Conference Session

ECE-Applications of AI and ChatGPT in Engineering Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Guoping Wang, Purdue University Fort Wayne

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Diversity

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Electrical and Computer Engineering Division (ECE)

secured multiple grants for innovative projects. A senior member of IEEE, he actively contributes to the field through publications and conference presentations. ©American Society for Engineering Education, 2025 Case Studies of ChatGPT for Embedded Systems TeachingAbstractThe rise of AI technology, particularly Generative AI, has significantly transformed the landscapeof higher education. Generative AI, such as ChatGPT, has been extensively studied in fields likeComputer Science to assess its effectiveness in enhancing learning. However, its impact on morespecialized areas, such as bare-metal embedded systems, remains underexplored. Bare-metalembedded systems, which include hardware (e.g

Conference Session

ECE-Applications of AI and ChatGPT in Engineering Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ren Butler, Carnegie Mellon University; D. Matthew Boyer, Clemson University; Andrew Begel, Carnegie Mellon University; Rick Kubina, Pennsylvania State University; Somayeh Asadi, University of Virginia; Taniya Mishra; JiWoong Jang, Carnegie Mellon University

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Diversity

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Electrical and Computer Engineering Division (ECE)

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

AI Integration in Engineering Economy Course

Collection

2025 ASEE Annual Conference & Exposition

Authors

Hamed Samandari, University of Massachusetts Dartmouth

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Diversity

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Engineering Economy Division (EED)

Engineering Economy CoursesAuthor: Hamed SamandariAffiliation: University of Massachusetts DartmouthAbstractThe rapid development of Artificial Intelligence (AI) presents both opportunities and challengesfor engineering education. As AI tools like ChatGPT become more accessible, studentsincreasingly use them to complete assignments, prompting educators to evaluate whether tointegrate AI as a learning aid or restrict its usage. This study explores the potential of AI toenhance student learning outcomes in an engineering economics course. Specifically, we utilizeChatGPT, which provides detailed explanations of economic theories, guidance onmicroeconomic principles, example problems, and real-world economic

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

DASI Technical Session 2: Artificial Intelligence in Higher Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Lauren Singelmann, Minnesota State University, Mankato; Jack Elliott, Minnesota State University, Mankato; Yuezhou Wang, Minnesota State University, Mankato; Jacob John Swanson, Minnesota State University, Mankato

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Diversity

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Data Science and Artificial Intelligence (DSAI) Constituent Committee

Capabilities to Perform Specific TasksIntroductionGenerative AI (GAI) tools like ChatGPT and Copilot can quickly prepare polished, fiveparagraph essays and clever limericks about any given topic, but can they multiply seventwo-digit numbers? Or answer a question from the Fundamentals of Engineering exam? Or tellyou what the image in a “connect-the-dots” puzzle is? GAI tools are designed to be able toproduce human-like language responses to given prompts, but performance varies depending onthe nature of each task. To further complicate the evaluation of GAI performance, each tool (e.g.ChatGPT, Copilot, Gemini) has its own process for generating responses, and these processescan evolve rapidly – with success varying across tools

Conference Session

Technological and Engineering Literacy/Philosophy of Engineering Division (TELPhE) Technical Session 2

Collection

2025 ASEE Annual Conference & Exposition

Authors

Adeel Khalid, Kennesaw State University; Sanjeev Adhikari, Kennesaw State University

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Diversity

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Technological and Engineering Literacy/Philosophy of Engineering Division (TELPhE)

Engineering Education, 2025 Educators’ Perspectives on the use of Generative AI Tools in Teaching and Educational Research in EngineeringAbstractSince the release of ChatGPT by OpenAI in November 2022, the integration of generative AI(genAI) into teaching and education has gained significant attention and experienced rapid growthwithin university engineering programs. This paper investigates the application of genAI inengineering education and research, focusing on the potential benefits and challenges of itsadoption. Specifically, the study: A) Analyzes how educators and students perceive and utilizegenAI and ChatGPT in engineering education; B) Explores the advantages, challenges, andlimitations associated with these technologies

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

ME Division Technical Session 2 - Harnessing AI and Machine Learning to Transform ME Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Harrison Zimmerman Brown, Worcester Polytechnic Institute; Reza Ebadi, Worcester Polytechnic Institute

