Conference Session

Biomedical Engineering Division (BED) Postcard Session (Best of WIPs)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nathan Hyungsok Choe, The George Washington University; Chanyee Hong; Hyeyeon Lim

Tagged Topics

Diversity

Tagged Divisions

Biomedical Engineering Division (BED)

al.emphasized that utility value and self-efficacy are essential in shaping the learning outcomes ofengineering students, highlighting the importance of integrating practical applications into thecurriculum to enhance students' perceived utility value [3]. In the context of using large languagemodel (LLM) like ChatGPT in engineering education, the utility value can significantlyinfluence how students perceive and utilize these tools. Recent studies have explored the impactof LLM on students' perception of utility value in using AI tools. For instance, Rosenzweig et alexamined the effectiveness of utility value interventions in online math courses and found thatsuch interventions significantly increased students' perceived utility value and

Conference Session

WiP: Gen AI, Mixed Reality, and Simulations

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jonathan Verrett, University of British Columbia, Vancouver

Tagged Divisions

Chemical Engineering Division (ChED)

perceptions and usage of generative AI in second- year chemical engineering design exercisesIntroductionGenerative AI (Gen. AI) systems have recently become widely and easily accessible followingthe launch of systems such as ChatGPT in late 2022. One topic of interest is how students areusing these tools and the educational impacts of their use [1]. Researchers have sought tounderstand student use and perception of Gen. AI through a variety of means including surveysand case studies [2], [3], [4], [5]. Weber et al. surveyed 760 respondents at an R1 universityincluding students and faculty on their perception of Large Language Models (LLMs) [2].Students believed that LLMs would significantly impact their ability to quickly

Conference Session

Computers in Education Division (COED) Track 2.A

Collection

2025 ASEE Annual Conference & Exposition

Authors

Trini Sofia Balart, Texas A&M University; Sidney Katherine Uy Tesy, Texas A&M University; Kristi J. Shryock, Texas A&M University

Tagged Divisions

Computers in Education Division (COED)

increasingly essential. As industries and workplaces continue to adopt advancedtechnologies, particularly artificial intelligence (AI), the demand for professionals equipped withthese skills has intensified [1]. Generative AI (GenAI) tools, which are transforming varioussectors, offer the potential to revolutionize educational methodologies by fostering these criticalskills among students. These tools, such as ChatGPT, can provide adaptive learning experiences,real-time feedback, and interactive problem-solving opportunities [2], [3]. While the integration of AI into educational environments promises to create morepersonalized, engaging, and effective learning experiences, its potential impact on durable skilldevelopment remains underexplored

Conference Session

Computers in Education Division (COED) Track 5.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sita Vaibhavi Gunturi, Pennsylvania State University, Harrisburg, The Capital College; Jeremy Joseph Blum, Pennsylvania State University, Harrisburg, The Capital College; Tyler S. Love, University of Maryland Eastern Shore

Tagged Divisions

Computers in Education Division (COED)

. Gunturi1, Jeremy J. Blum1, Tyler S. Love2 1 Pennsylvania State University, Harrisburg 2 University of Maryland Eastern Shore AbstractGenerative AI, powered by Large Language Models (LLMs), has the potential to automateaspects of software engineering. This study implemented a monostrand conversion mixed-methods approach to examine how computer science students utilize generative AI toolsduring a competitive programming competition across multiple campuses. Participants usedtools such as ChatGPT, GitHub Copilot, and Claude and submitted transcripts documentingtheir interactions for analysis. Drawing

Conference Session

Track 4: Technical Session 5: Impact of Generative AI Technologies on Blind and Visually Impaired Students: A Case Study

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Lance Leon Allen White, Texas A&M University; Sara Amani, Texas A&M University; Trini Sofia Balart, Texas A&M University; Amanda Kate Lacy; Gene Sung-Ho Kim, Stanford University; Gibin Raju, Texas A&M University; Karan Watson P.E., Texas A&M University; Kristi J. Shryock, Texas A&M University

