Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Anthony Cortez, Point Loma Nazarene University; Paul Schmelzenbach, Point Loma Nazarene University

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Diversity

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Computers in Education Division (COED)

Paper ID #48446BOARD # 78: Student Use of ChatGPT and Claude in Introductory EngineeringEducation: Insights into Metacognition and Problem-Solving PatternsDr. Anthony Cortez, Point Loma Nazarene University Anthony Cortez is currently an Assistant Professor in the department of Physics and Engineering at Point Loma Nazarene University. He received his BS in Physics from University of California San Diego (UCSD). He went on to complete his MS and Ph.D. in Mechanical Engineering from University of California Riverside (UCR). His research interests include technology as a tool in the classroom, high temperature superconductivity

Conference Session

Computers in Education Division (COED) Track 5.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Milad Rezvani Rad, University of Southern Indiana; Ronald Diersing, University of Southern Indiana; Ryan Integlia, University of Southern Indiana; Julian Ly Davis, University of Southern Indiana

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Computers in Education Division (COED)

Education, 2025 Enhancing Coding Skills and Learning Efficiency in Engineering Programming Courses by Using AI ToolsAbstractIntegrating AI tools like ChatGPT and Gemini into programming courses, such as the freshman-level Fundamentals of Engineering, provides students with invaluable support for enhancing theircoding skills. One common challenge students face is the correct use of characters and punctuation,which often leads to errors and frustration. This manuscript examines how ChatGPT can helpstudents overcome these obstacles by providing real-time feedback and guidance. In-classexamples were used to evaluate the accuracy of code troubleshooting, and student surveys assessedthe impact on motivation, engagement, and coding

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Hannah Oluwatosin Abedoh, Morgan State University; Blessing Isoyiza ADEIKA, Morgan State University; Pelumi Olaitan Abiodun, Morgan State University; Oludare Adegbola Owolabi P.E., Morgan State University; Abiola Olayinka Ajala, Morgan State University; OLUWATOYOSI OYEWANDE, Morgan State University

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Diversity

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Computers in Education Division (COED)

Master’s in Advanced Computing and a Bachelor’s in Computer Science, Abiola has expertise in data science, cybersecurity, networking, business analysis, and system administration. A member of ASEE,IEEE who is passionate about STEM education to introduce K1-12 students to computing/ engineering skills and digital literacy.OLUWATOYOSI OYEWANDE, Morgan State University ©American Society for Engineering Education, 2025Perception of the Impact of Artificial Intelligence on EducationAbstractThis work-in-progress paper explores the perceptions of students and educators regarding theimpact of Artificial Intelligence (AI) on education, specifically before and after the release ofOpenAI’s ChatGPT. Using a mixed

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Michaela Harper, Utah State University; Cassandra J McCall, Utah State University; Daniel Kane, Utah State University; Wade H Goodridge, Utah State University; Linda Davis Ahlstrom, Utah State University; Oenardi Lawanto, Utah State University

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Computers in Education Division (COED)

, respectively. He also hasextensive experience in working collaboratively with several universities in Asia, the World Bank Institute,and USAID to design and conduct workshops promoting active-learning and life-long learning that issustainable and scalable. Dr. Lawanto’s research interests include cognition, learning, and instruction,and online learning. ©American Society for Engineering Education, 2025 WIP: Voices of the Future: Student Insights on AI's Role in Shaping Learning, Integrity, and Norms in Higher EducationAbstractThis work-in-progress paper explores university students’ perspectives on Generative ArtificialIntelligence (GAI) tools, such as ChatGPT, an increasingly prominent topic in the

Conference Session

Computers in Education Division (COED) Track 4.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Arezou Harraf; Yuetong Lin, Embry-Riddle Aeronautical University - Worldwide; A. Mehran Shahhosseini, Indiana State University

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Computers in Education Division (COED)

