Conference Session

Harnessing AI and Collaborative Platforms to Personalize and Innovate K-12 STEM Curriculum

Collection

2025 ASEE Annual Conference & Exposition

Authors

Michael Thomas Vaccaro Jr, University of Connecticut; Mikayla Friday, University of Connecticut; Arash Esmaili Zaghi P.E., University of Connecticut

Tagged Divisions

Pre-College Engineering Education Division (PCEE)

Research Traineeship(TRANSCEND) under Grant No. 2152202 at the time this research was conducted. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe author(s) and do not necessarily reflect the views of the National Science Foundation.During the preparation of this paper, the authors used OpenAI’s ChatGPT models as a writingassistant to check grammar and to enhance the clarity of the written text. These models wereused with extreme oversight and care. The authors have reviewed and edited the output and takefull responsibility for the content of this publication.Ethics StatementThe study regarding human subjects was reviewed and approved by the University ofConnecticut’s Storrs-campus Institutional

Conference Session

ME Division 8: Measuring What Matters: Concept Inventories, FE Exam, and Learning Skills

Collection

2025 ASEE Annual Conference & Exposition

Authors

Anahita Ayasoufi, Auburn University; Amanda Sterling, Auburn University; Jeffrey C. Suhling, Auburn University; Daniel Kevin Harris; Kyle D Schulze, Auburn University; Ashu Sharma, Auburn University

Tagged Topics

Diversity

Tagged Divisions

Mechanical Engineering Division (MECH)

in freshman information processing and the rise in Using academic resources both fall outside of the 2 sigma bands starting the Fall of 2022. Since ChatGPT was introduced in November 2022, this decrease is likely not due to AI usage. The COVID-19 pandemic effect, on the other hand, matches the timing. The national trends mentioned in sections IV.A.1 and 2 above support this theory. However, whether this is the true cause needs further research. Further, the rise in Using academic resources may be happening in compensation for the dropping Information Processing skill. Again, to establish if this is the case, will need further research. 2

Conference Session

First-Year Programs Division (FPD) Technical Session 6: Learning by Doing - Contextual and Community-Based Engineering

Collection

2025 ASEE Annual Conference & Exposition

Authors

David Gray, Virginia Polytechnic Institute and State University; Juan David Ortega Álvarez, Virginia Polytechnic Institute and State University

Tagged Divisions

First-Year Programs Division (FPD)

see several opportunities to refine the assignment based on the lessonslearned. Currently, the scenarios were developed by a single faculty member in the EngineeringEducation department through the use of generative AI (ChatGPT Model 4.0). To enhancedisciplinary representation, we will collaborate with colleagues from degree-granting majors todevelop scenarios that better highlight underrepresented fields, such as biological systems,mining, and materials science. Faculty from these disciplines are well-positioned to identifyemerging challenges and opportunities that reflect the nuances of their fields while remainingrelevant to first-year students.Additionally, we plan to guide students more explicitly toward resources that clarify both

Conference Session

Leveraging AI and Computational Tools for Enhanced Learning

Collection

2025 ASEE Annual Conference & Exposition

Authors

Carlo Bato Galicia, Cebu Institute of Technology - University

Tagged Divisions

Chemical Engineering Division (ChED)

, this wasnot explored in the study, but in future iterations, it will be measured via pre-test.Some questions were adapted from textbook exercises, while other problems werewritten for the project. For those that were adapted from textbooks, some sets weregenerated using the original problem statements, while in others, the problem set wasmodified using AI tools, which included ChatGPT and Google Gemini. Other AI chatbottools were not used during the project.AI could be utilized to change the language, style, and context of problem sets bychanging the content and style of the problems. This is particularly useful in theprocess of keeping assessments “fresh” or adaptable. The instructor of the coursedoes need to evaluate if the modified problem

Conference Session

DSAI Technical Session 7: Natural Language Processing and LLM Applications

Collection

2025 ASEE Annual Conference & Exposition

Authors

Alexis Frias, University of California Merced; Shrivaikunth Krishnakumar, San Jose State University; Ayush Pandey, University of California Merced

