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

Conference Session

Instrumentation in Engineering Projects

Collection

2025 ASEE Annual Conference & Exposition

Authors

Abhijit Nagchaudhuri, University of Maryland Eastern Shore; Lance Ward, University of Maryland Eastern Shore; Danny Pham, University of Maryland Eastern Shore; Anubhav Dixit, University of Maryland College Park; Christopher Snyder, University of Maryland Eastern Shore

Tagged Divisions

Instrumentation Division (INST)

implications analytics obstacles in laboratory and field settings as well as Students reflect on AI, ML, and the impact Design of mobile devices for simulated lunar environments. of utility of large language models such as unknown and rough terrains ChatGPT. such as that may be encountered Students will reflect on their learning in moon. experiences in written reports

Conference Session

Computing and Information Technology Division (CIT) Technical Session 10

Collection

2025 ASEE Annual Conference & Exposition

Authors

Nikunja Swain, South Carolina State University; Biswajit Biswal, South Carolina State University; Janmejay Mohanty, South Carolina State University

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

prompts in LLMs (ChatGPT, Bard and Hugging Face)These modules include lecture notes, practice problems, and quizzes. The learners can completethese modules at their own pace. The course instructor acts as the facilitator and provides help asneeded.The modules can be accessed at https://skills.yourlearning.ibm.com/. Students need to createaccounts to log in and sign up a module to see the module content. The login screen is shown inFigure 2: Figure 2 – Log in options Analysis of Course Survey Results Student Surveys A. Cybersecurity (Fall 2024, Sample Size N = 88)The Cybersecurity module was infused to six sections of CS 150 course during

Conference Session

Computers in Education Division (COED) Track 2.C

Collection

2025 ASEE Annual Conference & Exposition

Authors

Deana Delp, Arizona State University

Tagged Divisions

Computers in Education Division (COED)

students were provided with anexample essay generated by ChatGPT on the topic of the engineering design process. As a class,we reviewed the essay, analyzing its strengths and identifying areas for correction orimprovement. We also explored ways to refine the prompt and discussed potential biases inChatGPT responses. The pre-survey and post-survey questions are detailed in Figure 1. Figure 1: The questions administered on the pre-survey and post-survey aligned with project learning goals for the freshman-level project class.Data Analysis for Freshman-Level Project ClassThe data analysis involved examining the pre-survey and post-survey data and conducting a finalanalysis to compare both surveys to determine growth in each

Conference Session

Faculty Development at Various Career Stages

Collection

2025 ASEE Annual Conference & Exposition

Authors

Matthew W Liberatore, Trine University; Cheryl A Bodnar, The Ohio State University; Selen Cremaschi, Auburn University; Victor Breedveld, Georgia Institute of Technology

Tagged Divisions

Faculty Development Division (FDD)

, these initiatives canhelp faculty members navigate the complexities of their careers and achieve excellence in theirmultifaceted roles. This study serves as a valuable resource for chemical engineering faculty anda template for other engineering disciplines to conduct similar analyses, ultimately promoting aholistic approach to faculty development across the engineering field.AcknowledgmentsThe authors thank assistance from the Kern Family Foundation for some support travel to thisconference and support of new faculty development initiatives. Several generative artificialintelligence tools (e.g., ChatGPT, Co-Pilot) were used to create first drafts of sections of thispaper.AppendixTable 4. Links or references to provide additional details

Collection

2025 ASEE -GSW Annual Conference

Authors

Rahul Sharan Renu, Austin College

Collection

2025 Northeast Section Conference

Authors

Eric P. Flynn; Arthur McAdams

component? It needs to be just large enough to attachacross technical fields [3]. four vacuum hose fittings, and two mounting bolts…we In this paper, we will demonstrate how an LLM (specifically need to ensure the internal cavities can support the airOpenAI ChatGPT-4.0) can provide insights into material flow, and the walls can provide enough thread...”selection, wall thickness, airflow characteristics, and specific Fig. 1. A napkin sketch of the boost manifold design.techniques and tools for machining features in T6-6061aluminum. This is achieved through the model's ability toleverage both causal relationships such as the direct

Conference Session

New Engineering Educators (NEE) Technical Session 2 - Technology Tools

Collection

2025 ASEE Annual Conference & Exposition

Authors

Casey J Rodgers, University of Illinois at Urbana - Champaign; Afeefa Rahman, University of Illinois Urbana-Champaign; Ann C Sychterz Ph.D., P.Eng, University of Illinois at Urbana - Champaign; Jacob Henschen, University of Illinois at Urbana - Champaign

