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)

discussions in higher educationincluding its potential uses in and beyond the classroom. Initially, the focus was primarily onpreventing students from using generative AI tools, but attention is now shifting towardintegrating these tools into teaching and learning [1]. Many educators are exploring ways toincorporate generative AI into instruction [2].Students are often assumed to be tech-savvy [3]. With the widespread use of tools like ChatGPT,they may also be perceived as competent users of generative AI. However, effectively using AIfor learning requires more than just basic digital literacy, which can impact both the learningexperience and its benefit. Therefore, studying students’ interactions with AI is important, as thefindings will shape how

Conference Session

AI, Technology, and Data-Driven Learning in Biomedical Engineering

Collection

2025 ASEE Annual Conference & Exposition

Authors

Angela Lai, Tufts University; Kavon Karrobi, Boston University

Tagged Topics

Diversity

Tagged Divisions

Biomedical Engineering Division (BED)

their writing in sustained or long-term writing projects[13, 14]. Due to thismodule, the majority of students were optimistic towards using AI in future assignments forwriting. However, students who use ChatGPT to write tend to run into common pitfalls such asambiguous writing, bias reinforcement, and “hallucinations”[15]. This shift reflects the need toprovide clear guidance on appropriate AI usage in educational settings. This work highlights thegrowing recognition that fostering AI literacy is a crucial educational practice in modernclassrooms.To investigate the ways students respond to AI literacy efforts and how they may change theiruse of genAI in these situations, we introduce structured usage of AI in one lecture to increase AIliteracy

Conference Session

Poster Session-Electrical and Computer Engineering Division (ECE)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Christopher Horne, North Carolina A&T State University (CoE)

Tagged Topics

Diversity

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

withsports. These findings suggest the need for alternative analogies that better resonate with diversestudent backgrounds.For the solar charging station analogy, 72% of students matched all terms correctly, although someconfusion persisted. For example, 10% mistook ‘DC Source’ for the interface controller, and 15%confused ‘computer controller’ with the image of a cell phone. These findings suggest areas forrefining analogies, particularly in distinguishing components with similar terminology.A survey conducted at the end of the semester confirmed that students preferred real-worldanalogies over AI tools like ChatGPT, highlighting their value in establishing a strong conceptualfoundation and boosting confidence. Table 1 presents key survey results

Conference Session

Computing and Information Technology Division (CIT) Technical Session 2

Collection

2025 ASEE Annual Conference & Exposition

Authors

Prarthona Paul, University of Toronto; Chirag Variawa, University of Toronto

Tagged Divisions

Computing and Information Technology Division (CIT)

literature review encompasses academic databases, focusing on search terms such as“GenAI,” “ChatGPT,” and “Generative AI in engineering education.” Relevant papers areanalyzed to identify common themes, which are then synthesized to provide a thematic overviewof GenAI's role in engineering education. Initial findings suggest themes around ethicalconsiderations, pedagogical shifts, and the potential of GenAI to enhance student learning.Ethical concerns, such as algorithmic bias, privacy, and academic integrity, are highlighted,alongside the need for continuous upskilling of both students and educators.This study aims to offer a comprehensive understanding of GenAI's implications in engineeringeducation, serving as a valuable resource for educators

Conference Session

Computers in Education Division (COED) Track 4.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Reine Azzi, Lebanese American University

Tagged Divisions

Computers in Education Division (COED)

Learning: Insights from Liberal Education Courses in Lebanon Reine Azzi Lebanese American University A Framework for Hybrid Human-AI Learning: Insights from Liberal Education Courses in LebanonAbstractThe global debate over Generative Artificial Intelligence (GenAI) has continued in academicinstitutions, resulting in discussions on academic integrity and educational standards in a worldwhere ‘ChatGPT’ use continues to permeate educational, professional, and social contexts.While some academic institutions initially called for banning GenAI tools, many haveemphasized the need to introduce these tools within controlled

Conference Session

Computers in Education Division (COED) Track 4.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Marlee Jacobs, Utah State University; Daniel Kane, Utah State University; Rosemary Yahne, Utah State University; Wade H Goodridge, Utah State University