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

159 of the 183 Python projects in total,which were divided between training and testing. One student in the dataset developed a longproject that did not fit the maximum prompt size and we had to remove this project’s grading fromthe finetuning. This is an area of improvement for future designs of autograders.2.7 Off the shelf LLMWe conducted experiments using two popular off-the-shelf LLMs: Claude and ChatGPT. We usedsystem messages to enforce a consistent structure across the models, ensuring uniform outputformatting that can be easily parsed into the gradebook Table 7. Table 6: Feedback Comparison between Human and Models system content user content assistant content ### Instruction

Conference Session

Track 5: Technical Session 6: Advancing Accessibility: Leveraging Technology to Empower Deaf and Hard of Hearing Students in STEM Higher Education

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Sunday David Ubur, Virginia Polytechnic Institute and State University; Sarah Over, Virginia Tech; Denis Gracanin, Virginia Polytechnic Institute and State University; C. Cozette Comer, Virginia Polytechnic Institute and State University

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

precision in controlled environments, focusing on improving model accuracy.However, the emphasis on machine learning also reflects a broader gap in addressing otheraccessibility challenges, particularly in contexts where communication is not the only barrier.Large Language Models (LLMs) such as ChatGPT and chat bots are other technology that couldbe explored to enhance communication accessibility for the hearing impaired [56], however thelack of tested application of LLMs to address accessibility for the hearing impaired may be, atleast in part, explained by how recently LLMs became available to the public.Limited Focus on Classroom AccessibilityDespite the wide range of technology explored, there is a noticeable dearth of studies aimedspecifically

Conference Session

Minorities in Engineering Division(MIND) Technical Session 11

Collection

2025 ASEE Annual Conference & Exposition

Authors

Haya Alshayji, Pennsylvania State University; Deja Workman, Pennsylvania State University; Swapnika Dulam, Pennsylvania State University; Lauren A Griggs, The Pennsylvania State University; Dixon Zor, Pennsylvania State University; Christopher L Dancy, The Pennsylvania State University, University Park

Tagged Topics

Diversity

Tagged Divisions

Minorities in Engineering Division(MIND)

://doi.org/10.1145/3375627.3375868[7] J. Borenstein and A. Howard, “Emerging challenges in AI and the need for AI ethicseducation,” AI and Ethics, 2021[8] J. Borenstein and A. Howard, “Emerging challenges in AI and the need for AI ethicseducation,” AI Ethics, vol. 1, pp. 61–65, 2021. doi: 10.1007/s43681-020-00002-7. [Online].Available: https://doi.org/10.1007/s43681-020-00002-7[9] S. Wang, T. Xu, H. Li, C. Zhang, J. Liang, J. Tang, P. S. Yu, and Q. Wen, “Large LanguageModels for Education: A Survey and Outlook,” arXiv preprint, vol. abs/2403.18105, 2024.[Online]. Available: https://arxiv.org/abs/2403.18105[10] E. Kasneci et al., “ChatGPT for Good? On Opportunities and Challenges of Large LanguageModels for Education.” Center for Open Science, 2023

Conference Session

Multidisciplinary Engineering Division (MULTI) Technical Session 8

Collection

2025 ASEE Annual Conference & Exposition

Authors

Liuying Gong, School of Public Affairs, Zhejiang University; Jingyuan Chen; Min Ye, Zhejiang University

Tagged Divisions

Multidisciplinary Engineering Division (MULTI)

implication: Taking Zhejiang University as an Example,”(in Chinese), Open Educ. Res., vol. 30, no. 1, pp. 89–98, 2024, doi:10.13966/j.cnki.kfjyyj.2024.01.010.[7] A. M. Al-Abdullatif and M. A. Alsubaie, “ChatGPT in Learning: Assessing Students’ UseIntentions through the Lens of Perceived Value and the Influence of AI Literacy,” Behav. Sci.,vol. 14, no. 9, Sep. 2024, doi: 10.3390/bs14090845.[8] A. Alamaeki, C. Nyberg, A. Kimberley, and A. O. Salonen, “Artificial intelligence literacyin sustainable development: A learning experiment in higher education,” Front. Educ., vol. 9,Mar. 2024, doi: 10.3389/feduc.2024.1343406.[9] F. J. Cantú-Ortiz, N. Galeano Sánchez, L. Garrido, H. Terashima-Marin, and R. F. Brena,“An artificial intelligence educational