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

of Blind and Visually Impaired Students and the Impact of Generative AI: A NarrativeAbstractThe advent of Generative AI (GenAI) in our society has taken root so deeply that simple Googlesearches invoke a GenAI response attempting to synthesize a simplified summary for a user.Incidentally, these GenAI systems like ChatGPT from OpenAI, LLaMA from Meta, Geminifrom Google, and Copilot from Microsoft are all largely text-based large language modelsproviding an increased level of access to people who use screen reading technology to interactwith personal computing systems. This study investigates the impact of GenAI on accessibilityfor blind and visually impaired students, focusing on the experiences of two computing

Conference Session

Computers in Education Division (COED) Track 3.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Robert J Kerestes, University of Pittsburgh; Jack Thomas Carnovale, University of Pittsburgh; Paulo Radatz

Tagged Divisions

Computers in Education Division (COED)

asked, ”I understand the roleof programming (i.e., Python) in Power Systems Analysis,” while Q2 asked, ”I feel confident inmy ability to use Python for solving basic engineering problems.” Q4 focused on the use ofgenerative AI tools with the question, ”To what extent did you use generative AI tools (e.g.,ChatGPT, GitHub Copilot) to assist you in learning or completing Python assignments?” TheLikert scale ranged from ”Strongly Disagree” (1) to ”Strongly Agree” (5) for Q1 and Q2, andfrom ”Never” (1) to ”Always” (5) for Q4.Two open-ended questions (Q3 and Q5) provided opportunities for students to share qualitativefeedback. Q3 asked, ”Is there anything you would like the instructor to know, or do you have anyrecommendations for improving the

Collection

2025 Northeast Section Conference

Authors

Tariq A. Alshugran; Lina H. Kloub, University of Connecticut

banpersonalized learning and the development of dynamic edu- on ChatGPT by the Italian Data Protection Authority in 2023cational materials. However, the use of GenAI often involvesprocessing sensitive student data, raising concerns about pri- raised concerns about the lack of transparency in AI datavacy and regulatory compliance. This paper examines these collection practices [3]. Institutions must navigate a complexchallenges, highlighting key risks such as data breaches and regulatory landscape, ensuring that GenAI applications alignunauthorized data sharing. A comprehensive solution is proposed with existing legal frameworks such as the GDPR in Europeinvolving privacy-preserving technologies and robust data gov

Conference Session

Computers in Education Division (COED) Poster Session (Track 1.A)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Katie Vu, University of Michigan; Avery Mitchell Maddox, University of Michigan; Caleb William Tonon, University of Michigan; Guli Zhu, University of Michigan; Tyler Wang, Stony Brook University; Rafael Mendes Opperman, University of Michigan; Qiuyi Ding, University of Michigan; Zifei Bai, University of Michigan; zhanhao liu, University of Michigan; Ziyi Wang, University of Michigan; Arvind Rao, University of Michigan; Daniel Yoon, University of Michigan

Tagged Divisions

Computers in Education Division (COED)

engines where the user must search through resources related totheir query. Also like a personal tutor, their utility is dependent upon their ability to draw fromtheir knowledge base to give accurate responses. OpenAI promotes the breadth of knowledge intheir latest model, GPT-4 [2], underpinning their general-purpose chat application ChatGPT [3],which is capable of scoring a 5, the best score possible, on advanced placement exams for arthistory, biology, macroeconomics and more [2]. This high level of performance has led to amassive increase in use by students across academic disciplines, with mixed acceptance at theuniversity and department level. How to ensure that students gain experience with these tools,which are likely to be essential

Conference Session

Computers in Education Division (COED) Track 2.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ryan Tsang, University of California, Davis; SYDNEY Y WOOD, University of California, Davis

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

-dictive power on performance outcomes. Finally, we call for continued empirical research on theefficacy of LLM-based technologies in STEM education and propose future research directions inexploring their impact on teaching and learning.1 IntroductionThe introduction of OpenAI’s ChatGPT in November 2022 [1] triggered an unprecedented surgeof interest in applications of artificial intelligence (AI) based on Large Language Models (LLMs)and their underlying transformer architecture.In particular, LLMs appear to be exceptional in applications that involve human interaction, infor-mation retrieval, and summation, making them an attractive prospect for improving the effective-ness and accessibility of education in the digital age [2, 3, 4]. However

Conference Session

Computers in Education Division (COED) Track 3.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Eric L Brown, Tennessee Technological University; Douglas A. Talbert, Tennessee Technological University; Jesse Roberts, Tennessee Technological University

