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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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) 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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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

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ahmed Ashraf Butt, Carnegie Mellon University; Eesha tur razia babar, University of California, Irvine; Muhsin Menekse, Purdue University, West Lafayette; Ali Alhaddad, Purdue University, West Lafayette

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Computers in Education Division (COED)

Comparative Analysis of Large Language Models and NLP Algorithms to enhance Student Reflection SummariesAbstractThe advent of state-of-the-art large language models has led to remarkable progress incondensing enormous amounts of information into concise and coherent summaries, benefitingfields like education, health, and public policy, etc. This study contributes to the current effort byinvestigating two NLP approaches’ effectiveness in summarizing students’ reflection text. Thisapproach includes Natural Language Processing (NLP) algorithms customized for summarizingstudents’ reflections and ChatGPT, a state-of-the-art large language model. To conduct the study,we used the CourseMIRROR application to collect students’ reflections from

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ibukun Samuel Osunbunmi, Pennsylvania State University; Stephanie Cutler, Pennsylvania State University; Viyon Dansu, Florida International University; Yashin Brijmohan, University of Nebraska, Lincoln; Bolaji Ruth Bamidele, Utah State University; Abasiafak Ndifreke Udosen, Purdue University, West Lafayette; Lexy Chiwete Arinze, Purdue University, West Lafayette; Adurangba Victor Oje, University of Georgia; Deborah Moyaki, University of Georgia; Melissa J Hicks, Pennsylvania State University; Bono Po-Jen Shih, Pennsylvania State University

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Boundaries of Engineering Education.AbstractGenerative artificial intelligence (GAI) has long been used across various fields; however, itsusage in engineering education has been limited. Some areas where GAI tools have beenimplemented in education include intelligent tutoring, assessment, predicting, curriculum design,and personalized student learning. The recent proliferation of CHATGPT and other GAI toolspresents limitless possibilities for transforming engineering pedagogy and assessment. At thesame time, there are challenges associated with implementation. Consequently, there is a need toconduct an empirical study to evaluate these tools' strengths, limitations, and challenges tohighlight potential opportunities for their application in

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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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 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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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) 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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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 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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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.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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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

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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) Track 4.E

Collection

2025 ASEE Annual Conference & Exposition

Authors

Michael Thomas Vaccaro Jr, University of Connecticut; Mikayla Friday, University of Connecticut; Zeynep Gonca Akdemir-Beveridge, University of Connecticut; Arash Esmaili Zaghi P.E., University of Connecticut

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personalizationdevelop custom graphical user interfaces (GUI)—such as that developed in the follow-up studyby Vaccaro et al. [22]—rather than rely on public-facing interfaces like ChatGPT as it minimizesthe potential for user error. Such a controlled GUI is also beneficial from an experimental contextwhere consistency in implementation is of critical importance. Finally, it should be noted thatsuch an environment allows for strict control over the types of information students can sharewith an LLM, thus maintaining student privacy.Integration of Personalized Learning in Engineering Education through LLMsThe integration of PL into engineering education through advanced AI and LLMs represents atransformative yet nascent field. The use of cutting-edge LLMs, such

Conference Session

Computers in Education Division (COED) Track 2.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Edward F. Gehringer, North Carolina State University at Raleigh; Madhur Dixit, North Carolina State University at Raleigh; Kavya Lalbahadur Joshi

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Computers in Education Division (COED)

of the dual-submission strategies, there is more variety to what is submitted for thesecond deadline. Sometimes students are asked to self-grade their homework [2–4]; usually theyare asked to make corrections, and some strategies ask them to undertake other activities, such asa quiz [5], group discussion [6–7], filling in missing steps in a derivation [8], or filling out a“homework wrapper” [9–10] that asks about the strategies that students used in doing thehomework and how successful they proved to be.However, the rise of Large Language Models (LLMs) like ChatGPT presents a challenge. Thesemodels can solve simple homework problems, but can they also produce credible reflections? IfLLMs can generate authentic-looking reflections, the dual

Conference Session

The Best of Computers in Education Division (COED)

Collection

2024 ASEE Annual Conference & Exposition

Authors

Gerald Tembrevilla, Mount Saint Vincent University; Mohosina Jabin Toma, University of British Columbia, Vancouver; Marina Milner-Bolotin, University of British Columbia, Vancouver

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Computers in Education Division (COED)

were recorded and uploaded on CLAS, they couldsee the difference between their original and improved lessons. It was an empowering learningexperience that gave the preservice teachers the much-needed confidence that they can figurethings out and if a lesson doesn’t go as well as they wanted the first time around, they alwayshave a second chance.Exploration of Novel Pedagogical ApproachesLearning to remove yourself from your own lessons and to reflect on them in order to teachbetter in the future is a core quality of a STEM educator in the 21st century. To be successful inthe era of fast-changing student population, rapidly evolving technologies, that haveunprecedented pedagogical potential, such as ChatGPT [42, 43], continuously

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Quintana (Quincy) Clark, Oregon State University; Chidinma Grace Okoye; Theodore Ja

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Computers in Education Division (COED)

eNotebook to include a tutoring AI feature that students could talk to along with their favoritestudy methods. eNotebook provides a general platform for nearly all of today’s study methods andmaterials students use to create and customize for efficient access and assessment. For example,we have implemented a two-way talking conversation feature called Jarvis, which is an audio-to-text / text-to-audio feature with a ChatGPT engine with AI-specific aids to improve the quality ofAI responses. We have embedded weblinks to over 50 of the most popular study apps easilyaccessible through a pull-down menu, where favorites appear at the top of the list. We haveimplemented a feature that converts handwritten notes into typed text. Images, audio, videos