Tagged Divisions

New Engineering Educators Division (NEE)

learning.Following these frameworks, faculty will be able to develop and implement their own custom VRmodules in class to teach civil engineering concepts.AcknowledgementsWe gratefully acknowledge the generous support provided by the Strategic InstructionalInnovations Program (SIIP) from the Academy of Excellence for Engineering Education and theKern Family Foundation Network, whose funding was instrumental in facilitating this research.AI-Assisted Technologies DisclosureIn this paper, ChatGPT was used to enhance the coherence and flow of ideas presented in theintroduction section. This use of AI was limited to improving the connectivity of the text and didnot influence the content, interpretation, or conclusions of the research. The final version of

Conference Session

Civil Engineering Division (CIVIL) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

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

Tagged Divisions

Civil Engineering Division (CIVIL)

. Furthermore,the emphasis on interdisciplinary collaboration mirrors the demands of modernconstruction practices, preparing students to contribute effectively to professionalenvironments. As a forward-looking approach, this integration highlights thetransformative potential of technology in education, setting a foundation forsustainable and efficient learning practices that align with the evolving needs of theconstruction industry.References:Abril, D. E., Guerra, M. A., & Ballen, S. D. (2024). ChatGPT to Support Critical Thinking in Construction-Management Students. 2024 ASEE Annual Conference & Exposition. https://peer.asee.org/48459.pdfAcosta, J., & Guerra, M. A. (2022). Validating Guerra’s Blended Flexible Learning

Conference Session

ECCNE Technical Session 3 - Energy and Society

Collection

2025 ASEE Annual Conference & Exposition

Authors

Tony Lee Kerzmann, University of Pittsburgh; David V.P. Sanchez, University of Pittsburgh; Suraya Rahim, University of Pittsburgh

Tagged Topics

Diversity

Tagged Divisions

Conservation and Nuclear Engineering Division (ECCNE), Energy Conversion

Using Instructor-Specified Criteria, “ Advances in Engineering Education, 2(1), 1-28, 2010.[10] Loughry, M. L., et. al., “Development of a Theory-Based Assessment of Team MemberEffectiveness,” Educational and Psychological Measurement, 67, 505-524, 2007.[11] Loignon, A. C., et. al., “Facilitating Peer Evaluation in Team Contexts: The Impact ofFrame-of-Reference Rater Training,” Academy of Management Learning & Education, 16(4),562-578, 2017.[12] CATME, “CATME Terms Student Dictionary,” https://info.catme.org/student/student-help/catme-terms-student-dictionary/, [Accessed Jan. 12, 2025].Note: ChatGPT was used in this manuscript to check grammar and spelling; (GPT-4o). OpenAI,https://chat.openai.com/chat. [Accessed Jan. 20, 2025]Appendix A

Conference Session

Engineering and Public Policy Division (EPP) Technical Session 1

Collection

2025 ASEE Annual Conference & Exposition

Authors

Hortense Gerardo, University of California, San Diego; Dana Polojärvi, Maine Maritime Academy; Jon Wade, University of California, San Diego

Tagged Divisions

Engineering and Public Policy Division (EPP)

International Game Technology, senior director of Enterprise Server Development at Sun Microsystems, and director of Advanced System Development at Thinking Machines Corporation. Dr. Wade received his S.B., S.M., E.E. and Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology. Dr. Wade is an INCOSE Fellow. ©American Society for Engineering Education, 2025 Generative AI, Artists’ Intellectual Property Rights, and Collective ActionabstractSince the rise of generative AI large language models (LLMs) such as ChatGPT, artists haveinitiated lawsuits over copyright infringement. Developers argue for impunity because they donot directly use images and texts that are

Conference Session

Civil Engineering in the Age of AI

Collection

2025 ASEE Annual Conference & Exposition

Authors

Christina Cercone, Manhattan University; Konstantine Aristomenis Mendrinos, Manhattan College; Matthew Volovski, Manhattan College; JUNESEOK LEE, Manhattan University; Medya Fathi, Manhattan University; Mehdi Omidvar, Manhattan University; Shahriar Quayyum, Manhattan College