Tagged Divisions

Computers in Education Division (COED)

standards management [2].The advent of advanced machine learning mechanisms—evolving from early neural networks tomodern transformer architectures—has ushered in a new renaissance in artificial intelligence andits practical applications. The rapid development of large language models (LLMs), capable ofprocessing substantial volumes of unstructured text and generating structured outputs, nowempowers framework mapping projects at a quality level that was inconceivable less than adecade ago. SMEs now have access to AI tools that facilitate comprehensive reviews of localguidance documents and alignment exercises with strategic frameworks. In practice, instructionaldesign teams have used tools like ChatGPT and Copilot to accelerate the development of

Conference Session

Tech Session 3: Emerging Trends in Engineering Education: AI, Clean Energy, and Curriculum Design

Collection

2025 ASEE Annual Conference & Exposition

Authors

Dayna Mandalyn Cline, United States Military Academy; David Zgonc, United States Military Academy at West Point; William B Vass, United States Military Academy; Michael A. Butkus P.E., United States Military Academy; Matthew Baideme, United States Military Academy; Brett Ryan Krueger, United States Military Academy

Tagged Divisions

Environmental Engineering & Sustainability Division (ENVIRON)

theprofessional engineer licensing process and is geared towards undergraduates completingaccredited programs [5]. The FE Environmental Exam consists of 15 sections coveringsupporting skills, including calculus, fluid mechanics, and thermodynamics, as well asenvironmental-specific topics such as biological wastewater processes, atmospheric modeling,and solid waste management.Generative artificial intelligence (genAI) may change current curriculum development processesin a way other technological advances have not. Publicly accessible, native language processinggenAI tools have expanded greatly since the release of OpenAI’s ChatGPT in November 2022.The U.S. Government Accountability Office estimated for the U.S. Congress in June 2024 thatmore than 100

Conference Session

Construction Engineering Division: AI & Automation

Collection

2025 ASEE Annual Conference & Exposition

Authors

Souhail Elhouar, Bradley University; Phuong Nguyen, South Dakota State University

Tagged Divisions

Construction Engineering Division (CONST)

Integrating Artificial Intelligence (AI) in Construction CurriculaAbstractArtificial Intelligence (AI) applications, such as machine learning, deep learning, naturallanguage processing, and computer vision, have been increasingly used in the constructionengineering and management (CEM) area for the past decades to enhance productivity andproject performance. Recently, the rise of large language models, such as ChatGPT, has evenenlarged the number of AI-powered approaches that academic researchers and industryprofessionals can utilize to solve CEM problems. The wide range of AI applications challengespractitioners regarding the effective selections and efficient implementations in the CEMeducation and training programs. The

Conference Session

Computers in Education Division (COED) Track 2.A

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jason M. Keith, Iowa State University of Science and Technology; Jason Coleman, Kansas State University; Lis Pankl, Mississippi State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

a growth in academic integrityfilings since the advent of ChatGPT. In fact, [2] points to a Stanford University survey where1/6th of students said they had used ChatGPT on assignments or exams. This article [2] alsopoints towards the issues of hallucinations, where AI focuses on generating text that sounds goodbut may not be scientifically accurate. However, [1] also points to potential efficiencies andutility of AI in higher education, such as teaching ethical use of AI, growth of tutoring/teachingassistants and for operational efficiencies. Auon [3] discussed the impact of AI on the humanexperience in physical (personalized medicine/drug delivery and disease identification),cognitive (increased workplace productivity, focused effort on

Collection

2025 ASEE North Central Section (NCS) Annual Conference

Authors

Aniruddha Maiti; Samuel Adewumi; TEMESGEN ALEMAYEHU TIKURE; Zichun Wang; Niladri Sengupta; Anastasiia Sukhanova, Marshall Community & Technical College; Ananya Jana, Marshall University

Tagged Topics

Diversity

outputs of bothmodels.For alignment, fuzzy matching techniques were used. These techniques matched sentences be-tween GPT-4o and DeepSeek R1, even when there were minor differences in phrasing. This ap-proach improved the accuracy of mapping and ensured consistency in the processed data. Theresult was a clean and reliable dataset for analysis.5.2. Overall Categorization CoverageWe analyzed the total number of sentences processed and the extent to which GPT-4o and DeepSeekR1 provided category assignments. Table 1 summarizes the categorization coverage across all an-alyzed sentences. ChatGPT DeepSeek Total Sentences 1823 1823