Worldwide in 2016 as an associate professor in the School of Engineering (formerly Department of Engineering and Technology).Dr. A. Mehran Shahhosseini, Indiana State University A. Mehran Shahhosseini is a Professor in the Department of Applied Engineering and Technology Management at Indiana State University. He has published over 65 articles in different journals and conferences ©American Society for Engineering Education, 2025 Leveraging AI-Based Tool to Guide Students on Literature Review: A Case StudyAbstractThis study aimed to compare the effectiveness of traditional literature review methods withAI-based search tools (ChatGPT 03Mini and Perplexity Pro Paid

Conference Session

Computers in Education Division (COED) Track 2.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Melina O'Dell, University of Michigan; Andrew DeOrio, University of Michigan

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Computers in Education Division (COED)

course forum to use as prompts. Anexpert team of instructors evaluated each bot’s response for accuracy (hallucination) andhelpfulness. We used ChatGPT Pro as a baseline “generalist” chatbot.Overall, the specialist bots hallucinated less and were considered more helpful for studentquestions than the generalist bot. The best specialist bot was correct 80% of the time and helpful70% of the time. The generalist bot was correct 70% of the time and helpful only 26% of thetime. There were minimal performance differences between the specialist bots with varyingscopes.Our experience can guide educators using generative AI. First, a custom RAG chatbot is morehelpful than a general-purpose chatbot. Second, a single chatbot with a course-wide scope has

Conference Session

Computers in Education Division (COED) Track 2.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Tammy Mackenzie, The Aula Fellowship; Lisa D. McNair, Virginia Tech; Rubaina Khan, University of Toronto; Animesh Paul, University of Georgia; Sreyoshi Bhaduri, Private Corporation

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Diversity

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Computers in Education Division (COED)

designs in mechanical engineering [65], making ethical choices during prototypingin time-sensitive situations such as hackathons [66], and learning disciplinary skills needed fordesign projects through personalized learning [67]. Lastly, a handful of papers explore howGenAI tools can give timely, relevant, and epistemic feedback during design. One exampleis the use of ChatGPT to analyze progress reports, instrumental to team collaborations, byrecommending readability improvements and clarifying complex ideas [68].3.3 PositionsOur review found 33 position papers revealing diverse viewpoints on its integration, eth-ical considerations, and potential applications of GenAI in EE. Specifically, these papersare where authors argue their stance on or

Conference Session

Computers in Education Division (COED) Track 2.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Venkata Alekhya Kusam, University of Michigan - Dearborn; Zheng Song, University of Michigan - Dearborn; Khalid Kattan, University of Michigan - Dearborn; Bruce R Maxim, University of Michigan - Dearborn

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Computers in Education Division (COED)

, zhesong, bmaxim, kkattan}@umich.edu Department of Computer and Information Science, University of Michigan-Dearborn, USAAbstractThis paper presents an investigation into the use of Generative AI (GenAI), specifically ChatGPT,to automate quiz generation in higher education by conducting a case study in a graduateArtificial Intelligence (AI) course. The study aims to compare the quality and relevance ofAI-generated quizzes with manually created ones, addressing a critical question in computerscience education: Can Generative AI effectively support educators in creating assessments thatalign with course learning objectives?We conducted the study in a graduate-level AI course, which involved 47 students, one instructorand one

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Johannes Kubasch, University of Wuppertal; Dominik May, University of Wuppertal; Doha Meslem, Bergische Universität Wuppertal

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Computers in Education Division (COED)

Meslem, Bergische Universit¨at Wuppertal ©American Society for Engineering Education, 2025 WIP: AI in Online Laboratory Teaching - A Systematic Literature ReviewIntroductionThe presence of ChatGPT has recently, and in a short period of time, become increasinglyprevalent in the day-to-day life. Education, being a part and a reflection of the day-to-day life,has therefore also been affected by this change. The fast spread of this technology within thiscontext has however come with its challenges. These include the lack of an adequateunderstanding of it, of how to use it, and how to integrate it in an efficient way in the dailylife (Gill & Kaur, 2023). Many students

Conference Session

Computers in Education Division (COED) Track 6.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Shana Shaw, Texas A&M University; L. Taylor Starr, Texas A&M University; laila badran, Texas A&M University

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Diversity

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Computers in Education Division (COED)

