Conference Session

Design in Engineering Education Division (DEED) - Emerging and Sustainable Design Practices

Collection

2025 ASEE Annual Conference & Exposition

Authors

Russell K. Marzette Jr., The Ohio State University; Bhavana Kotla, The Ohio State University; Cal King, The Ohio State University

Tagged Divisions

Design in Engineering Education Division (DEED)

method to find survivors that have access to their phones and can connect to an automatedinternet source. Second, it's useful in hazardous situations like the Turkey earthquake, likementioned before. Third, it offers quick response to people, minimized lives blasting theaftermath.”Sub-theme 4: NoveltyThis sub-theme highlights participants acknowledging the novelty and uniqueness of their createdsolutions (e.g., how the product stands out).“Our project, Flowware, stands out by using ChatGPT API to offer smart, personalized financialmanagement while displaying your finances through react flow, creating a dynamic, real-timemap of your money.”Theme 2: Design and ApplicationThe design and application theme includes challenges, design considerations

Conference Session

GSD 5: Mentorship

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jacqueline E McDermott, Purdue University at West Lafayette (COE); Nathan Tompkins, Wabash College

Tagged Topics

Diversity

Tagged Divisions

Graduate Studies Division (GSD)

mentees and randomly sorting each column independently to create a random butrepresentative set of mentees. The mentees were then manually paired to create the seeds formentoring groups. Sample student data was generated using a combination of generative AI(ChatGPT) and previous student data. Random student names were generated in ChatGPT byasking for a list of 100 random names from all ethnicities in the US with likely ethnicity and genderfor each name (ChatGPT only returned 98 entries). Gender was classified as Man or Woman with2% of the list being randomly classified with a gender of More to account for transgender and non-binary students. Sample student ethnicity was classified as one of: African American/Black, EastAsian/Asian American (e.g

Conference Session

DSAI Technical Session 3: Integrating Data Science in Curriculum Design

Collection

2025 ASEE Annual Conference & Exposition

Authors

Md. Yunus Naseri, Virginia Polytechnic Institute and State University; Vinod K. Lohani, Virginia Polytechnic Institute and State University; Manoj K Jha P.E., North Carolina A&T State University; Gautam Biswas, Vanderbilt University; Caitlin Snyder; Steven X. Jiang, North Carolina A&T State University; Caroline Benson Sear, Virginia Polytechnic Institute and State University

Tagged Topics

Diversity

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

required by employers. As more data and analytical methods becomeavailable, more aspects of the economy, society, and daily life will become dependent on data-driven decision-making. Recognizing this shift, the National Academies of Sciences (2018)emphasizes that academic institutions must prioritize developing "a basic understanding of datascience in all undergraduates" to prepare them for this new era [1]. This is particularly crucial forSTEM graduates, who must develop varying levels of expertise in working with data – the abilityto understand, interpret, and critically evaluate data, as well as to use data effectively to informdecisions. The recent emergence of large language models (LLMs) such as ChatGPT, which arebecoming increasingly

Conference Session

ENT-4: Experiential Approaches to Developing Entrepreneurial Mindsets in Engineering

Collection

2025 ASEE Annual Conference & Exposition

Authors

Stephanie G Wettstein, Montana State University - Bozeman

Tagged Divisions

Entrepreneurship & Engineering Innovation Division (ENT)

could focus on performing the jigsaw activities without thealumni present or the seminar series to see if the change in EM is similar and a larger sample sizeof students would benefit the study.AcknowledgmentsI would like to acknowledge the Robert D. and Patricia E. Kern Family Foundation, Inc. and thetask force of leaders representing the Engineering Unleashed Faculty Development communitywho selected me for the KEEN Fellowship and provided the grant funds for the activities.Additionally, I would like to thank Dr. Douglas Hacker who performed the statistical analysesreported within. During the preparation of this work, I used ChatGPT in order to improve thereadability and concision of the document. After using ChatGPT, I reviewed and edited

Conference Session

Sustainability and Social Responsibility

Collection

2025 ASEE Annual Conference & Exposition

Authors

Erick S. Vasquez-Guardado, University of Dayton; Megan Morin, North Carolina State University at Raleigh

Tagged Divisions

Chemical Engineering Division (ChED)

