Conference Session

Multidisciplinary Engineering Division (MULTI) Technical Session 11

Collection

2025 ASEE Annual Conference & Exposition

Authors

Stephen Andrew Wilkerson P.E., York College of Pennsylvania; Scott F. Kiefer, York College of Pennsylvania; Yargo Teixeira Gomes de Melo, York College of Pennsylvania

Tagged Divisions

Multidisciplinary Engineering Division (MULTI)

integrated into several engineering courses and consider potentialmethods for measuring the growth of its use by students.ChatGPT, in particular, has been extensively used by students for writing code, debugging code,refining term papers, and understanding complex problems. In several Fall 2024 classes, studentsreported increasing reliance on ChatGPT for assistance with their academic assignments. Wepresent several examples where students were encouraged to consult ChatGPT for help incompleting projects and assignments. In some cases, we found that students benefited from AIassistance. For instance, students who were stuck on specific algebraic problems orprogramming tasks were able to quickly access help or debug code, enabling them to

Conference Session

Multidisciplinary Engineering Division (MULTI) Technical Session 8

Collection

2025 ASEE Annual Conference & Exposition

Authors

Resha Tejpaul, University of Minnesota ; Travis Henderson; Nicole Kennedy; Nikos Papanikolopoulos, University of Minnesota - Twin Cities

Tagged Divisions

Multidisciplinary Engineering Division (MULTI)

findings reflect broadertrends observed in higher education; for instance, a recent global survey indicated that 24% ofstudents employ AI tools daily, and over half utilize them at least weekly [7]. Our cohort, beingpart of a technology-oriented graduate program, appears even more inclined toward frequent useof GenAI.Figure 1: Distribution of self-reported frequency of GenAI tool usage among Robotics MS students(N=19). About 47.3% use GenAI tools “Frequently” (weekly) or “Almost Daily,” while a minority(about 5.3%) use them rarely or never.As shown in Figure 2, ChatGPT is the leading GenAI platform among students, with nearly 90%utilizing it for academic tasks. Google’s Bard is accessed by approximately 50% of students,serving as an alternative to

Conference Session

Multidisciplinary Engineering Division (MULTI) Technical Session 8

Collection

2025 ASEE Annual Conference & Exposition

Authors

Pooya Niksiar, The Citadel; Dimitra Michalaka P.E., The Citadel

Tagged Divisions

Multidisciplinary Engineering Division (MULTI)

OpenAI’s ChatGPT and DALL·E, have been utilized to supportdiverse educational needs, including content creation, question generation, and adaptive learningenvironments. For instance, generative AI can create dynamic learning modules tailored toindividual student needs, enabling differentiated instruction and addressing varying levels ofprior knowledge [5,6]. This personalization is particularly valuable in engineering education,where students often face challenges in grasping complex concepts. In addition to personalizedinstruction, generative AI aids instructors by automating administrative tasks, such as gradingand feedback provision. Automated grading tools powered by AI can evaluate assignments andexams efficiently while providing detailed

Conference Session

Multidisciplinary Engineering Division (MULTI) Technical Session 8

Collection

2025 ASEE Annual Conference & Exposition

Authors

Liuying Gong, School of Public Affairs, Zhejiang University; Jingyuan Chen; Min Ye, Zhejiang University

Tagged Divisions

Multidisciplinary Engineering Division (MULTI)

implication: Taking Zhejiang University as an Example,”(in Chinese), Open Educ. Res., vol. 30, no. 1, pp. 89–98, 2024, doi:10.13966/j.cnki.kfjyyj.2024.01.010.[7] A. M. Al-Abdullatif and M. A. Alsubaie, “ChatGPT in Learning: Assessing Students’ UseIntentions through the Lens of Perceived Value and the Influence of AI Literacy,” Behav. Sci.,vol. 14, no. 9, Sep. 2024, doi: 10.3390/bs14090845.[8] A. Alamaeki, C. Nyberg, A. Kimberley, and A. O. Salonen, “Artificial intelligence literacyin sustainable development: A learning experiment in higher education,” Front. Educ., vol. 9,Mar. 2024, doi: 10.3389/feduc.2024.1343406.[9] F. J. Cantú-Ortiz, N. Galeano Sánchez, L. Garrido, H. Terashima-Marin, and R. F. Brena,“An artificial intelligence educational