[4]. In2024, more research is available for AI in education and industry, including as a virtual assistantusing AI as a prompting tool [14], and as a development bot to enhance software design [18].With the popularity of ChatGPT increasing, from one million users in the first week during thelaunch in 2022, to more than 200 million weekly users in late 2024 [16], the usage of ChatGPTin college engineering courses is expected to follow a significant increase soon. Using AI in the engineering classroom has been seen to offer both advantages anddisadvantages. Students saw an increased confidence in decision-making, critical thinking andproblem-solving skills using AI tools, which may help develop professional skills [14]; however,the

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Christopher Allen Calhoun, University of Cincinnati; David Reeping, University of Cincinnati; Siqing Wei, University of Cincinnati; Aarohi Shah, University of Cincinnati

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Computers in Education Division (COED)

focus of the literature. Within the first monthsof its launch, it was found that ChatGPT could pass law school exams, though it only managed aC+ [20]. This is just one example of the deluge of papers describing how large language modelscan perform reasonably well on traditional examinations (e.g., [21], [22], [23], [24], [25]). Thesemodels are trained using large and diverse sets of writing and employ statistical procedures topredict a response to a statement or question, which can lead to surprising coherence and theappearance of analytical reasoning.In STEM fields, where communication is less in written short responses and more often acombination of diagrams and equations, generative AI tools have seen uneven success in problem-solving. For

Conference Session

Computers in Education Division (COED) Track 4.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Reine Azzi, Lebanese American University

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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

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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

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

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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

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

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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

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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

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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

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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

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Diversity

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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

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

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Diversity

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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

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

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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

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

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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

Computers in Education Division (COED) Track 4.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Madison Melton, University of North Carolina at Charlotte; Mohsen M Dorodchi, University of North Carolina at Charlotte

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Computers in Education Division (COED)

, images, and music [7],using deep learning models like GANs and transformers to generate original data by learningpatterns from training datasets. Unlike traditional machine learning, which primarily analyzes orclassifies existing data [8], GenAI models, such as OpenAI’s GPT, leverage large languagemodels (LLMs) trained on vast text datasets [9, 10]. Beyond LLMs, models like GANs, VAEs,and diffusion models further expand GenAI’s capabilities, with applications spanning NLP [11],art creation [12], and game design [13]. The release of ChatGPT quickly raised concerns aboutacademic integrity and student overreliance, potentially hindering learning due to its accessibility[14, 15]. However, these concerns have also driven interest in leveraging GenAI

Conference Session

Computers in Education Division (COED) Track 2.A

Collection

2025 ASEE Annual Conference & Exposition

Authors

Animesh Paul, University of Georgia; VINCENT OLUWASETO FAKIYESI, University of Georgia; Md Ulfat Tahsin, The Ohio State University; Lexy Chiwete Arinze, Purdue University at West Lafayette (COE); Sreyoshi Bhaduri, Private Entity

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Computers in Education Division (COED)

deconstructed the question using the Population, Concept, and Context (PCC)framework, a widely used approach in systematic literature reviews [7]. The PCC guidelines for this review arePopulation – engineering educators and students; Concept – utilization of generative models (e.g., GenerativeAI, ChatGPT, GPT); Context – formal and informal engineering education settings.3.2. Identifying Relevant StudiesThe search strategy is structured into concept lines, following the approach outlined in [8] for scopingreviews, which is designed to identify and include articles, conference papers, and gray literature relevant tothe research question. For the scope of our project, we define this as an "Aspect": An aspect is an element ordimension of the research

Conference Session

Computers in Education Division (COED) Track 2.B

Collection

2025 ASEE Annual Conference & Exposition

Authors

Stephany Coffman-Wolph, Ohio Northern University; Abigail Clark, Ohio Northern University; J. Blake Hylton, Ohio Northern University; Bryan Alan Lutz, Ohio Northern University; Gabriel Mott, Ohio Northern University