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

Tagged Topics

Diversity

Tagged Divisions

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

ERM Technical Session: Developing Engineering Competencies III

Collection

2025 ASEE Annual Conference & Exposition

Authors

Katherine Drinkwater, Virginia Polytechnic Institute and State University; Olivia Ryan, Virginia Polytechnic Institute and State University; Susan Sajadi, Virginia Polytechnic Institute and State University; Mark Vincent Huerta, Virginia Polytechnic Institute and State University

Tagged Divisions

Educational Research and Methods Division (ERM)

pose. Subcode Representative Quote1. Perceptions of how AI-generated Getting the feedback from ChatGPT will likely help me give better feedback in the future since I canfeedback helps with providing and/or use it as a guide as how to phrase my feedback to others. (151)receiving feedback2. Managing emotions in engaging in I know I could be stubborn and feel that I am right, but that is simply not being an engineer. I need tofeedback processes know that collaboration is key to success in this class and all facets of engineering…(64

Conference Session

DSAI Technical Session 3: Integrating Data Science in Curriculum Design

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ashraf Badir, Florida Gulf Coast University; Ahmed S. Elshall, Florida Gulf Coast University

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

, and more time allotted towards the special topics (Machine learning and GeeMap API). I would shorten the panda lesson and python programming lesson by one lesson each to hit another subject in there. It moved well. I would say extend class hours in general for subjects like Matplotlib, Xarray, Numpy, and Pandas so we could cover more topics in the future. I feel that a lesson just on AI coding assistance is not entirely necessary, especially because much of the utility of having an integrated AI API key in the jupyter notebook can be replicate by simplying accessing ChatGPT, Copilot, or any other LLM online. Additionally, it may be worth reducing the lessons on Matplotlib and instead teaching it alongside other lessons. None. I wish we were

Conference Session

Minorities in Engineering Division(MIND) Technical Session 1

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nia A. Keith, Purdue University College of Engineering; Jacqueline E McDermott, Purdue University at West Lafayette (COE)

Tagged Topics

Diversity

Tagged Divisions

Minorities in Engineering Division(MIND)

includedstudent experiences, feedback on program sessions, and suggestions for improvement. Next,feedback was separated by years (2017-2019, 2020-2023, and 2024) based on the different EarlyDiscovery program formats and input into Open AI software (ChatGPT), with the command ofidentifying the most frequently used words. These frequently used words were inserted into aword cloud generator website (https://www.freewordcloudgenerator.com/) to visually representthese terms. The final word cloud result provides a visual of the student feedback and keytakeaways from their experiences.Results and DiscussionThe three different Early Discovery program formats have their own goals, frameworks,benefits, and limitations (RQ1)To determine which Early Discovery

Conference Session

Computing and Information Technology Division (CIT) Technical Session 7

Collection

2025 ASEE Annual Conference & Exposition

Authors

Yu-Zheng Lin, The University of Arizona; Karan Patel, The University of Arizona; Ahmed H Alhamadah, The University of Arizona; Sujan Ghimire, The University of Arizona; Jesus Pacheco; Banafsheh Saber Latibari, The University of Arizona; Soheil Salehi, The University of Arizona; Pratik Satam, University of Arizona