Conference Session

DSAI Technical Session 7: Natural Language Processing and LLM Applications

Collection

2025 ASEE Annual Conference & Exposition

Authors

Suman Saha, Pennsylvania State University; Fatemeh Rahbari, The Pennsylvania State University; Farhan Sadique, Kansas State University; Sri Krishna Chaitanya Velamakanni, Pennsylvania State University; Mahfuza Farooque, Pennsylvania State University; William J. Rothwell, Penn State University

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

→ 𝑞" (𝑝 implies 𝑞) might be illustrated using everyday examples like "If it israining, then we take an umbrella." Adopting microlearning as a structured approach couldsignificantly enhance early computer science education, enabling students to solidifyfundamental principles from the start of their studies.Creating microlearning materials can be time-consuming for educators [42]. However,Generative AI like ChatGPT [25] can streamline this process by generating personalizedsummaries, flashcards, and quizzes tailored to specific subjects. Generative AI has become aprevalent tool for content creation across various sectors today. Daniel examined the impact ofgenerative AI on creating learning videos with synthetic virtual instructors, finding

Conference Session

Computers in Education Division (COED) Track 2.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Runu Proma Das, University of Georgia; Tathyana Moratti, University of Georgia; Shari Gasper, University of Georgia; Beshoy Morkos, University of Georgia

Tagged Divisions

Computers in Education Division (COED)

expert for students in theirlearning process.This research aims to redefine the creation of engineering problems by utilizing generative AI,particularly ChatGPT. The study assesses student performance by conducting a mixed-methodapproach that combines both quantitative and qualitative analyses. By adopting a novel approachfor creating engineering problems beyond traditional textbook problems, we explore a way toimprove student learning outcomes and enhance the essence of engineering education.This research specifically addresses a major research question illustrated in Figure 1: Figure 1: Assessment of Research Question 2. Background 2.1. Pedagogy of Engineering ProblemSeveral recent studies focused on reshaping

Conference Session

Construction Engineering Division: AI & Automation

Collection

2025 ASEE Annual Conference & Exposition

Authors

Anh D. Chau P.E., Florida Gulf Coast University; Cade M. Cratsley, Florida Gulf Coast University; Long Duy Nguyen P.E., Florida Gulf Coast University

Tagged Divisions

Construction Engineering Division (CONST)

relativelynew research area, AI chatbot studies are rapidly becoming more significant across a variety offields, including CEM. This growing body of research underscores the potential for chatbots toaddress discipline-specific challenges, such as improving efficiency, cost estimation, and projectmanagement in the construction industry.While numerous studies have explored AI chatbots in CEM, most focus on using existinggeneral-purpose AI tools rather than teaching students to develop custom solutions. In academicsettings, general-purpose AI tools like ChatGPT, Claude 3, and Gemini have generatedsignificant discussion and applications. For instance, Campbell [8] demonstrates their use inautomating VBA code creation for Excel in steel design courses

Conference Session

Computers in Education Division (COED) Track 3.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Randy McDonald, Texas A&M University; Salvatore Enrico Paolo Indiogine; Nasiha Lachaud, Texas A&M University; Wei Lu, Texas A&M University; Mohammad Affan Khokhar

Tagged Divisions

Computers in Education Division (COED)

was used only in a few instances, but given the focus of the course, in mostcases, it did not meet the expectations of the professor.Background and Related LiteratureThe impact of ChatGPT has led to a significant increase in awareness and experimentation withgenerative AI tools among educators since its release in November 2022 [1]. As generativeartificial intelligence technologies have emerged onto the landscape of higher education, therehas been a healthy research interest in how students are using AI to promote their success inclasses, how faculty might integrate AI into their teaching, and how staff employees, in general,might use AI to work more efficiently [2]. The use of generative AI in all these areas isconsiderably nascent and needs

Conference Session

ERM Technical Session: Improving Assessment in Engineering Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

David Coulter Jangraw, University of Vermont; Anneliese Marie Shoudt; Courtney D Giles, University of Vermont