Effects of Alcohol in Heat Transfer Fluid Flow and Heat Transfer Principles in ClimateIn addition to obtaining the “top-ranked” micromoments, we also examine the students’suggestions for future efforts. Examining the answers to question P5: What can be improved forfuture student-led micromoment presentations? and using AI (ChatGPT 4.0), five general themeswere obtained, including: “Alignment with class material, guidance and resources, timing andaccessibility, engagement and interaction, and open-ended creativity with practical constrains.” Ofsignificance in the alignment with class material, we found that presentations should connectdirectly with class topics to enhance understanding and relevance of the content. Also, studentsnoted that

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Tayo Obafemi-Ajayi, Missouri State University; Naomi L Dille, Missouri State University; Dhanush Bavisetti, Missouri State University; Sherrie Ilene Zook

Tagged Divisions

Computers in Education Division (COED)

for teaching 6th-grade Missouri math standards, incorporating project-based learning with LEGO Mindstorm cars and coordinate plane activities. These activities provide hands-on,engaging ways to connect coding with math standards, fostering both computational thinking and mastery ofgrade-level concepts. This provided a framework to implement advanced ML knowledge into STEM education bydeveloping practical methodologies to teach complex ML principles through easily accessible tools. For the high school students, an intentional choice was made to utilize Scratch, rather than Python for program-ming due to the influence of AI tools (such as ChatGPT) that can provide the entire Python code script. Scratchseemed a little more foolproof, as

Conference Session

DSAI Technical Session 1: K–12 and Early Exposure to Data Science and AI

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sri Krishna Chaitanya Velamakanni, Pennsylvania State University; Suman Saha, Pennsylvania State University

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

ethical concerns, biases, andover-reliance on AI, which could undermine critical thinking and equitable access to education.E. Microlearning, AI-Driven Feedback, and Student EngagementAI-generated feedback has also emerged as a key enabler of personalized education. Escalantedemonstrated that AI tools provide concise, actionable guidance, aligning with the principles ofbite-sized learning [28]. Similarly, studies such as KOGI's application in programming educationand insights from ChatGPT in first-year engineering courses emphasize the value of modular,on-demand support in enhancing educational outcomes [29]. These works collectively reinforcethe importance of tailored educational resources, such as microlearning videos, in addressing thespecific

Conference Session

Engineering Education Methods and Reflections

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jad El Harake, Vanderbilt University; gina yu, Vanderbilt University; Kaden Jorge Tro; Jonathan Ehrman, Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA

Tagged Topics

Diversity

Tagged Divisions

Student Division (STDT)

perceived growth and development of the student. In the latter case, manualcoding of the responses revealed which specific skills were acquired by the student and identifiedby the mentor but not by the student response, leading to a positive score discrepancy, or theareas which mentors identified as having room for improvement, leading to a negative scorediscrepancy.When considering the thematic content of all responses rather than focusing on those whichpresented with score discrepancies, coding and tallying of responses was complemented with theaid of the LLM ChatGPT (OpenAI, CA, USA). The use of LLMs in content analysis has beenpreviously shown to have good agreement with human results [12], [13]. In this study, ChatGPTwas prompted to identify

Conference Session

Liberal Education/Engineering & Society Division (LEES) Technical Session 8: Communication and Liberal Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Amanda Dawn Hilliard, The Johns Hopkins University

Tagged Topics

Diversity

Tagged Divisions

Liberal Education/Engineering & Society Division (LEES)

-5ct7-54du.[13] S. A. Athaluri, S. V. Manthena, V. S. R. K. M. Kesapragada, V. Yarlagadda, T. Dave, and R. T. S. Duddumpudi, “Exploring the Boundaries of Reality: Investigating the Phenomenon of Artificial Intelligence Hallucination in Scientific Writing Through ChatGPT References,” Cureus, Apr. 2023, doi: 10.7759/cureus.37432.[14] A. E. Greene, Writing Science in Plain English, Chicago, IL, USA: The University of Chicago Press, 2013.[15] G. R. Hess and E. N. Brooks, “The Class Poster Conference as a Teaching Tool,” Journal of Natural Resources and Life Sciences Education, vol. 27, no. 1, pp. 155–158, 1998, doi: 10.2134/jnrlse.1998.0155.[16] J. Schimel, Writing Science: How to Write Papers that Get Cited and Proposals

Conference Session

First-Year and Experiential Learning for Women Engineers

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jie Sheng, University of Washington, Tacoma; Justin Wang, The Overlake School