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

revolution workforce needs,” in 2023 IEEE Integrated STEM Education Conference (ISEC). IEEE, 2023, pp. 271–276.[27] J. White, Q. Fu, S. Hays, M. Sandborn, C. Olea, H. Gilbert, A. Elnashar, J. Spencer-Smith, and D. C. Schmidt, “A prompt pattern catalog to enhance prompt engineering with chatgpt,” arXiv preprint arXiv:2302.11382, 2023.[28] P. Lewis, E. Perez, A. Piktus, F. Petroni, V. Karpukhin, N. Goyal, H. K¨uttler, M. Lewis, W.-t. Yih, T. Rockt¨aschel et al., “Retrieval-augmented generation for knowledge-intensive nlp tasks,” Advances in Neural Information Processing Systems, vol. 33, pp. 9459–9474, 2020.[29] L. Shani, A. Rosenberg, A. Cassel, O. Lang, D. Calandriello, A. Zipori, H. Noga, O. Keller, B. Piot, I. Szpektor et

Conference Session

GSD 1: From Recruitment to Retention

Collection

2025 ASEE Annual Conference & Exposition

Authors

Samuel Sola Akosile, Morgan State University; Michael Oluwafemi Ige, Morgan State University; Tolulope Abiri, Morgan State University; Pelumi Olaitan Abiodun, Morgan State University; Oludare Adegbola Owolabi P.E., Morgan State University

Tagged Topics

Diversity

Tagged Divisions

Graduate Studies Division (GSD)

ideas in diverse manners, reviewing related literature in the area ofstudy, discussing assignments with lecturers, and using editors and academic social media likeResearchGate, Google Scholar, and YouTube, to mention a few enhanced academic writings. Inaddition, using technology and artificial intelligence AI tools (ChatGPT, Grammarly, and so on)helps overcome these writing challenges.The absence or lack of a proper understanding of academic writing may cause respondents to applytheir preexisting assumptions, opinions, and methods that have provided them with confidence andreliability when faced with academic challenges like writing a research paper [49]. According toCasanave and Hubbard, [50], faculty members failed to provide students with

Conference Session

ME Division 10: Innovation in the Sophomore Year

Collection

2025 ASEE Annual Conference & Exposition

Authors

Marino Nader, University of Central Florida; Ricardo Zaurin, University of Central Florida; Michelle Taub, University of Central Florida; Sierra Outerbridge, University of Central Florida; Harrison N Oonge, University of Central Florida; Hyoung Jin Cho, University of Central Florida

Tagged Divisions

Mechanical Engineering Division (MECH)

students’learning gains in STEM education as in Arora et al.1 and Van den Broeck et al.2. However, a rapidchange in online landscape accelerated by COVID-19 pandemic has brought up serious academicmisconduct issues, as evidenced by the students’ frequent utilization of websites and AI tools suchChegg3, Quizlet4, and ChatGPT 4o5. The matter was compounded during COVID-19 when theisolated environments contributed to students’ lack of motivation to study and learn, Y. Terada6.The academic misbehaviors are further described by P. Charlesworth et al.7, M. M. Lanier8 as wellas by A. Fask et al.9. In effect, this creates grade inflation and possibly jeopardizes the academicintegrity of the institution’s program that could in turn dampen students’ motivation.One

Conference Session

Empowering Pre-College Students through AI and Computer Science: Standards, Self-Efficacy, and Social Impact

Collection

2025 ASEE Annual Conference & Exposition

Authors

Shana Lee McAlexander, Duke University; George Delagrammatikas, Duke University

Tagged Topics

Diversity

Tagged Divisions

Pre-College Engineering Education Division (PCEE)

. Students generated a wall ofideas, with over three hundred ideas written on brightly colored sticky notes. For the initialideation round, students were asked to think of societal problems without the assistance of theirphones or computers. After they seemed exhausted thinking on their own, with 5-10 ideas each,they were next directed to use available resources to gather ideas. Facilitators suggested thatstudents review UN Sustainable Development Goals and explore global grand challenge lists.In the third ideation phase, students were guided to use generative AI applications and to recordand share their iteration process in prompting. The decision to support the exploration of productideas with ChatGPT was not made lightly. Aligned with

Conference Session

First-Year Programs Division (FPD) Work-in-Progress 5: Academic Support, Retention, and Success Strategies

