Conference Session

Engineering Economy Division (EED) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Tamara R. Etmannski, University of British Columbia

Tagged Topics

Diversity

Tagged Divisions

Engineering Economy Division (EED)

material. Upon further investigation, it was determined thatwhen asking ChatGPT some specific questions, the responses are also very similar to thatmaterial, suggesting its use of the publisher’s material in its training, and perhaps use of eitherthe materials directly or of ChatGPT by the student development team. In any case, the materialdevelopment phase of the project ended in September, four months before this discovery (inFebruary 2024) so the student development team was unable to support in any corrections thatwere required. The instructor then rewrote and/or restructured many slides prior to use, to ensurethe was no question of copyright infringement.The debugging process proceeded seamlessly, with students in the course finding 29typos

Collection

2025 ASEE -GSW Annual Conference

Authors

Colby Edward Kurtz, Houston Christian University

Tagged Topics

Diversity

AbstractThis paper demonstrates the design and implementation of an innovative gamified softwareapplication for learning human-spoken languages. The game serves as an interactive and enjoyablesupplement to aid the learning process of different languages for elementary-aged children. At its core,the application uses a translation Application Programming Interface (API) to process text and outputtranslations in the target language chosen by the learner. Additionally, it is AI-enabled, allowing theutilization of APIs such as OpenAIs’s ChatGPT to enhance the translation capabilities. Provided is abasic proof of concept that was developed as part of the Final Pi Project in the Intermediate ComputerProgramming (COSC 1352) course. The gamified program was

Conference Session

Educational Research and Methods Division (ERM) Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

Xiuhao Ding, University of Illinois at Urbana - Champaign; Meghana Gopannagari, University of Illinois at Urbana - Champaign; Kang Sun, University of Illinois at Urbana - Champaign; Alan Tao, University of Illinois at Urbana - Champaign; Delu Louis Zhao; Sujit Varadhan, University of Illinois at Urbana - Champaign; Bobbi Lee Battleson Hardy, University of Illinois at Urbana - Champaign; David Dalpiaz, University of Illinois at Urbana - Champaign; Chrysafis Vogiatzis, University of Illinois at Urbana - Champaign; Lawrence Angrave, University of Illinois at Urbana - Champaign; Hongye Liu, University of Illinois at Urbana - Champaign

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods Division (ERM)

gold standard to evaluateautomated text analytic approaches. Raw text from open-ended questions was converted intonumerical vectors using text vectorization and word embeddings and an unsupervised analysisusing document clustering and topic modeling was performed using LDA and BERT methods. Inaddition to conventional machine learning models, multiple pre-trained open-sourced local LLMswere evaluated (BART and LLaMA) for summarization. The remote online ChatGPTclosed-model services by OpenAI (ChatGPT-3.5 and ChatGPT-4) were excluded due to subjectdata privacy concerns. By comparing the accuracy, recall, and depth of thematic insights derived,we evaluated how effectively the method based on each model categorized and summarizedstudents

Conference Session

The Best of Computers in Education Division (COED)

Collection

2024 ASEE Annual Conference & Exposition

Authors

Gerald Tembrevilla, Mount Saint Vincent University; Mohosina Jabin Toma, University of British Columbia, Vancouver; Marina Milner-Bolotin, University of British Columbia, Vancouver

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

were recorded and uploaded on CLAS, they couldsee the difference between their original and improved lessons. It was an empowering learningexperience that gave the preservice teachers the much-needed confidence that they can figurethings out and if a lesson doesn’t go as well as they wanted the first time around, they alwayshave a second chance.Exploration of Novel Pedagogical ApproachesLearning to remove yourself from your own lessons and to reflect on them in order to teachbetter in the future is a core quality of a STEM educator in the 21st century. To be successful inthe era of fast-changing student population, rapidly evolving technologies, that haveunprecedented pedagogical potential, such as ChatGPT [42, 43], continuously

Collection

2024 South East Section Meeting

Authors

Brian Aufderheide, Hampton University; LaNika M. Barnes, Albemarle County Public Schools (Charlottesville, Virginia); Otsebele E Nare, Hampton University; Garrick E. Louis, University of Virginia; Daniel Webster Fairley II, 100 Black Men of Central Virginia

Tagged Topics

Diversity

represented the overall interest of all the participating students. The students fillingout the form were 38 out of a total of 46 or 82.6%. The breakdown of students who stated theirpreferred topics was 17 (85%) from HBCU, 9 (100%) from high school, and 12 (70.6%) fromPWI. Over 90% of the students who filled out the form got one of their top three choices. Seetable 1 below for more information on topics and student choices. In the end, those not chosenwere Drone Use and Global Justice, AI and Written Papers ChatGPT, and Flint Michigan Water. Table 1: Ethics Case Study Topics % Student Choices No. Topic