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering Division (WIED)

curriculum of our Computer Engineering program and require only basicknowledge of physics and calculus. For Arduino code, templates will be given and explained, soattendees can focus on the key concepts like A/D and D/A conversions, circuit modeling andperformance, feedback control, as well as Proportional-Integral-Derivative (PID) controller.The organizing faculty worked with the recruiting staff and started the preparation in latesummer of 2024. ChatGPT found a name for the workshop as ‘Circuit Breaker: Women inEngineering’; and Nov. 15 was chosen for this half-day hands-on free workshop from 12 to 4pm.We chose Nov. 15 since it was a Friday when community colleges in the area usually don’t offerclasses in the afternoon. Also, the Autumn quarter is

Conference Session

ME Division 6: Innovative Simulation and Extended Reality Techniques

Collection

2025 ASEE Annual Conference & Exposition

Authors

Osama Desouky, Texas A&M University at Qatar; Marwa AbdelGawad, Hamad Bin Khalifa University

Tagged Divisions

Mechanical Engineering Division (MECH)

understanding and experience.Additionally, applying robust statistical methods is essential for tracking and analyzing studentperformance over time, ensuring that the effectiveness of the VR interventions can be measured andrefined for future improvement. IX. Suggested Survey QuestionsPlease rate your agreement with each statement using the following scale:*These questions were formatted and formulated with the help of ChatGPT: • 1 - Strongly Disagree • 2 - Disagree • 3 - Neutral • 4 - Agree • 5 - Strongly AgreeA. Learning and Understanding 1. The VR activities enhanced my understanding of complex mechanical concepts. 2. VR helped me visualize engineering problems better than traditional methods

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Gautom Kumar Das, University of Maryland Baltimore County

Tagged Divisions

Experimentation and Laboratory-Oriented Studies Division (DELOS)

allowed to use generative AI tools (e.g., ChatGPT) during anystage of the writing process or they could choose not to use them. If AI assistance was used,students were asked to include the following information in the Appendix of their reports: theprompt(s) used, and other details on how the AI-assisted content was incorporated or revised.This information was collected to ensure the accuracy of the report content and the authenticityof references.2.2 Instructor’s AssessmentA total of 48 draft reports (i.e., first submission) were evaluated for this study. Reports in whichstudents self-reported the Checklist were analyzed further for this study.3. Results and DiscussionAs mentioned earlier, the primary goal of this study was to evaluate the

Conference Session

ELOS Technical Session 1: Integrating AI, VR, and MR in Engineering Lab Experiences

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jessica Ohanian Perez, California State Polytechnic University, Pomona; Yitong Zhao, California State Polytechnic University, Pomona; Juliana Lynn Fuqua, Cal Poly Pomona

Tagged Divisions

Experimentation and Laboratory-Oriented Studies Division (DELOS)

question and wanted a simple answer. When that happened, they wanted to be able to turn off the AI temporarily or permanently. They coped by totally muting it. A better solution would be for the AI to have a feature like Alexa or Siri in which users can easily say “hey, stop”. That’s essential, according to students. • How the AI was responding to the surrounding speech. AI occasionally responded to not direct questions so if the student was talking through the lab as they completed the assignment, the AI would respond to a question that was not asked. • Students felt that the AI was trained on ChatGPT. Students were asking history questions to it, and it was answering with somewhat relevant

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

John William Hassell, OU Polytechnic Institute; Christopher Freeze, The University of Oklahoma; Ahmed Ashraf Butt, The University of Oklahoma; H. Glen McGowan III, Google; William Ray Freeman

Tagged Divisions

Computers in Education Division (COED)

educators.By removing technical barriers while maintaining pedagogical quality, we aim to support moreefficient and effective assessment creation processes across engineering disciplines. Future workwill focus on measuring this impact through detailed evaluation of system adoption patterns andeducational outcomes.References[1] J. Hassell, "Best Practices for Using Generative AI to Create Quiz Content for the CanvasLMS," 2024 ASEE Midwest Section Conference, ASEE, 2024.[2] S. Willison, "Things we learned about LLMs in 2024," SimonWillison.net, Dec. 31, 2024.[Online]. Available: https://simonwillison.net/2024/Dec/31/llms-in-2024/.[3] J. Yang et al., "Harnessing the Power of LLMs in Practice: A Survey on ChatGPT andBeyond," ACM Transactions on Knowledge