Tagged Divisions

Computers in Education Division (COED)

variety of complex technical topics, students face challenges in understandingand applying theoretical knowledge. AI technologies such as AI-assisted tutoring systems,performance predictions models, and generative AI tools are effective in enhancing studentinteractions with engineering curriculum improving student understanding and engagement[1][2]. By enabling real-time feedback, personalized learning experiences, and interactiveproblem-solving environments, AI tools are creating new opportunities for engineering education[3][4].The advancement of AI technology, particularly generative AI systems such as ChatGPT fosterscritical thinking and collaboration among students. In a study done by Abril students used AItools such as ChatGPT to obtain and

Conference Session

Faculty Development: Grading and Artificial Intelligence

Collection

2025 ASEE Annual Conference & Exposition

Authors

Azadeh Hassani, University of Nebraska - Lincoln; Tareq Daher, University of Nebraska - Lincoln; Guy Trainin, University of Nebraska Lincoln; Jordan M Wheeler, University of Nebraska - Lincoln

Tagged Topics

Diversity

Tagged Divisions

Faculty Development Division (FDD)

. The Chronicle of Higher Education has observed, One year after its release, ChatGPT has pushed higher education into a liminal place. Colleges are still hammering out large-scale plans and policies governing how generative AI will be dealt with in operations, research, and academic programming. But professors have been forced more immediately to adapt their classrooms to its presence. Those adaptations vary significantly, depending on whether they see the technology as a tool that can aid learning or as a threat that inhibits it [11]. Faculty perspectives and responses are particularly critical in professional programs suchas engineering, medicine, and teacher preparation, where the rapid integration

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

Engineering Ethics Division (ETHICS) Technical Session - GenAI in ethics education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sourojit Ghosh, University of Washington; Sarah Marie Coppola, University of Washington

Tagged Divisions

Engineering Ethics Division (ETHICS)

weights as a percentage of the totalfinal grade and were graded complete/incomplete based on meeting the assignment requirements. The use of GAItools to complete assignments was permitted, since the authors believe that such tools could be important equitymeasures in a reading-heavy course [16], with the requirement that students attribute their usage of such toolswherever used, such as signing assignments with “proofread by ChatGPT” if done so. Students were alsoencouraged, in line with some assignment requirements mentioned below, to experiment with various GAI assistantsin writing and completing assignments, thus being able to determine which tool could best support which action.The course was offered in a synchronous HyFlex format [8], where

Conference Session

Civil Engineering in the Age of AI

Collection

2025 ASEE Annual Conference & Exposition

Authors

Siddaiah Yarra, University of California Merced; Abbas Ghassemi, University of California, Merced

Tagged Divisions

Civil Engineering Division (CIVIL)

equitable and effective implementation. Ultimately, AI has thepotential to revolutionize higher education by making learning more efficient, inclusive, andadaptable to the needs of the learner.Keywords: Artificial Intelligence, higher education, personalized learning, adaptive teaching,student outcomes, data-driven education.IntroductionIn recent years, the integration of artificial intelligence (AI) into educational settings hascaptured significant public interest, eliciting both fascination and concern. According toEducause, while administrators and educators worry about AI undermining instructional quality,students have embraced AI tools like ChatGPT, appreciating their utility while remainingcautious about risks. This dichotomy underscores the

Conference Session

First-Year Programs Division (FPD) Technical Session 11: Shaping Engineers - Competency, Creativity, and Iteration in the First Year

Collection

2025 ASEE Annual Conference & Exposition

Authors

Mehek Kunal Vora, Tufts University; Ethan E Danahy, Tufts University

Tagged Divisions

First-Year Programs Division (FPD)

studies representative of student experiences from eachcategory that expands on the model and its implications in higher education learningenvironments. The findings emphasize that learning is not a static process; students’ interactionswith AI tools evolve over time, influenced by their initial attitudes and skills. The implications ofthis paper extend to curriculum design, pedagogical approaches, and the broader integration ofgenerative AI tools in higher education.IntroductionThe rapid advancement of generative artificial intelligence has revolutionized various industries,including education. As generative AI tools such as ChatGPT, Claude, and Gemini becomeincreasingly accessible, educators are exploring their potential to transform teaching