Collection

2025 ASEE Annual Conference & Exposition

Authors

Hiba Assi, University of Detroit Mercy; E. Prasad Venugopal, University of Detroit Mercy; Shuvra Das, University of Detroit Mercy; Dawn Archey, University of Detroit Mercy; Mark Andrew Steffka, University of Detroit Mercy; Darrell K. Kleinke P.E., University of Detroit Mercy

Tagged Topics

Diversity

Tagged Divisions

First-Year Programs Division (FPD)

and biases that seepinto the design of products and their effect on different populations and society at large.Increasing the representation of historically marginalized populations in the engineering pipelineand into the workforce is crucial in creating a more equitable future for all people.VI: AcknowledgementsThis project is being supported through an internal grant from the university president’s office tofoster innovation. ChatGPT was used for editing earlier drafts of this paper. Also, we wish toacknowledge several colleagues Drs. Kirstie Plantenberg, Michael Santora and Kenneth Lamb ofUniversity of Detroit Mercy, who contributed in various ways to the project discussed here.References[1] “Transforming Undergraduate Engineering

Conference Session

Architectural Engineering Division (ARCHE) Technical Session 2

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ignacio Guerra P., Universidad San Francisco de Quito USFQ; MiguelAndres Andres Guerra P.E., Universidad San Francisco de Quito USFQ

Tagged Divisions

Architectural Engineering Division (ARCHE)

. Toscano, M. A. Guerra, S. Durán-Ballén, y B. M. Valarezo, «WIP- Development of Critical Thinking in AEC Students Aided by Artificial Intelligence», en 2024 IEEE Frontiers in Education Conference (FIE), IEEE, 2024, pp. 1-6. Accedido: 30 de abril de 2025. [En línea]. Disponible en: https://ieeexplore.ieee.org/abstract/document/10893092/[16] D. E. Abril, M. A. Guerra, y S. D. Ballen, «ChatGPT to Support Critical Thinking in Construction-Management Students», en 2024 ASEE Annual Conference & Exposition, 2024. Accedido: 29 de abril de 2025. [En línea]. Disponible en: https://peer.asee.org/48459.pdf[17] J. Acosta, J. Ubidia, M. A. Guerra, V. Guerra, y C. Gallardo, «Work in Progress: Collaborative Environments in

Conference Session

Two-Year College Division (TYCD) Technical Session 4: Curriculum and Assessment

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ali Zilouchian, Florida Atlantic University; Nancy Romance, Florida Atlantic University

Tagged Divisions

Two-Year College Division (TYCD)

efficiencies, as wellas expanding the types of jobs and sectors available in the workforce. However, as with anytechnological revolution, there will also be challenges, particularly regarding the ethical use ofAI, job displacement, and ensuring that the benefits of AI are accessible to all. By understandingand preparing for these shifts, society can maximize the potential of AI for positivetransformation in the coming decades. II. AI: PAST, PRESENT & FUTURE Artificial Intelligence (AI) has various definitions. To many, AI refers to machines that think,understand language, and solve problems, and gaining popularity with ChatGPT. Scientifically,AI is a computer system capable of tasks associated with intelligence. John McCarthy and Marvin

Conference Session

ENT-5: Pathways for Developing Entrepreneurial Skills Across Educational Levels

Collection

2025 ASEE Annual Conference & Exposition

Authors

John Reap, Quinnipiac University

Tagged Divisions

Entrepreneurship & Engineering Innovation Division (ENT)

outputs from recently developed AI tools is a quite newchallenge that research communities are just now forming to address [23]. An investigation ofAI accuracy found that ChatGPT 3.5 proved, “…generally good at writing concepttopics…”[24]. One reasonably classifies a literature survey task as a concept topic, suggestingthe potential for accurate results from AI. However, this work uses Gemini 1.5 Flash, notChatGPT 3.5. Verhulsdonck and coauthors introduce a subjective means of evaluating theaccuracy of AI generated content independent of the particular tool [24]. Their HEAT method,an acronym formed from Human experience, Expertise, Accuracy and Trust, attempts tosubjectively gage AI output credibility. In this work’s contents, the H and E terms

