Collection

2025 ASEE North Central Section (NCS) Annual Conference

Authors

Caleb Edward Scheideger, Ohio Northern University; Evan Louis Fisher, Ohio Northern University; Kaden Wince, Ohio Northern University; Emma Pond, Ohio Northern University; Maxwell Phillips, Ohio Northern University; Abigail Collins, Ohio Northern University; Rhys Francis Davies, Ohio Northern University

described above has been dubbed the “AIPipeline” and consists of the following software components: ●​ Speech-to-Text (STT) Module – voice recognition/natural language processing (NLP) ●​ Large Language Model (LLM) – ex. ChatGPT, Google Gemini ●​ Text-to-Speech (TTS) Module – transforms text output from the LLM into audible speechFor a better understanding, Figure 4 shows a visual representation of the AI Pipeline: Figure 4: AI Pipeline OverviewTo select an LLM for the AI Pipeline, the following five metrics were considered: (1) contextwindow (in thousands of tokens) – the number of tokens (numerical representations of words)that an instance of generative AI can process at once. Essentially, it determines

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Shenghua Wu, University of South Alabama; Min-Wook Kang, University of South Alabama; John Cleary, University of South Alabama; Lisa LaCross, University of South Alabama

Tagged Topics

Diversity, Professional Papers

writing In-class activity2.1 Week 1: First In-person Meeting Activity: Setting Up Your Goal2.1.1 Use of MentimeterIn the first in-person class, the course expectations are introduced. A Mentimeter is used to makethe session interactive and engaging. The following questions are asked during the first meeting,allowing students to see their responses in real-time: How are you today? Use one word todescribe how you feel now. How do you rate your current writing skill? (0-100 points). Howmany journal articles (not including conference presentations) have you published so far? Whatare your expectations for this course? Have you used AI (e.g. ChatGPT) in your academic work?Which area(s) do you find challenging when starting to write? How are

Collection

2025 Northeast Section Conference

Authors

Elyas Irankhah; Sashank Narain; Kelilah L. Wolkowicz

students to learn about lab safety through machine learning [36]. They would select objects deemed safe for a chemistry lab and train the model to classify items, thus directly engaging with the concept of AI learning and classification. The Ask Me Anything (AMA) booth featured a ChatGPT-powered chatbot limited to discussing child-friendly

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Marino Nader, University of Central Florida

Tagged Topics

Diversity, Professional Papers

, DOI: 10. 1080/105112506008661663. Fask, A., Englander, F., & Wang, Z. (2014). Do online Exams Facilitate Cheating? An Experiment Designed to Separate Possible Cheating from the Effect of the Online Test Taking Environment. J Acad Ethic, 12:101–112 DOI 10.1007/s10805-014-9207-14. Charlesworth, P., Charlesworth, D.D., & Vician, C. (2006) Students’ Perspectives of the influence of Web- Enhanced Coursework on Incidences of Cheating, Journal of Chemical Education, vol. 83 No.9.5. Chegg Inc., website https://www.chegg.com, accessed on November 4th, 2024.6. ChatGPT 4o, https://chat.openai.com, accessed on November 4th, 2024.7. Coure Hero, website www.coursehero.com, accessed on November 4th, 2024.8. Nader, M

Collection

2025 Northeast Section Conference

Authors

Haneen Alzahrani; Arthur C. McAdams

[6] Daniel, R. (2021). Exploring creativity through artists’ reflections. Creativity Studies, 14(1), 48-61. https://doi.org/10.3846/cs.2021.1120[7] Dwivedi, Y. K., Tiwari, P., Rana, P. L., Sharma, P. K., Singh, P. K., & [17] Barnett, C. (2003). Culture and democracy: Media, space, andKapoor, J. (2023). Opinion Paper: "So what if ChatGPT wrote it?" representation. Edinburgh University Press.Multidisciplinary perspectives on opportunities, challenges, and implications [18] Benjamin, W. (2008). The work of art in the age of mechanicalof generative conversational AI for research, practice, and policy. reproduction (J. A. Underwood

Collection

2025 Northeast Section Conference

Authors

PS. Dhanasekaran

ensuring its responsible and equitable use [9].can also widen societal and digital inequalities. AI offersnew learning opportunities but may also put II. CHALLENGESmarginalized students at risk. Unsurprisingly, teachers There is growing concern that the widespread use ofview AI as both a "pal and rival" [2]. computers in education may harm students' physical In recent times, concerns have grown in health, contributing to repetitive strain injuries, eyeacademic settings regarding the use of text-generative strain, obesity, and other related conditions. Asartificial intelligence (AI) tools like ChatGPT, Bing, and computers become

Collection

2025 Northeast Section Conference

Authors

Jorge Paricio Garcia; Paul Spirito

potential for inappropriateeffectiveness of market and user research, by leveraging access and misuse of personal or sensitive information, even ingenerative AI tools like ChatGPT, Bard, CoPilot, or Vizcom. the sketching stages, as well others, like inadvertent release ofDesigners and trained engineers can quickly gather and patient data, or de-identification of raw data input for AIsynthesize vast amounts of market and consumer data, algorithms [14]. Wearable healthcare devices are capable ofrevealing opportunities and overlooked user needs, which continuous data recording and can collect extensive patientwould later lead to ethnographic interviews and additional

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

Collection

2025 ASEE -GSW Annual Conference

Authors

Rahul Sharan Renu, Austin College

Conference Session

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

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

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

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

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

Conference Session

CANCELLED: Track 6: Technical Session 1: A Student-Centered, Theory-Informed, Integrated Model to Academic and Career Advising to Educate the Whole Engineer: Transforming Engineering Education and Broadening Participation in Engineering is Possible!

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Olga Pierrakos, Wake Forest University; Melissa C Kenny, Wake Forest University

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

content generated from ChatGPT 4.0 (Sept. 2, 2024)and edited by the lead author, are showcased in Figure 2. We do not suggest that this is anexhaustive list of higher education career advising models, but this information offers somerelevant insights upon which to understand and consider different approaches to career advising. Figure 2: Some of the career advising models we see across higher education. This is not an exhaustive list or representation. Many existing career advising models combine elements and features from various of these models.III. THEORETICAL FRAMEWORKS GUIDING WHOLE STUDENT DEVELOPMENTAs an engineering education researcher, the lead author (Pierrakos) has been an NSF-fundedprincipal investigator

Conference Session

CANCELLED: Track 5: Technical Session 5: Hiring Practices to Build a Diverse Team at Wakr Forest Engineering: Transforming Engineering Education and Broadening Participation in Engineering is Possible!

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Olga Pierrakos, Wake Forest University

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

education faces, and manyorganizations face, in recruiting diverse talent is also known. According to ChatGPT 4.0(September 2, 2024) and edited to be represented in a figure format (Figure 1), we highlight justsome of the challenges that hinder organizations from building diverse teams. Some of thesechallenges that hinder higher education and hinder engineering education too include: • Biases in Recruitment Processes • Biased Institutional Barriers and Practices • Misalignment of Goals and Practices • Resistance to Change • Company Culture and Lack of Inclusivity • Resource Constraints to Implement Effective Strategies • Lack of Diversity