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Ahmed Ashraf Butt, University of Oklahoma; Saira Anwar, Texas A&M University; Asefeh Kardgar, Texas A&M University

Tagged Divisions

Computers in Education Division (COED)

limitation was that we used a general-purpose GPT-4 model without any fine-tunedhuman annotator. Fine-tuning GPT-4 with human-annotated LO evaluation based on theSMART criteria may improve the LLM's performance. The third limitation was that although weused the SMART criteria, its criteria needed to be refined and evaluated by educational experts.This process will help us to design better guidelines for evaluating learning objectives. Lastly,we only used 1 LLM model (i.e., GPT-4) to evaluate LOs. Therefore, exploring the efficacy ofother LLM models and comparing their ability to assess LOs is necessary.References:[1] E. Kasneci et al., “ChatGPT for good? On opportunities and challenges of large language models for education,” Learn. Individ

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

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

. 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

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Muhammed Yakubu, University of Toronto; Jasnoor Guliani, University of Toronto; Nipun Shukla, University of Toronto; Dylan O'Toole; Hamid S Timorabadi P.Eng., University of Toronto

Tagged Divisions

Computers in Education Division (COED)

CHATGPT prompt engineering method for automatic question generation in English education,” Education and Information Technologies, vol. 29, no. 9, pp. 11483–11515, Oct. 2023. doi:10.1007/s10639-023-12249-8[10] I. Coffee, “Anki FSRS Explained,” Anki-decks.com, 2024. https://anki-decks.com/blog/post/anki-fsrs-explained/ (accessed Apr. 29, 2025).[11] B. C. Figueras and R. Agerri, “Critical Questions Generation: Motivation and Challenges,” arXiv.org, 2024. https://arxiv.org/abs/2410.14335 (accessed Apr. 29, 2025).[12] S. Mucciaccia, T. Paixão, F. Mutz, A. De Souza, C. Badue, and T. Oliveira-Santos, “Automatic Multiple-Choice Question Generation and Evaluation Systems Based on LLM: A Study Case With University Resolutions

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Aysel Guliyeva, The Institute of Education of the Republic of Azerbaijan; Ibrahim H. Yeter, Nanyang Technological University

Tagged Divisions

Pre-College Engineering Education Division (PCEE)

for educators and policymakers to enhance AI literacy among kindergarten teachers.IntroductionEducation, one of the industries most significantly impacted by rapid advancements in artificialintelligence (AI), is on the brink of a revolution. Since the introduction of generative AItechnologies in 2022, as demonstrated by ChatGPT and other platforms, the potential of thesetools to revolutionize a range of educational processes has come to light more and more [1]. AIenables a revolutionary change in education by utilizing its powers in data analysis, patternrecognition, and personalized feedback. In addition to improving teaching strategies, thistechnology is changing how students learn, encouraging participation and comprehension [2, 3

Conference Session

First-Year Programs Division (FPD) Technical Session 12: Bridging the Gap - Strategies to Support Diverse Learners in Early Engineering Courses

Collection

2025 ASEE Annual Conference & Exposition

Authors

Brainerd Prince, Plaksha University; Sohan Panda, Plaksha University; Shubham Goel, Plaksha University; Tanmay Ravi Chowdhary, Plaksha University

Tagged Divisions

First-Year Programs Division (FPD)

Metric Analysis of ‘The Future of Thinking Analysis of PBL Video (Part Two) Manifesto’ (Part One) AI Utilization The average AI-generated content of all AI tools were used to a lesser extent 15 students is about 80-85% generated for elaborating ideas and content using AI tools such as ChatGPT, primarily creation, complemented by for structuring, content creation and paraphrasing and incorporating research. The team relied heavily on class research papers. Around 30% of the content was AI-generated and later notes and ideas taught in class which were rephrased. As

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jessica Lofton, University of Evansville

Tagged Divisions

Mechanical Engineering Division (MECH)

., Kim, S.H., Lee, D. et al. Utilizing Generative AI for Instructional Design: Exploring Strengths, Weaknesses, Opportunities, and Threats. TechTrends 68, 832–844 (2024). https://doi.org/10.1007/s11528-024-00967-w [4] Nikolic, S., Sandison, C., Haque, R., Daniel, S., Grundy, S., Belkina, M., … Neal, P. (2024). ChatGPT, Copilot, Gemini, SciSpace and Wolfram versus higher education assessments: an updated multi-institutional study of the academic integrity impacts of Generative Artificial Intelligence (GenAI) on assessment, teaching and learning in engineering. Australasian Journal of Engineering Education, 29(2), 126–153. https://doi.org/10.1080/22054952.2024.2372154 [5] Subramanian, R., & Vidalis, S