Collection

2024 South East Section Meeting

Authors

Arezou Shafaghat, Kennesaw State University; Mohammad Jonaidi; Hoseoen Lee; Craig A Chin, Kennesaw State University; Ali Keyvanfar, Kennesaw State University

Tagged Topics

Diversity

: Non-numerical evaluation at the end of an instructionalunit, focusing on the application of learned concepts. - Quantitative Summative Assessment: Numerical evaluation at the end of an instructionalunit, like final grades or scores.XYZ EduOwl Tool ValidationIn order to comprehensively evaluate the user perception of the XYZ EduOwl tool, an innovativeapproach was employed using ChatGPT, a generative AI language model developed by OpenAI.The model, known as ADA, was instrumental in generating a simulated dataset, which wascrucial for our analysis.With the assistance of ChatGPT ADA, a set of simulated responses was structured to mirror real-world user feedback. This simulation involved creating responses for 100 respondents,encompassing a

Conference Session

Biomedical Engineering Division (BED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Amy N Adkins, North Carolina State University; Naji S Husseini, North Carolina State University; Lianne Cartee, North Carolina State University

Tagged Topics

Diversity

Tagged Divisions

Biomedical Engineering Division (BED)

into technical writing instruction.References[1] “Best Practices for Using AI When Writing Scientific Manuscripts: Caution, Care, andConsideration: Creative Science Depends on It” ACS Nano 2023, 17, 5, 4091–4093. 2023.https://doi.org/10.1021/acsnano.3c01544[2] Leung TI, de Azevedo Cardoso T, Mavragani A, Eysenbach G. Best Practices for Using AITools as an Author, Peer Reviewer, or Editor. J Med Internet Res. 2023 Aug 31;25:e51584. doi:10.2196/51584. PMID: 37651164; PMCID: PMC10502596.[3] J. Qadir, "Engineering Education in the Era of ChatGPT: Promise and Pitfalls of GenerativeAI for Education," 2023 IEEE Global Engineering Education Conference (EDUCON), Kuwait,Kuwait, 2023, pp. 1-9, doi: 10.1109/EDUCON54358.2023.10125121.[4] A. Adkins, N. S

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Quintana (Quincy) Clark, Oregon State University; Chidinma Grace Okoye; Theodore Ja

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

eNotebook to include a tutoring AI feature that students could talk to along with their favoritestudy methods. eNotebook provides a general platform for nearly all of today’s study methods andmaterials students use to create and customize for efficient access and assessment. For example,we have implemented a two-way talking conversation feature called Jarvis, which is an audio-to-text / text-to-audio feature with a ChatGPT engine with AI-specific aids to improve the quality ofAI responses. We have embedded weblinks to over 50 of the most popular study apps easilyaccessible through a pull-down menu, where favorites appear at the top of the list. We haveimplemented a feature that converts handwritten notes into typed text. Images, audio, videos

Conference Session

Track 3: Technical Session 1: Bridging Educational Equity Gaps: A Systematic Review of AI-Driven Tools for Students Living with Disabilities in Engineering and STEM Education

Collection

2025 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Kevin Zhongyang Shao, University of Washington; Denise Wilson, University of Washington; Eric Kyeong-Min Cho, University of Washington; Sophia Tang, University of Washington; Hanlin Ma, University of Washington; Sep Makhsous, University of Washington

Tagged Topics

2025 CoNECD Paper Submissions, Diversity

intersecting factors on theaccessibility of educational resources, opportunities, accommodations, and support systems.In recent years, the pursuit of educational equity has increasingly intersected with advancementsin technology, particularly artificial intelligence (AI). Just as earlier legal and policy reformssought to address the systemic barriers faced by marginalized groups, technological innovationsare opening new pathways to equitable education. A pivotal moment in AI research occurred inMarch 2016, when AlphaGo defeated the world chess champion, capturing global attention andsparking global interest across numerous fields. In education, AI-driven tools have similarlyushered in a new era, with tools like ChatGPT. Introduced in November 2022

Collection

2023 Fall Mid Atlantic Conference: Meeting our students where they are and getting them where they need to be

Authors

Sakhi Aggrawal, Purdue University at West Lafayette (PPI); Kevin C. Dittman, Purdue University at West Lafayette (COE)