Tagged Divisions

Civil Engineering Division (CIVIL)

, [Accessed January 2, 2025].[3] B. Eager and R. Brunton, "Prompting higher education towards AI-augmented teaching and learning practice," Journal of University Teaching & Learning Practices, vol. 20, no. 5, 2023.[4] D. Cotton, P. A. Cotton, and J. R. Shipway, "Chatting and cheating: Ensuring academic integrity in the era of ChatGPT," Innovations in Education and Teaching International, pp. 1–12, 2023.[5] C. Cassidy, "Australian universities to return to ‘pen and paper’ exams after students caught using AI to write essays," The Guardian, Jan. 10, 2023, Available: https://www.theguardian.com/australia-news/2023/jan/10/universities-to-return-to-pen-and- paper-exams-after-students-caught-using-ai-to-write-essays

Conference Session

Computing and Information Technology Division (CIT) Technical Session 7

Collection

2025 ASEE Annual Conference & Exposition

Authors

Udayan Das, Saint Mary's College of California

Tagged Divisions

Computing and Information Technology Division (CIT)

option Historically, across institutions, the implementation option is selected by 15-20% of students. Typically, 5-6 studentsout of 30. This time 16 students out of 35 opted for and completed an implementation. I believe this is indicative ofgreater confidence in being able to accomplish the final project.E. Other notes This is also a course in which I used GPT tools at different points, the results of which I present elsewhere. However,one of the amusing elements of this course was spending a fair amount of time including in-class thought exercisesdeveloping pivot strategies for a dependable O(n log n) QuickSort, only to then ask ChatGPT and Perplexity to generateQuickSort code which was exactly identical, to variable names, that was

Conference Session

Design in Engineering Education Division (DEED) - Team-Based and Experiential Learning

Collection

2025 ASEE Annual Conference & Exposition

Authors

Prarthona Paul, University of Toronto; Anipreet Chowdhury, University of Toronto; Loura Elshaer, University of Toronto; Anushka Sethi, University of Toronto; Hamid S Timorabadi P.Eng., University of Toronto

Tagged Divisions

Design in Engineering Education Division (DEED)

project-based courses. Theexisting pre-trained models did not yield good enough results; therefore, we decided to train ourown. We extracted sample tasks from 200 syllabi from engineering project-based courses. Someof these are publicly available syllabi, from real engineering courses from different NorthAmerican Universities, while others are of fictional engineering courses developed by generativeLLM tools, such as ChatGPT and Microsoft Copilot based on the formats of the real syllabi.These extracted tasks were then labelled with their corresponding classes, which were used totrain a RoBERTa model. This model performed better than the pre-trained models, as it had anF1 score closer to the requirements for the project (outlined in Appendix A

Conference Session

Innovative Pedagogies and Assessment Strategies

Collection

2025 ASEE Annual Conference & Exposition

Authors

Erick S. Vasquez-Guardado, University of Dayton

Tagged Divisions

Chemical Engineering Division (ChED)

area of research. Both exampleshelped the students prepare a script for their final individual recordings. Additionally, a rubric wasprepared to assess the student's performance in the last vodcast assignment. The course instructorprepared the rubric using a series of AI interactions (ChatGPT). Once generated, the rubric wasshared with the students before their assignment due date. The rubric can be seen in Table 1.As noted in Table 1, several aspects of the vodcast recordings were evaluated. Most of the gradewas assigned to the technical content or content knowledge that the students demonstratedthroughout the video recording. Other aspects of the evaluation included relevance and focus,structure and organization, delivery and engagement, use

Conference Session

Minorities in Engineering Division(MIND) Technical Session 2

Collection

2025 ASEE Annual Conference & Exposition

Authors

Aldo R Pinon Villarreal, Angelo State University

Tagged Topics

Diversity

Tagged Divisions

Minorities in Engineering Division(MIND)

personalexperience relating to one of the topics covered in the course materials. The second high contextquestion was a fill in the gap series of questions in which they needed to identify the name of theconcept or equation after providing a description of a real-case scenario. See Figure 1. To deterstudents from copying or collaborating with others, a total of three different exam versions werereleased and the included numeric problems were not previously published so they coul d not befound online. ChatGPT had not been released yet so it had no effect on this investigation, but itwould need to be addressed for future applications.Figure 1. Excerpt from a fill-in-the gap question series to identify the name of the concept orequation by providing them a