Conference Session

Enhancing Student Engagement and Support in ECE Education

Collection

2025 ASEE Annual Conference & Exposition

Authors

Rohit Dua, Missouri University of Science and Technology

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

, especially in individual project implementations. Group project work (maximum of two students per group) can help lower the required amount of interaction time. Moreover, hiring a Teaching Assistant (TA) can help lower the interaction time if hiring funds are available, which can be a challenge. Of course, finding a good TA for the job is also a challenge! Continuous creativity: To keep projects challenging and minimize cheating and copying past executed projects, creating new and varied project specifications can be challenging and time consuming. This issue is especially observed in courses that are offered frequently. Threat from AI: To ensure students are not using AI tools, such as ChatGPT, to find solutions for

Conference Session

DSAI Technical Session 5: Educational Technology and Innovative Tools

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nandan Reddy Muthangi, University of Toledo; Ananya Singh, The University of Toledo

Tagged Divisions

Data Science and Artificial Intelligence (DSAI) Constituent Committee

. Lundberg, "An introduction to explainable AI with Shapley values," SHAP Documentation. [Online]. Available: https://shap.readthedocs.io/en/latest/example_notebooks/overviews/An%20introduction% 20to%20explainable%20AI%20with%20Shapley%20values.html [9] C. Piech et al., "Deep knowledge tracing," in Adv. Neural Inf. Process. Syst., vol. 28, 2015. [10] A. M. Hasanein and A. E. E. Sobaih, "Drivers and consequences of ChatGPT use in higher education: Key stakeholder perspectives," Eur. J. Investig. Health Psychol. Educ., vol. 13, no. 11, pp. 2599–2614, Nov. 2023, doi: 10.3390/ejihpe13110181. [11] Y. Lu, D. Wang, P. Chen, and Z. Zhang, "Design and evaluation of trustworthy knowledge tracing model for intelligent tutoring

Conference Session

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

Collection

2025 ASEE Annual Conference & Exposition

Authors

Julie M. Smith, Institute for Advancing Computing Education; Jacob Koressel; Bryan Twarek

Tagged Divisions

Pre-College Engineering Education Division (PCEE)

describe – all of whichare at the lowest two Bloom’s levels. Thus, it seems to be the case that the different standardsemphasize lower-order thinking skills.It is perhaps surprising given the recent expansion of AI technologies that the least paralleledCSTA standard concerns the implementation of AI algorithms. However, that expansion is sorecent – largely stemming from the November 2022 introduction of ChatGPT – that it has not yethad an impact on learning standards at scale. We anticipate that future iterations of state andCSTA standards will probably focus more on AI. Many states adopted their standards between2016 and 2022 – a narrow window in itself, with significant policy implications.Third, the most frequent difference between the state

Conference Session

AI in the Engineering Management Classroom

Collection

2025 ASEE Annual Conference & Exposition

Authors

Edwin R Addison, North Carolina State University at Raleigh

Tagged Topics

Diversity

Tagged Divisions

Engineering Management Division (EMD)

processing, and transformer architectures and how they fit into larger systems • Generative adversarial networks and survey of AI methods (Bayesian reasoning, genetic algorithms, expert systems) and when they are used • Relationship with signal processing, pattern recognition, and data analytics • Open-source tools, data sourcing, licensing, and rights management • Data cleansing strategies and data cost estimation, including cost of data generation • LLMs, prompt engineering, ChatGPT, and organizational adoption and use • Multi-modal AI, agent-based models, and humanoid robotics • Computing infrastructure for AI, including compute requirements and platform selection • The disruptive impact of AI on the

Conference Session

Design in Engineering Education Division (DEED) - Best in DEED

Collection

2025 ASEE Annual Conference & Exposition

Authors

L'Nard E.T. Tufts II, Stanford University; Alessandra O. Napoli, Stanford University; Shima Salehi, Stanford University; Anna Lisa Boslough, Stanford University