Tagged Divisions

Computers in Education Division (COED)

limitations. First, AI tools, such as ChatGPT andCopilot are relatively new, and constantly evolving in their abilities. Secondly, the sampledstudent work represented a small portion of available data and thus is not representative of thewhole set. Finally, while every effort was made to ensure that the evaluators were consistent withthe application of the rubric, it is simply not realistic to expect people with varying expertise tobe completely consistent. While these limitations were important to acknowledge, they do notlimit the importance of this work. We see potential not only for optimizing writing support butalso for fostering student-involved negotiations on how AI can aid the writing process.MethodsContextThis study occurred at a small

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Peter Jamieson, Miami University; Ricardo Ferreira, Universidade Federal de Viçosa; José Nacif, Universidade Federal de Viçosa

Tagged Divisions

Computers in Education Division (COED)

, personalized online learning experiences. We evaluate the effectiveness of this methodthrough a series of case studies and provide guidelines for instructors to leverage these technologiesin their courses.1 IntroductionLarge Language Models (LLMs) and their emerging skills provide educators with new capabilitiesto improve our teaching and save time. LLMs like ChatGPT have emerged as powerful tools thatcan assist in creating educational content and interactive learning experiences [1].For digital system design and computer architecture, traditional education often relies on expen-sive hardware, specialized software, and physical laboratory spaces. These requirements can limitaccess to hands-on learning experiences, particularly for students in

Conference Session

Computers in Education Division (COED) Track 2.A

Collection

2025 ASEE Annual Conference & Exposition

Authors

Griffin Pitts, University of Florida; Viktoria Medvedeva Marcus, University of Florida; Sanaz Motamedi, University of Florida

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Diversity

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Computers in Education Division (COED)

ChatGPT [1], Google’s Gemini [2],and Microsoft’s Copilot [3] have gained widespread student adoption due to their free access andease of use. This expansion has occurred amid varying acceptance [4–6] and trust [7] in digitallearning technologies across student populations through the COVID-19 pandemic and into thepresent day. Approximately one-third (35.4%) of students reported regular usage of ChatGPT,while 47% expressed concern about AI’s impact in education [8]. Additionally, 60% reported thattheir instructors or schools had not yet provided guidelines for ethical or responsible AI tool use [8].As students increasingly use available online AI assistants, researchers have concurrently devel-oped specialized educational AI tools designed

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Daniel Kane, Utah State University; Wade H Goodridge, Utah State University; Linda Davis Ahlstrom, Utah State University; Oenardi Lawanto, Utah State University; Michaela Harper, Utah State University; Cassandra J McCall, Utah State University

Tagged Topics

Diversity

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Computers in Education Division (COED)

publications have been recognized by leading engineering education research journalsat both national and international levels. Dr. McCall has led several workshops promoting the inclusionof people with disabilities and other minoritized groups in STEM. She holds B.S. and M.S. degrees incivil engineering with a structural engineering emphasis. ©American Society for Engineering Education, 2025 WIP: Understanding Patterns of Generative AI Use: A Study of Student Learning Across University CollegesIntroductionDue to the relatively recent introduction of AI to academia, facilitated by the development andrelease of popular generative AI systems such as ChatGPT, few studies have examined theeffects of AI use on

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Linda Davis Ahlstrom, Utah State University; Oenardi Lawanto, Utah State University; Cassandra J McCall, Utah State University; Michaela Harper, Utah State University; Wade H Goodridge, Utah State University; Daniel Kane, Utah State University

Tagged Divisions

Computers in Education Division (COED)

, Use of AI tools and Peer Collaboration on AI Assisted Learning: Perceptions of the University students.,” Digit. Educ. Rev., no. 45, pp. 43–49, Jun. 2024, doi: 10.1344/der.2024.45.43-49.[5] M. Edali, A. Milad, H. Saad, Z. Sahem, T. Alajaili, and A. Elkamel, “ChatGPT and Artificial Intelligence (AI) Massive Transformation of Trainers’ Education Sector Revolutionizing How Students Learn,” in Proceedings of the International Conference on Industrial Engineering and Operations Management, Dubai, UAE: IEOM Society International, Feb. 2024. doi: 10.46254/AN14.20240340.[6] C. Spreitzer, O. Straser, S. Zehetmeier, and K. Maaß, Mathematical Modelling Abilities of Artificial Intelligence Tools: The Case of ChatGPT., vol. 14