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods Division (ERM)

hypotheses for future research.A preliminary qualitative analysis of Ticket Home student exit surveys and TA Ticket Homesummaries used ChatGPT to identify common themes. The surveys were first manuallyanonymized by removing names, then entered into ChatGPT with the prompt “Please summarizethese responses to the question: . List the most common themes and how manyresponses mentioned each of them.” While a similar approach has been used successfully forthematic analysis before [20], our approach involves different data and prompts; it shouldtherefore be considered preliminary and subject to a more extensive validation. To assess theapproximate accuracy of this approach, a human rater manually identified the four most commoncodes identified by ChatGPT

Conference Session

Engineering Libraries Division (ELD) Technical Session 3

Collection

2025 ASEE Annual Conference & Exposition

Authors

Kristina Bloch, University of Louisville; Campbell R Bego, University of Louisville

Tagged Divisions

Engineering Libraries Division (ELD)

an ongoing collaboration between anEngineering Fundamentals professor and the Engineering Librarian at a largesuburban university in the Southeast. In this study, a purposive sample of sixstudents in an Introduction to Engineering course participated in semi-structuredinterviews regarding the student experience of course- integrated GenAI research intheir class.Researchers utilized Charmaz’s constructivist grounded theory to analyze the data[13]. ChatGPT-3.5 was not utilized in the analysis or in writing this article. Thisstudy was approved by the Institutional Review Board (Reference Number794713) at the University of LouisvilleParticipantsAll study participants were enrolled in the Introduction to Engineering course atthe University of

Conference Session

Curriculum Development and Pedagogical Innovations

Collection

2025 ASEE Annual Conference & Exposition

Authors

William H Guilford, University of Virginia

Tagged Divisions

Biomedical Engineering Division (BED)

according topredefined rubric criteria, which aligned with levels of DPK. Each student's pre and postresponses were evaluated for the presence or absence of rubric categories. ChatGPT providedconsistency in applying the rubric across the dataset and sped the analysis. Further, for eachrubric criterion, ChatGPT highlighted specific examples and patterns of alignment ormisalignment with rubric, allowing for manual validation of the results.Statistical comparisons were performed using SPSS. Scores were ordinal and not normallydistributed. Therefore, a Wilcoxon Signed Ranks test was used for comparison of pre-post paireddata. A Mann-Whitney test was used to compare beginning of semester scores between the twosemesters.ResultsBefore the curriculum

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

John M Mativo, University of Georgia; Ramana Pidaparti, University of Georgia; Jarron Gravesande, Providence Chrisitian Academy

Tagged Topics

Professional Papers

aimed tointegrate artificial intelligence (AI) into the K-12 curriculum by exploring computer vision andAI tools to augment science and technology education. ImageSTEAM specifically introducedvisual media as a critical technology to engage middle school students, particularly in 7th-gradescience, through AI-related topics, digital 3D modeling, and coding.As a result of the workshop, the “Create your 3D Eye” lesson module was developed using AItools such as Pixlr X, TinkerCAD, and ChatGPT prompts. This module helps studentsunderstand the structure and function of the eye and apply their knowledge through interactivedigital tools. The summative assessment for the students is to design and build their 3D model ofan eye from scratch using

Conference Session

First-Year Programs Division (FPD) Work-in-Progress 3: Integration of Math, Computing, and AI in First-Year Courses

Collection

2025 ASEE Annual Conference & Exposition

Authors

Bishweshwor Rimal, University of Texas at Austin; Sneha Ballabh, University of Texas at Austin; Nina Kamath Telang, University of Texas at Austin

Tagged Divisions

First-Year Programs Division (FPD)

articlesummarizing the impact of ChatGPT on a variety of engineering assessments, the authorsconcluded that introductory-level programming assessments can be very accurately solved byChatGPT, and that instructors must add complex features to their assessments to deter studentcheating [7].However, there is no published research on the usage of generative AI to offer customizedquestion banks and explanations of course concepts based only on course materials, for anintroductory computing course, within the learning management system, thereby providing apersonalized learning experience tailored to each student’s needs. The primary innovation in ourstudy lies in ensuring that the generated questions remain entirely focused on the course content,strictly avoiding

