid Vesali, The Citadel Dr. Nahid Vesali is an Assistant Professor in the Department of Engineering Leadership and Program Management (ELPM) in the School of Engineering (SOE) at The Citadel. She joined the program in Aug 2020. She teaches project management, technical planning ©American Society for Engineering Education, 2025 Developing Critical Thinking in Engineering Management through AI-Based Scheduling Assignments: A

Conference Session

AI in the Engineering Management Classroom

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ekaterina Koromyslova, South Dakota State University; Bishnu karki, South Dakota State University; Prafulla Salunke, South Dakota State University; Carrie Steinlicht, South Dakota State University; Gary Anderson, South Dakota State University

Tagged Topics

Diversity

Tagged Divisions

Engineering Management Division (EMD)

prompt to AI. Thus, a lack of effective communications skills can compromise thequality of the generated output if the question is not clearly formulated, and the prompts are notrefined or elaborated. Moreover, without an expert to evaluate the generated solution, there is adanger that the solution is based on incorrect or biased information [16]. Unless the decisionmakers are able to critically evaluate the generated solutions, they may make costly mistakes.Farrokhnia, Banihashem, Noroozi, and Wals [17] completed a SWOT analysis of ChatGPT – agenerative AI tool which is commonly used in higher education by instructors and students. Theyidentified the following weaknesses and threats of generative AI: • Lack of deep understanding of the

Conference Session

AI in the Engineering Management Classroom

Collection

2025 ASEE Annual Conference & Exposition

Authors

Neil Littell, Ohio University

Tagged Divisions

Engineering Management Division (EMD)

. The destination and future use of the data that iscollected through interactions with the chatbot is unknown. Therefore, conversations with thechatbot should be limited to typical projects and assignments, not classified research or researchwhere intellectual property may be a concern. For example, as noted by [9], ChatGPT andpresumably other GPT and AI tools are not HIPAA compliant. As such, students and users of AIshould understand the privacy constraints concerning the use of their data.Bias – Bias appears to exist in the chatbots, perhaps as a result of the corpus of data that themodel was trained upon [8]. Bias was also cited as a concern by [9]. It is important thatconsumers of the output of chatbots understand this dynamic as an

Conference Session

AI in the Engineering Management Classroom

Collection

2025 ASEE Annual Conference & Exposition

Authors

Philip Appiah-Kubi, University of Dayton; Khalid Zouhri, University of Dayton; Yooneun Lee, University of Dayton

Tagged Divisions

Engineering Management Division (EMD)

respondentsexpress their lack of readiness to accept AI integration for performance monitoring and workloadassignment. Thus, since many engineering students are eventually going to graduate and becomeengineering managers who may utilize AI tools, engineering educators and researchers mustcontinue to explore ways to enhance students’ familiarity and proficiency with AI systems.LimitationsThis exploratory study utilized a limited sample in a randomized survey. Therefore, additionalwork is needed before the findings can be generalized.References[1] A. Kovari, "Explainable AI chatbots towards XAI ChatGPT: A review," Heliyon, vol. 11, no. 2, p. e42077, 2025/01/30/ 2025, doi: https://doi.org/10.1016/j.heliyon.2025.e42077.[2] M. V. Pusic and R. H

Conference Session

AI in the Engineering Management Classroom

Collection

2025 ASEE Annual Conference & Exposition

Authors

Edwin R Addison, North Carolina State University at Raleigh

Tagged Topics

Diversity

Tagged Divisions

Engineering Management Division (EMD)

processing, and transformer architectures and how they fit into larger systems • Generative adversarial networks and survey of AI methods (Bayesian reasoning, genetic algorithms, expert systems) and when they are used • Relationship with signal processing, pattern recognition, and data analytics • Open-source tools, data sourcing, licensing, and rights management • Data cleansing strategies and data cost estimation, including cost of data generation • LLMs, prompt engineering, ChatGPT, and organizational adoption and use • Multi-modal AI, agent-based models, and humanoid robotics • Computing infrastructure for AI, including compute requirements and platform selection • The disruptive impact of AI on the