Tagged Divisions

Design in Engineering Education Division (DEED)

efficacy.AcknowledgmentsWe utilized resources from Stanford University's "AI Playground" to explore and validate ourapproaches to incorporating AI tools into the feedback generation process. Through this portal,Anthropic's Claude.ai, version 3.5-Sonnet, helped automate the analysis of student reflectiveresponses by identifying general themes, common omissions, unique realizations, and evidenceof reflective practice. OpenAI's ChatGPT, version 4o, helped generate reflection scores forstudent responses, providing a quantitative measure of reflective practice. We thank thedevelopers of these tools which are available using the links below.https://aiplayground-prod.stanford.eduhttps://claude.aihttps://chat.openai.comReferences[1] T. Anderson and J. Shattuck, "Design

Conference Session

Engineering Ethics Division (ETHICS) Technical Session - Ethics in ML/AI

Collection

2025 ASEE Annual Conference & Exposition

Authors

Emad Ali, Virginia Polytechnic Institute and State University; Bailey Kathryn McOwen, Virginia Polytechnic Institute and State University; Arsalan Ashraf, Virginia Polytechnic Institute and State University; Dayoung Kim, Virginia Polytechnic Institute and State University

Tagged Divisions

Engineering Ethics Division (ETHICS)

Conference Session

Computers in Education Division (COED) Track 6.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sandra Monika Wiktor, University of North Carolina at Charlotte; Mohsen M Dorodchi, University of North Carolina at Charlotte

Tagged Divisions

Computers in Education Division (COED)

Conference Session

Design in Engineering Education Division (DEED) - Innovative Assessment Strategies in Design

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jessie Cortez, Texas A&M University; Joanna Tsenn, Texas A&M University

Tagged Divisions

Design in Engineering Education Division (DEED)

sampleBackground sections responding to the following problem statement: The McDonnell Douglas DC-10's outward-opening cargo door has a faulty locking mechanism that, upon failure, causes the door to open and the plane to explosively decompress. The project sponsor, a representative of McDonnell Douglas, has asked the design team to redesign the aft cargo door to prevent accidental opening during flight.Each background section was written with the aid of ChatGPT to simulate problems withrhetorical appropriateness and formatting and organization observed in students’ backgroundresearch sections in previous semesters. For example, the technical writing coordinator promptedChatGPT to write a background research section focused on types of cargo doors

Conference Session

Computing and Information Technology Division (CIT) Technical Session 8

Collection

2025 ASEE Annual Conference & Exposition

Authors

Juan Felipe Calderón, Universidad Andres Bello, Viña del Mar, Chile; Marco Aguilera; Martin Ignacio Gil; Maria Elena Truyol, Universidad Andres Bello, Santiago, Chile; Danilo Leal, Universidad Andres Bello; Claudia Bascur, Universidad Andres Bello, Santiago, Chile

Tagged Divisions

Computing and Information Technology Division (CIT)

like programming, where innovative methodologieshave outperformed traditional teaching methods [1], [2]. Adaptive learning technologies arecrucial for customizing educational experiences to meet diverse student needs, promotingflexibility and adaptability within VLEs. Implementing LLMs can enhance this adaptive learningby providing real-time feedback and support, fostering a more engaging educationalenvironment. Studies have shown that generative artificial intelligence tools, such as ChatGPT,can motivate students, increase participation, and offer individualized assistance, therebyimproving learning experiences[3], [4]. However, there are notable gaps in the practicalapplication of LLMs within VLEs, as many institutions struggle to integrate

Conference Session

Computers in Education Division (COED) Track 2.D

Collection

2025 ASEE Annual Conference & Exposition

Authors

Maryam Khalid Multani, University of Florida; Laura Melissa Cruz Castro, University of Florida

Tagged Divisions

Computers in Education Division (COED)

Systematic Literature Review,” in Frontiers in Education 2024, Washington DC, Oct. 2024.[5] L. Labadze, M. Grigolia, and L. Machaidze, “Role of AI chatbots in education: systematic literature review,” Int J Educ Technol High Educ, vol. 20, no. 1, p. 56, Oct. 2023, doi: 10.1186/s41239-023-00426-1.[6] B. Freeman and K. Aoki, “ChatGPT in education: A comparative study of media framing in Japan and Malaysia,” in Proceedings of the 2023 7th International Conference on Education and E-Learning, in ICEEL ’23. New York, NY, USA: Association for Computing Machinery, May 2024, pp. 26–32. doi: 10.1145/3637989.3638020.[7] S. Hadjerrouit, “Learning Management Systems Learnability: Requirements from Learning Theories,” presented at the