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nadya Shalamova, Milwaukee School of Engineering; Olga Imas, Milwaukee School of Engineering; James Lembke; Maria Pares-Toral, Milwaukee School of Engineering; Derek David Riley, Milwaukee School of Engineering; Daniel Bergen, Milwaukee School of Engineering

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Computers in Education Division (COED)

Intelligence (AI) is no longer a subject of science fiction or a niche for specializedindustries. AI permeates everyday life, impacting how people work, communicate, and solveproblems locally and globally [1]. AI applications in higher education have grown significantlyin recent years, as evidenced by the adoption of AI-driven instructional design tools andapplications (e.g., Khan Academy's Khanmigo, ChatGPT for Education, MagicSchool), AI-enabled scientific literature search engines (e.g., Semantic Scholar, Consensus), collaborativeapplications (e.g., MS Teams), smart AI features in learning management systems (e.g., Canvas),and AI-based assistants (e.g., Grammarly, Canva).The widespread infusion of generative AI (GenAI) specifically marked a new

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Maria Elena Truyol, Universidad Andres Bello, Santiago, Chile; Monica Quezada-Espinoza, Universidad Andres Bello, Santiago, Chile; Genaro Zavala, Tecnologico de Monterrey, Monterrey, Mexico; Universidad Andres Bello, Santiago, Chile; Claudia Bascur, Universidad Andres Bello, Santiago, Chile

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. R. Adapa, and Y. E. V. P. K. Kuchi, “The Power of Generative AI: A Review of Requirements, Models, Input–Output Formats, Evaluation Metrics, and Challenges,” Future Internet, vol. 15, p. 260, 2023, doi: 10.3390/fi15080260.[15] A. K. Y. Chan and W. Hu, “Students’ voices on generative AI: perceptions, benefits, and challenges in higher education,” International Journal of Educational Technology in Higher Education, vol. 20, no. 1, p. 43, 2023, doi: 10.1186/s41239- 023-00411-8.[16] Tlili et al., “What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education,” Smart Learning Environments, vol. 10, no. 1, p. 15, 2023, doi: 10.1186/s40561-023-00237-x.[17] M. S

Conference Session

COED: AI and ML Topics

Collection

2023 ASEE Annual Conference & Exposition

Authors

Nebojsa I. Jaksic, Colorado State University, Pueblo; Bahaa Ansaf, Colorado State University, Pueblo

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Computers in Education Division (COED)

lives. Thisis especially true now, since the world is in the midst of a number of controversies dealing withbiased data sets for training of neural networks, ChatGPT unfair uses, or the Elon Musk’s call fora moratorium on AI development. Results from this research will be used as preliminary findings while planning large-scale regionalresearch activities related to AI that could be supported by NSF, Amazon Machine LearningUniversity or the Department of Education. A collaborative network consisting of localschoolteachers interested in AI and AI-active university professors will be created to furtherpromote and implement AI in the K-12 curriculum. Partnership modalities with the AI4K12organization will be investigated to improve AI literacy

Conference Session

Computers in Education Division (COED) Track 3.E

Collection

2025 ASEE Annual Conference & Exposition

Authors

Samuel B Mazzone, Marquette University; Dennis W Brylow, Marquette University

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Computers in Education Division (COED)

.[28] Kapor Center. Culturally responsive-sustaining computer science education: A framework, 2021. URL https://kaporfoundation.org/publications/.[29] OpenAI. ChatGPT, 2024. URL https://chatgpt.com.[30] Ryan L Boyd, Ashwini Ashokkumar, Sarah Seraj, and James W Pennebaker. The development and psychometric properties of LIWC-22. Technical report, University of Texas at Austin, 2022. URL https://www.liwc.app/.[31] Matthew L. Newman, James W. Pennebaker, Diane S. Berry, and Jane M. Richards. Lying Words: Predicting Deception from Linguistic Styles. Personality and Social Psychology Bulletin, 29(5):665–675, May 2003. ISSN 0146-1672, 1552-7433. doi: 10.1177/0146167203029005010. URL http://journals.sagepub.com/doi/10.1177

Conference Session

Computers in Education Division (COED) Track 6.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Mitchell Gerhardt, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University

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. Inparticular, natural language processing (NLP) a subset of gen-AI, enables computers to quicklyparse and understand text by identifying the meaningful parts of sentences [34]. Since the releaseof ChatGPT and similar chatbots, engineering education researchers have explored diverse usecases of NLP, including for analyzing student writing and assignments, examining curriculums,research data processing, student support, and assessment [35], [36], [37]. Recent work by ourresearch group [38] has also demonstrated the potential for NLP to aid qualitative thematicanalysis by expediting the codebook generation process. Importantly, these efforts takeadvantage of how NLP handles semantically and syntactically different text by identifyingpatterns between word

Conference Session

Computers in Education Division (COED) Track 3.E

Collection

2025 ASEE Annual Conference & Exposition

Authors

Oyku Eren Ozsoy, Embry-Riddle Aeronautical University - Prescott; Luis Felipe Zapata-Rivera, Embry-Riddle Aeronautical University

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published an ASEE conference paper last year on the effects of ChatGPT on student learning in programming courses. With over seven years of experience teaching Computer Science courses, she is currently a faculty member at Embry-Riddle Aeronautical University’s Department of Computer, Electrical, and Software Engineering, where she teaches computer science courses.Dr. Luis Felipe Zapata-Rivera, Embry-Riddle Aeronautical University Dr. Luis Felipe Zapata-Rivera is an Assistant Professor at Embry Riddle Aeronautical University. He earned a Ph.D. in Computer Engineering at Florida Atlantic University, in the past worked as an assistant researcher in the group of educational Technologies at Eafit University in Medellin