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

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

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

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