Tagged Topics

Diversity

, andmusic, by learning patterns from existing data [14]. This differs from other AI approaches thatfocus on tasks like classification, prediction, and decision-making. Generative AI involvestraining a machine learning model on large amounts of data to learn the underlying patterns andthen using that learning to generate new content that has not been seen before.One example of generative AI is the ChatGPT language model developed by OpenAI, which hasbeen recognized for its ability to produce text that appears to be written by humans [15]. Recentadvancements in generative AI have shown significant potential in several fields, includinghealthcare, where generative models have been used to generate synthetic medical images [16],and robotics, where

Conference Session

DSA Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

Abdulrahman Alsharif, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA), Diversity

traditionalNLP methods alone [21]. Additionally, as Large Language Models (LLMs) increase and rapidly develop, manyorganizations and researchers compete to create more powerful and advanced GAI models.These new models aim to outperform older versions [22]. GAI models come as applications ortools like ChatGPT, GitHub Copilot, and Bard to name a few. One key example is the GPTmodel, which has gone through versions 3, 3.5, and now 4, each with different capabilities [22].When new GPT versions are released, they often gain new features, capabilities, and parameterscompared to previous versions [22]. Also, OpenAI and other research groups constantly work toimprove LLMs and other AI models. This could impact the accuracy of the information in

Conference Session

Broadening Perspectives in Construction Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Daniel Linares, Florida Gulf Coast University; Diana Marcela Franco Duran, University of Virginia; Kenneth Stafford Sands II, Auburn University; David R. Gutierrez, University of Virginia; Deyrel Diaz, Clemson University

Tagged Topics

Diversity

Tagged Divisions

Construction Engineering Division (CONST)

can understand what is appropriate for this this task? working well or not in task? the project. Which of the following tools are more appropriate for this problem? Expected Correct Answers Drones Virtual Reality Programming ChatGPT (+1) Point

Conference Session

Computing and Information Technology Division (CIT) Technical Session 6

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sreekanth Gopi, Kennesaw State University; Nasrin Dehbozorgi, Kennesaw State University

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology Division (CIT)

]. Anotherstudy indicates that ChatGPT-4 outperforms ChatGPT-3.5 and BARD by Google Inc. in several reasoning tasks,particularly in abductive reasoning, mathematical reasoning, and commonsense reasoning [46]. Therefore, in thisstudy, we chose GPT-4 as our preferred LLM model.Educational Implications in Engineering Easy access to psychological monitoring and measurement is imperative in engineering education due to theunique stressors associated with this field. Studies have shown that the engineering culture, often perceived asmasculine, competitive, and exclusionary, can lead to significant stress and mental health challenges for students,particularly for women and students of color [47]. This environment is characterized by a belief in enduring

Conference Session

Virtual Design and Construction (VDC) in Construction Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Luciana Debs, Purdue University; Alex Souza; Fernando Romero Moraes, University of Massachusetts Amherst

Tagged Topics

Diversity

Tagged Divisions

Construction Engineering Division (CONST)

construction industry, even fewer studies haveexplored the impact of predictive analytics using large language models (LLM), such asChatGPT or BERT. Yet, the little existing research also points to the need for reskilling theexisting workforce [17,18], albeit unclear on the broad implications beyond direct developmentand interaction of LLMs. Short- and long-term implications of the use of ChatGPT in allindustries are still unclear [18]. However, due to its analytical nature, it might displace differentpositions than those affected by the use of robotics.Moreover, it is clear through the increased use of information technologies that roles related tothis discipline will start to be part of the building process. For example, the centrality of

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

Conference Session

Curricular Innovations in Computing -2

Collection

2023 ASEE Annual Conference & Exposition

Authors

Lea Wittie, Bucknell University

Tagged Topics

Diversity

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

receive instant feedback about their score but do not have access to thequestion or their answer after they submit it. Students can re-attempt these exam topics infinitetimes; getting a (hopefully) different question each time.Students are free to access their notes and course materials while answering these questions andare encouraged to write and run test code as well. They are allowed to access the Internet ingeneral, however, they are forbidden from using Internet chat sites such as stackoverflow.com orquestion answering sites such as Chegg, CourseHero, or ChatGPT or from communicating withother people using any medium.Exam questions give the students 30 minutes to do problems that would typically take them 5-10minutes on a standard exam

Conference Session

Electrical and Computer Engineering Division (ECE) Poster Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Kenneth A Connor, Rensselaer Polytechnic Institute; Stephen M Goodnick, Arizona State University; Michelle Klein, Electrical and Computer Engineering Dept. Heads Assoc. (ECEDHA); Barry J. Sullivan, Electrical & Computer Engineering Department Heads Assn; John C. Kelly, North Carolina A&T State University (CoE); Pamela Leigh-Mack, Virginia State University; Shiny Abraham, Seattle University; John Janowiak; Sinais Alvarado; Petru Andrei, Florida A&M University - Florida State University; Wayne A Scales, Virginia Polytechnic Institute and State University; Tymia Wilson; Yeimidy Lagunas