Conference Session

Lightning Talk - Empowering Students and Strengthening Community Relationships

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jose Manuel Fuentes-Cid, Universidad Andres Bello, Santiago, Chile; Maria Elena Truyol, Universidad Andres Bello, Santiago, Chile

Tagged Divisions

Community Engagement Division (COMMENG)

; Computer ScienceEngineering conducts a workshop on using ChatGPT to optimize household tasks and searchfor job opportunities; Automation and Robotics Engineering provides a workshop on homeautomation, teaching the implementation of smart technologies; finally Social Work leads awomen’s empowerment workshop, addressing strategies to enhance self-confidence anddecision-making skills.The project’s evolution has been guided by a continuous improvement approach based onsatisfaction surveys administered to program participants and the government counterpart.This feedback has allowed for adjustments and enhancements to each workshop's content,ensuring that the training effectively addresses the real needs of the women beneficiaries.This growth has

Conference Session

Engineering Libraries Division (ELD) Technical Session 3

Collection

2025 ASEE Annual Conference & Exposition

Authors

Cari Kaurloto, University of Southern California; Jane Lah, University of Southern California; Alvaro Quezada, Caltech

Tagged Divisions

Engineering Libraries Division (ELD)

promising an opportunity to participate in the raffle for a gift card. As oursurvey and recruited participants were limited to our institution and targeted populations, itshould be noted that our findings may not be applicable or generalizable to other institutions. An area for future consideration would be to include more survey questions related tostudents’ understanding and use of artificial intelligence (AI). While the survey did have onequestion related to their use of ChatGPT specifically, any future studies of students’ informationliteracy skills should include the use of AI in information retrieval and citation. This wouldhighlight a gap in understanding how students engage with AI and the ethical and practicalchallenges they might

Conference Session

Cooperative and Experiential Education Division (CEED): Assessment, Curriculum & Instructional Design

Collection

2025 ASEE Annual Conference & Exposition

Authors

Eric Dino Andrews , E.I.T., BPR Surveying; Sherin Ashraf-Hanna E.I.T., ECS Mid-Atlantic; Paul John Ackerman Jr., York College of Pennsylvania

Tagged Divisions

Cooperative and Experiential Education Division (CEED)

® Fundamentals tutorial book. When the site designcourse was first developed in 2019, the Civil 3D® tutorial book was 658 pages and 12 chaptersin length [2]. The 2024 tutorial has now grown to 986 pages, 18 chapters in length [3]. As firstyear students navigate the challenges of college life, implementing an effective lesson methodcan assist in facing challenges in time management [4], anxiety, and their overall wellbeing [5].However, not having a structured lesson approach can lead to students feeling overwhelmed andhelpless. As a result, students may turn to external resources such as ChatGPT, Chegg and onlinesearch engines. These programs can be effective as a supplemental tool for learning but shouldnot be the primary source of information for a

Conference Session

Engineering Libraries Division (ELD) Technical Session 2

Collection

2025 ASEE Annual Conference & Exposition

Authors

Laura Woods, University of Sheffield

Tagged Topics

Diversity

Tagged Divisions

Engineering Libraries Division (ELD)

time.Holly mentions “doing research” a few times throughout her interview but is vague aboutwhat this entails. When pushed for details, she describes relying primarily on Google andGoogle Scholar. She sees Google as most helpful for finding what she terms as “hard facts,”such as how an air-based cooling system works. She uses Google Scholar to find morescholarly sources to supplement her work, but finds that the language is often “veryscientific” and difficult to understand. She also mentions using ChatGPT to help explainthings in simpler terms if her tutor is not available to answer questions. She seems generallyhappy to ask questions of her lecturers and her classmates, but is reluctant to admit shedoesn’t know something in front of people she

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

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

. 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

Preparing Future Chemical Engineers

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sourojeet Chakraborty Ph.D., EIT, Johns Hopkins University; Daniela Galatro, University of Toronto