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Diversity

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Mechanical Engineering Division (MECH)

ThermodynamicsAbstractGenerative artificial intelligence (GenAI) has become ubiquitous. Convincing languagecomplemented by constant modifications and upgrades have made GenAI models, such asOpenAI’s ChatGPT, an appealing tool to address complex problems. According to a survey byIntelligent.com nearly a third of college students in AY 2022-2023 used ChatGPT for schoolworkand 77.4% of them were likely to recommend using it to study to another student. Despite theirappeal, these models have proven flawed in answering technical prompts. Their convincinglanguage may entice the user to trust the responses without verifying them. For example, theauthors failed to retrieve accurate thermodynamics properties of some common substances fromthree publicly available models (OpenAI’s

Conference Session

Generative AI and Its Role in Industrial Engineering

Collection

2025 ASEE Annual Conference & Exposition

Authors

THOMAS AMING'A OMWANDO, Simpson University; Adel Alhalawani, Rose-Hulman Institute of Technology; Ashutosh Khandha, University of Delaware; Bhavana Kotla, The Ohio State University

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Diversity

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Industrial Engineering Division (IED)

Biomechanics, Medical Devices, Clinical Imaging and Bioinstrumentation.Dr. Bhavana Kotla, The Ohio State University Visiting Assistant Professor, Department of Engineering Education, College of Engineering, The Ohio State University ©American Society for Engineering Education, 2025 Assessing the Impact of Generative AI in Developing and Using Grading Rubrics for Engineering CoursesAbstractEngineering education is rapidly integrating generative artificial-intelligence (GenAI) tools thatpromise faster, more consistent assessment—yet their reliability in discipline-specific contextsremains uncertain. This mixed-methods study compared ChatGPT-4, Claude 3.5, and PerplexityAI across

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

Generative AI and Its Role in Industrial Engineering

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nadiye O. Erdil, University of New Haven

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Diversity

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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

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Diversity

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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)

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Diversity

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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

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

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Diversity

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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

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

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Diversity

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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

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Diversity

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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

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 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

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

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Diversity

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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

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

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Diversity

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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

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

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Diversity

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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

Conference Session

Biomedical Engineering Division (BED) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

Xianglong Wang, University of California, Davis; Tiffany Marie Chan, University of California, Davis; Angelika Aldea Tamura, University of California, Davis

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Diversity

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Biomedical Engineering Division (BED)

], rapidimprovement in the performance of these products, as reflected by one faculty’s experience ofPerplexity AI scoring 80% on their multiple choice-based engineering quiz, accentuated the needfor BME educators and students to improve AI literacy and cultivate responsible use of AI.ML algorithms are computer programs that improve their performance with more experience(data) [8]. Therefore, problems in the data used to train ML algorithms, such as demographicbiases, can be reflected in the performance of ML algorithms. In a BME context, GPT-4, whichpowers ChatGPT and Perplexity AI, showed strong ethnic biases when assigning medicalconditions such as HIV/AIDS [9], while GPT-4 and Gemini (also powers AI-enabled notebook,NotebookLM) showed negative perception

Conference Session

First-Year Programs Division (FPD) Technical Session 4: Fostering Belonging - Identity, Self-Efficacy, and Retention

Collection

2025 ASEE Annual Conference & Exposition

Authors

Brian Patrick O'Connell, Northeastern University; Kathryn Schulte Grahame, Northeastern University; Richard Whalen, Northeastern University; Constantine Mukasa, Northeastern University; Susan F Freeman, Northeastern University

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Diversity

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First-Year Programs Division (FPD)

using ChatGPT for high-level analysis. Datasets weremanually formatted to ensure consistent wrangling by the AI, using standardized key phrases andstructured formatting to enhance the AI's ability to parse and interpret the information accurately. Thisstudy implemented a simplistic segmentation, considering each sentence as a single statement, toimprove reliability and repeatability. This process was systematically repeated and refined by utilizingsubsets of the data with established qualities until preprocessing consistently achieved accurate parsingfollowing emerging best practices [23].Throughout the analysis, refinements were made to prompts and categorizations, ensuring alignmentwith the nuances of each reflection. Reanalysis occurred 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