Conference Session

Innovative Learning Tools and Visualizations in ECE Curriculum

Collection

2025 ASEE Annual Conference & Exposition

Authors

Raiyan Ishmam, University of Toronto; Salma Emara, University of Toronto; Hamid S Timorabadi P.Eng., University of Toronto

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

used search en-gines—primarily Google—or increasingly, LLM-based services like ChatGPT. While Googleprovides reliable but fragmented information, ChatGPT can produce more coherent, user-friendlysummaries but may occasionally “hallucinate” or fabricate content. Users relying on ChatGPTmust manually verify any suggested sources.Despite these limitations, ChatGPT still offers a valuable starting point for discovering potentiallyrelevant books, especially for non-expert users. We leveraged ChatGPT-4o to generate candidateground truth data, then applied rigorous human verification to mitigate misinformation. Our pro-cedure was as follows: • We issued arbitrary queries (main query plus one or more topics) to ChatGPT, asking it to identify

Conference Session

Focus on the First Year

Collection

2025 ASEE Annual Conference & Exposition

Authors

Elin Jensen, Lawrence Technological University

Tagged Divisions

Civil Engineering Division (CIVIL)

the qualitative analysis was to determine if a thematic comparison of the studentteam deliverables show the progression of the project evolution from initial concept ideas toconcrete project solution. The three deliverables were: • Preliminary Project Proposal (Text-Heavy) • Impact Statement (Text-Heavy) • Final Presentation (Image-Heavy)Thematic analysis of the project deliverables from one (Team 4) of the seven teams wasconducted using OpenAI's ChatGPT, an AI language model, to identify and compare emergingthemes across the project stages [12]. After uploading the deliverables (student names wereremoved) ChatGPT extracted the text from the documents. ChatGPT was prompted to comparethe evolution of ideas over the project duration. In

Collection

2025 Northeast Section Conference

Authors

Mohammad Rafiq Muqri; Simon Obeid; Gusteau Duclos, DeVry University

opportunities structures in vast datasets as in [1] and continuouslyacross multiple domains, including education, it also raises improving through fine-tuning and prompting.ethical concerns around issues such as copyright,misinformation, and bias. This paper explores the potential of Generative AI operates in three phases:generative AI to revolutionize teaching and learning, with a focuson its impact on student outcomes. Through an examination of • Training, to create a foundation model that can serveselective platforms such as ChatGPT, Character AI, Gemini, and as the basis of multiple gen AI applications.Deep Seek, this paper aims to introduce students to thefundamentals of building AI-powered applications

Conference Session

ENT-1: Innovative Approaches to Student Engagement and Belonging in Engineering

Collection

2025 ASEE Annual Conference & Exposition

Authors

Andrea T Kwaczala, Western New England University; Andrea Davis, Western New England University; Heidi Ellis, Western New England University

Tagged Topics

Diversity

Tagged Divisions

Entrepreneurship & Engineering Innovation Division (ENT)

-confidence in their individualskills in oral communication, specifically related to presentations, but these results requireadditional research to confirm these findings.Using AI to Assess Student Outcomes: Co-Pilot and ChatGPT were both used to evaluate pitchtranscripts using the Grading Rubric. The results of AI-evaluations were compared to the facultyevaluations using the same grading rubric. This was limited to transcripts of the pitch as anyonline video-based platform for video analysis was by paid subscription only. In identifyingavailable AI tools, some interesting subscription-based options we discovered. These tools focusspecifically on video analysis of body language and pitch performance, including uSpeek(Sarang, 2023) and Bodha (Cadet

Conference Session

Faculty Development Division (FDD) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

Yen-Lin Han, Seattle University; Wan D. Bae, Seattle University; Julie Homchick Crowe, Seattle University; Matthew John Rellihan, Seattle University

Tagged Divisions

Faculty Development Division (FDD)

, health and wellness, and human biology. She received her PhD from the University of Washington.Matthew John Rellihan, Seattle University ©American Society for Engineering Education, 2025 Lessons Learned- Facilitating conversations around Generative AI and its Impact on Society among faculty from different disciplines in a Jesuit UniversityBackgroundSince the arrival of ChatGPT, generative AI has continued to shake up higher educationinstitutions. Many institutions have scrambled to identify strategies and set policies for teachingand learning for faculty and students. One important fact to pay attention to is that generative AIimpacts all disciplines—not only those with

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

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