Conference Session

DASI Technical Session 2: Artificial Intelligence in Higher Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Xingyu You, Arcadia University; Wang Wang, Arcadia University; Zhairui Shen; Yanxia Jia, Arcadia University

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

identify trends in mental health apps since 2009.Privacy policy documents of mental health apps are also collected for analysis. ChatGPT isutilized to extract privacy-related metrics, such as the percentage of apps that reference privacyregulations like the General Data Protection Regulation (GDPR), the Health InsurancePortability and Accountability Act (HIPAA), and the Children’s Online Privacy Protection Act(COPPA). LLMs and RAG are employed to answer critical privacy and security-relatedquestions from the dataset of privacy policy documents. These questions cover multiplecategories, such as the types of user information collected, details on third-party data sharing,and whether users are given options to opt out of data collection.Results:Our

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

AI Integration in Engineering Economy Course

Collection

2025 ASEE Annual Conference & Exposition

Authors

Billy Gray, Tarleton State University; Gloria Margarita Fragoso-Diaz

Tagged Divisions

Engineering Economy Division (EED)

has been heralded as an enticing opportunity to improve education, there are concernswith the ethical use of AI in education [6]. What are the academic implications of using an LLMto assess student assignments? Students are potentially penalized or punished if they use it intheir assignments. How would the instructor’s use of an LLM be different? Kumar [6] discussesthis dilemma as to what is right and good. They list quick feedback that is of high qualityprovided at a reasonable cost and convenience as good but predicates these benefits with the AI’suse as being right or wrong.There are also questions on how student information is processed in an LLM. Though servicessuch as ChatGPT have a large number of users, if an assignment is loaded for

Conference Session

Computers in Education Division (COED) Track 6.A

Collection

2025 ASEE Annual Conference & Exposition

Authors

Abdulrahman AlRabah, University of Illinois at Urbana - Champaign; Zepei Li, University of Illinois at Urbana Champaign; Meredith Blumthal, University of Illinois at Urbana - Champaign; Sotiria Koloutsou-Vakakis, University of Illinois Urbana-Champaign; Volodymyr Kindratenko, University of Illinois Urbana-Champaign; Tomasz Kozlowski, University of Illinois Urbana-Champaign; Abdussalam Alawini, University of Illinois Urbana - Champaign

Tagged Divisions

Computers in Education Division (COED)

shown a wide range of interests in the AI-in-education domain, with themajority focusing on the applications, impacts, and potential of GenAI in education [2]. Studiesexplore the effects GenAI may have on academic practices and how it could shape the wayindividuals participate in academic activities and achieve educational outcomes. For example,Oguz et al. and Kasneci et al. examined the effectiveness of tools like ChatGPT as educationalaids in personalizing learning [14], [15]. Abedi et al. investigated the integration of LargeLanguage Models (LLMs) and chatbots in graduate engineering education, highlighting theirpotential to enhance self-paced learning, provide instant feedback, and reduce instructor workload[16]. Alasadi and Carlos, as well

Conference Session

Transformative and Just Futures in Engineering (Equity, Culture & Social Justice in Education Division ECSJ Technical Session 11)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nadia N. Kellam, Arizona State University

Tagged Topics

Diversity

Tagged Divisions

Culture & Social Justice in Education Division (EQUITY), Equity

disrupt inequities. Manywidely used AI tools, such as ChatGPT, are trained on massive proprietary datasets controlled byprivate corporations, raising questions about data security, bias, and accessibility. These concernsare particularly pressing in education, where AI’s role in student and faculty interactions must becritically examined. Without transparent and equitable governance, AI risks reinforcing existingpower imbalances rather than dismantling them.By centering only on the technical aspects of AI, we risk unintended consequences that reinforcesystemic inequities, creating outcomes that disproportionately harm marginalized groups. Someresearchers are exploring ethics, bias, and social responsibility regarding AI [5]. In this practicepaper

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

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

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

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