Tagged Topics

Diversity

Tagged Divisions

Chemical Engineering Division (ChED)

towardsthe Society 5.0 global vision. Coupled with the use of conscious, ethical Artificial Intelligence tools (ChatGPT, JasperAI, Copilot, Gemini, etc.) and learning modalities (active/experiential/inquiry-driven, flipped-classroom, etc.) willempower students to individualize learning experiences/outcomes. However, e-learning must be supplemented byopen discussions [13], and project-based/textbook-based learning, especially for foundational subjects. Withinchemical engineering, core subjects and topics like calculus, transport phenomena, chemical thermodynamics,separation processes, and plant/process design (undergraduate capstone) must be taught through a mix of pedagogicalstrategies. Our results reveal an increase (especially since 2017

Conference Session

Computing and Information Technology Division (CIT) Technical Session 1

Collection

2025 ASEE Annual Conference & Exposition

Authors

Mudasser Fraz Wyne, National University; Alireza Farahani, National University; Lu Zhang, National University

Tagged Divisions

Computing and Information Technology Division (CIT)

Conference Session

Computers in Education Division (COED) Best of CoED Paper Session (Track 1.B)

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jean Louis, University of Florida; Nadia Simone Jean Morrow, University of Florida; Juan E Gilbert, University of Florida

Tagged Divisions

Computers in Education Division (COED)

or health applications, on-device inference means datadoes not need to be transmitted to a server for processing, thus preserving user privacy. This alsosaves bandwidth and battery life [28], as transmitting and receiving are among the most energy-intensive tasks for IoT devices. Local ML models alleviate this burden, mitigate the risk of man-in-the-middle attacks, and enable customization, allowing the model to adapt to individual user needs.While highlighting the benefits of ML, we also addressed its challenges and limitations, suchas adversarial attacks, fairness concerns, and the need for explainable AI (XAI). Many students,having interacted with AI technologies like ChatGPT, were already familiar with AI’s potential forerror. However

Conference Session

Engineering Ethics Division (ETHICS) Technical Session - Student understanding

Collection

2025 ASEE Annual Conference & Exposition

Authors

Eman Hammad, Texas A&M University; Celeste Arden Riley, Texas A&M University - Kingsville; Virginia Pederson; Pierre Atieh

Tagged Divisions

Engineering Ethics Division (ETHICS)

and ChatGPT) models were used to help simplify the survey questionsto avoid complicated discipline specific jargon [32]. The LLM models were prompted torephrase the given question for target reader of an 8th grader. This level was selected based onrecommendations that 85% of a general audience understand information at an eighth gradereading level [32].The revised version was later edited by the research team to ensure alignment and consistencywith the involved disciplines (engineering, psychology) and the question intent. The studyprotocol is followed to administer the surveys to the target student population and to collect thatdata. Depending on the sample size, the proper analysis tools are used to gain insights.A. Study ProtocolThe IRB

Conference Session

Liberal Education/Engineering & Society Division (LEES) Technical Session 1: Critical Reflections on Teaching and Learning

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jennifer Howcroft, University of Waterloo; Kate Mercer, University of Waterloo; Julie Vale, University of Guelph; D'andre Jermaine Wilson-Ihejirika P.Eng., University of Toronto; Stephen Mattucci, University of Guelph

Tagged Topics

Diversity

Tagged Divisions

Liberal Education/Engineering & Society Division (LEES)

with participants in my research and to acknowledge thebiases I bring. From my early struggles with homesickness in first year, to my passion foroutreach and advocacy developed through NSBE, to finally securing my first internship in theOil Sands during my master’s degree which I felt ultimately validated my identity as an engineer,my career pathway has been shaped and informed by the experiences in my undergraduatedegree. These reflections ground me in focus of my PhD research: to illuminate the factorsshaping diverse career paths in engineering and to foster environments where all students canthrive.1 The author identified she used ChatGPT as part of her writing process for this section to synthesize similar writingsshe had previously done