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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

Engineering Ethics Division (ETHICS) Technical Session - Ethics education methodologies and interventions

Collection

2025 ASEE Annual Conference & Exposition

Authors

Robyn Mae Paul, University of Calgary

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Diversity

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Engineering Ethics Division (ETHICS)

ethics in engineering education. Science and Engineering Ethics, 10(2), 343–351. https://doi.org/10.1007/s11948-004-0030-8Paul, R. M., Hugo, R., & Falls, L. C. (2015). International expectations of engineering graduate attributes. 11th International CDIO Conference.Piers, C. (2024, February 7). Even ChatGPT Says ChatGPT Is Racially Biased. Scientific American. https://www.scientificamerican.com/article/even-chatgpt-says-chatgpt-is- racially-biased/Riley, D. (2012). Aiding and ABETing: The Bankruptcy of Outcomes-based Education as a Change Strategy. 2012 ASEE Annual Conference & Exposition Proceedings, 25.141.1- 25.141.13. https://doi.org/10.18260/1-2--20901Ross, S. R. (2019). Supporting your

Conference Session

Computing and Information Technology Division (CIT) Technical Session 4

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jason M. Keith, Iowa State University of Science and Technology; Amin Amirlatifi, Mississippi State University; Sudip Mittal, Mississippi State University; Subash Neupane, Mississippi State University; HIMANSHU TRIPATHI, Mississippi State University

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Diversity

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Computing and Information Technology Division (CIT)

Education, 2025 Barkplug 2.0 and Beyond: a Chatbot for Assisting Students in High DFW CoursesAbstractHigher education continues to respond to the challenges and opportunities presented by artificialintelligence (AI) and large language models (LLM) such as ChatGPT. In our prior work weintroduced a chatbot that used AI and LLM to recruit prospective students, assist current studentswith academic advising (course selection, changing majors) and student affairs (directingstudents to university resources regarding the campus community, housing and dining, studentorganizations, mental health and more). Towards the promotion of student success initiatives wereport in this work our formulation of course specific teaching

Conference Session

WIP Poster Session: Emerging Research and Practices in Pre-College Engineering Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Syeda Fizza Ali, Texas A&M University; Ayaan Sunil Rege, The Hill School; Susanna Angela Ponniah, The Hill School; Hoda Ehsan, The Hill School ; Saira Anwar, Texas A&M University

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Diversity

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Pre-College Engineering Education Division (PCEE)

developing systemscapable of performing tasks that usually require human intelligence, including learning,reasoning, and decision-making [21]. Generative AI (Gen-AI) is a subset of AI thatspecializes in creating human-like content, including text, images, and audio [22]. With AI'srecent innovations, many have explored its educational applications. Many educatorscurrently utilize AI tools to increase efficiency within the classroom [1]. Two examples ofGen AI tools include 1) ChatGPT, a generative AI chatbot, and 2) Grammarly, an AI-powered writing assistant. Both tools have proven valuable educational assistants [2, 3].GenAI can help educators with tasks like creating assessments and streamliningadministrative tasks and lessons [23, 24]. In the field

Conference Session

ELOS Technical Session 3: Advancing Engineering Competencies: From Labs to Writing

Collection

2025 ASEE Annual Conference & Exposition

Authors

Dave Kim, Washington State University-Vancouver; Charles Riley P.E., Oregon Institute of Technology; Sean St. Clair P.E., Oregon Institute of Technology; Olusola Adesope, Washington State University

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Experimentation and Laboratory-Oriented Studies Division (DELOS)

community of practice focusing on engineering lab writing education. Thispaper presents the content, delivery, and results of the professional development workshop onengineering lab writing.2. Workshop Content and DeliveryThe workshop was designed for the participants to conduct the following in a small groupsetting: 1) develop engineering lab report assignments; 2) improve engineering lab reportassessment; 3) guide students in navigating writing with generative AI (ChatGPT-4); and 4) trainlab teaching assistants or lab report graders. Participants accessed the guides (available atengineeringlabwriting.org) to design and develop sample labs, discuss issues related to labwriting and how to deliver lab writing expectations, and provide feedback to