Conference Session

NSF Grantees Poster Session II

Collection

2025 ASEE Annual Conference & Exposition

Authors

Justin L Hess, Purdue University at West Lafayette (COE); Robert P. Loweth, The University of North Carolina at Charlotte; Udeme Idem, Purdue University at West Lafayette (COE)

Tagged Topics

NSF Grantees Poster Session

,responsible, and nondiscriminatory uses of AI in education, including the impact AI systems haveon vulnerable and underserved communities.” Accordingly, there is a need to develop AI resourcesfor educational contexts (including engineering design) that bring clarity regarding AI’sresponsible and ethical use therein. Undergirding our project design is our belief that GenerativeAI can assist students in making more novel, inclusive, and ethical associations across domains.Pilot Observations of AI Use in Engineering Design CoursesThe first two authors have piloted use of ChatGPT to support students in our design courses. Thispilot work serves as the foundation for our RFE study. We found that the use of Generative AI inengineering courses is subject to

Conference Session

NSF Grantees Poster Session II

Collection

2025 ASEE Annual Conference & Exposition

Authors

Fatemeh Karimi Kenari, University of North Carolina at Charlotte; yasaswi bhumireddy, University of North Carolina at Charlotte; Xiaoliang Yan, Georgia Institute of Technology; Mahmoud Dinar, University of North Carolina at Charlotte; Shreyes N Melkote, Georgia Institute of Technology

Tagged Topics

NSF Grantees Poster Session

tracks learners’ progress, i.e., it adjusts future responses based onconversation history, and account for the user's existing knowledge. The Adviser alsoincorporates user-level personalization, dynamically adjusting language and the depth ofinformation to align with different user levels. Additionally, Knowledge Retrieval AugmentedGeneration (RAG) [8] integrates knowledge retrieval from manufacturing documents withLarge-Language-Model’s generation capabilities (ChatGPT in this case) to provide contextuallyrelevant responses. Manufacturing documents are divided into smaller chunks of 500 words.Each chunk is transformed into a numerical representation (embedding), capturing semanticinformation for similarity-based retrieval. Figure 1 shows the

Conference Session

NSF Grantees Poster Session I

Collection

2025 ASEE Annual Conference & Exposition

Authors

Lifford McLauchlan, Texas A&M University - Kingsville; David Hicks, Texas A&M University-Kingsville ; Mehrube Mehrubeoglu, Texas A&M University - Corpus Christi

Tagged Topics

NSF Grantees Poster Session

more systems include IoT-related control, communications andfunctionality; IoT-based projects, course materials and exercises should introduce or makestudents or end-users aware of potential cybersecurity issues, threats and concerns [10]-[14].Recent advances in AI have led to more readily available open-source machine learningframeworks and APIs, such as Gemini Developer API [15] or PyTorch [16], as well as many toolssuch as ChatGPT [17].Artificial Intelligence and CybersecuritySenior capstone course design projects should address cybersecurity issues and threats [18]. Aspart of the electrical engineering capstone course at Texas A&M University-Kingsville during theFall 2024 semester, students were tasked to perform a whole system mapping

Conference Session

NSF Grantees Poster Session II

Collection

2025 ASEE Annual Conference & Exposition

Authors

David Lattanzi, George Mason University

Tagged Topics

NSF Grantees Poster Session

–74. doi: 10.1007/978-1-4842-2256-0_3.[6] “Presentations.AI - ChatGPT for Presentations.” Accessed: Jan. 15, 2025. [Online]. Available: https://www.presentations.ai/

Conference Session

NSF Grantees Poster Session II

Collection

2025 ASEE Annual Conference & Exposition

Authors

Shana Lee McAlexander, Duke University; Catherine Brinson, Duke University; Richard J. Sheridan, Duke University; Junhong Chen, University of Chicago; Jennifer Nolan, University of Chicago

Tagged Topics

NSF Grantees Poster Session

. Option for judging competition 15 min Total 2 hours2.2 Ideation and screening. Next, teams were asked to brainstorm project ideas and articulate aresearch approach. Students are tasked with generating at least five project ideas that appliedmachine learning to materials science questions. They had the option to source ideas fromexisting literature, through ChatGPT prompts, and through curated lists of priority research areaslike The Materials Genome Initiative Challenges [10]. Teams then screened their ideas givingpriority to those which had the greatest potential impact and that they could accomplish as a teamand within the scope of a year

Conference Session

NSF Grantees Poster Session II

Collection

2025 ASEE Annual Conference & Exposition

Authors

Harpreet Auby, Tufts University; Namrata Shivagunde, University of Massachusetts Lowell; Anna Rumshisky, University of Massachusetts Lowell; Milo Koretsky, Tufts University

Tagged Topics

NSF Grantees Poster Session

, pp. 219–244, 2016, doi: 10.1002/jee.20116.[4] M. D. Koretsky, B. J. Brooks, and A. Z. Higgins, “Written justifications to multiple- choice concept questions during active learning in class,” Int. J. Sci. Educ., vol. 38, no. 11, pp. 1747–1765, Jul. 2016, doi: 10.1080/09500693.2016.1214303.[5] E. A. Alasadi and C. R. Baiz, “Generative AI in education and research: Opportunities, concerns, and solutions,” J. Chem. Educ., vol. 100, no. 8, pp. 2965–2971, Aug. 2023, doi: 10.1021/acs.jchemed.3c00323.[6] D. Baidoo-Anu and L. O. Ansah, “Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning,” J. AI, vol. 100, no. 8

Conference Session

NSF Grantees Poster Session I

Collection

2025 ASEE Annual Conference & Exposition

Authors

Tamara Powell Tate, University of California, Irvine; Beth Harnick-Shapiro, University of California, Irvine; Mark Warschauer, University of California, Irvine; Waverly Tseng, University of California, Irvine

Tagged Topics

Diversity, NSF Grantees Poster Session

California, IrvineAuthor NoteTamara P. Tate https://orcid.org/0000-0002-1753-8435Daniel Ritchie https://orcid.org/ 0000-0002-7110-8882Mark Warschauer https://orcid.org/0000-0002-6817-4416Correspondence concerning this article should be addressed to Tamara Tate, University ofCalifornia, Irvine, 3200 Education, University of California, Irvine, CA 92697. Email:tatet@uci.eduWriting and communication are crucial to engineers, taking up more than half their workinghours [1] [2]. However, too few engineers have the writing and communication skills requisitefor today’s information society [3]. Within this context, new generative artificial intelligence(AI) tools such as ChatGPT and other large language models (“AI writing tools”) pose bothopportunities and