Tagged Topics

Diversity

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

not a definitive and exhaustive list, it is a good starting point andcan be modified to suit the specific needs and context of the partnership. (Note that the rubricwas constructed with the assistance of ChatGPT. Putting a collection of related ideas into astandard format, like a rubric, is one of the tasks that AI seems to do well. We share thisinformation when we share the rubric as an incentive for potential collaborators to improve it.)Workshop PlanThe IEC has developed a broad and very challenging vision of enabling MSIs and their students,staff and faculty to more fully become part of and contribute to the ECE enterprise. To realizethis vision, this workshop brought together IEC Core MSI members with the heads of other ECEdepartments

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

Conference Session

Environmental Engineering Division (ENVIRON) Technical Session 4 - Engineering for One Planet & Sustainability Innovation

Collection

2024 ASEE Annual Conference & Exposition

Authors

Cindy Cooper, The Lemelson Foundation; Cynthia Anderson, Alula Consulting; Lynn A. Albers, Hofstra University; John K. Estell, Ohio Northern University; Micah Lande, South Dakota School of Mines and Technology; Bala Maheswaran, Northeastern University

Tagged Topics

Diversity

Tagged Divisions

Environmental Engineering Division (ENVIRON)

Conference Session

COED: AI and ML Topics

Collection

2023 ASEE Annual Conference & Exposition

Authors

Nebojsa I. Jaksic, Colorado State University, Pueblo; Bahaa Ansaf, Colorado State University, Pueblo

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

lives. Thisis especially true now, since the world is in the midst of a number of controversies dealing withbiased data sets for training of neural networks, ChatGPT unfair uses, or the Elon Musk’s call fora moratorium on AI development. Results from this research will be used as preliminary findings while planning large-scale regionalresearch activities related to AI that could be supported by NSF, Amazon Machine LearningUniversity or the Department of Education. A collaborative network consisting of localschoolteachers interested in AI and AI-active university professors will be created to furtherpromote and implement AI in the K-12 curriculum. Partnership modalities with the AI4K12organization will be investigated to improve AI literacy

Conference Session

Experimentation and Laboratory-Oriented Studies Division (ELOS) Technical Session 3: Best of ELOS

Collection

2023 ASEE Annual Conference & Exposition

Authors

Rachel C. Childers, The Ohio State University; Sunny Kwok, The Ohio State University

Tagged Topics

Diversity

Tagged Divisions

Experimentation and Laboratory-Oriented Studies Division (DELOS)

to the question “Was there anything that you would take away fromthis experience and apply to future projects or group work? If so what?” in the survey wasanalyzed and validated in two ways. Salient themes were identified by the authors and thefrequency of those themes were tabulated to count the number of occurrences specific featureswere identified from students. Responses were coded into the following 8 themes:Communication, assigned roles, motivation, lab skills/course content, collaboration/teamwork,leadership, enjoyment, and delegation/group organization. In addition, the responses were inputinto an artificial intelligence natural language processing tool (ChatGPT, OpenAI) to identifythemes from responses in an unbiased manner. This

Conference Session

Engineering Ethics Division (ETHICS) Technical Session_Tuesday June 27, 9:15 - 10:45

Collection

2023 ASEE Annual Conference & Exposition

Authors

Laura Bottomley, North Carolina State University at Raleigh; Cynthia Bauerle; Lisette Esmeralda Torres-Gerald; Carrie Hall

Tagged Topics

Diversity

Tagged Divisions

Engineering Ethics Division (ETHICS)

learning community of the course? Ex. Engage students with personal knowledge that can enhance class activities like students from various origins or countries who can discuss how climate change is affecting their homes YES or NO Are students required to demonstrate self-reflective processes in evaluating engineering in society? Ex. Require students to express and defend opinions on engineering issues in the news on a regular basis, like the effects of ChatGPT on education YES or NO Are there opportunities for students to demonstrate their ability to integrate multiple values into evaluation and decision making in an engineering context? Ex

Conference Session

Curricular Innovations in Computing - 1

Collection

2023 ASEE Annual Conference & Exposition

Authors

Yufang Jin, The University of Texas at San Antonio; Robert Applonie, The University of Texas at San Antonio; Paul E. Morton, The University of Texas at San Antonio; Mason Cole Conkel, Electrical and Computer Engineering, Klesse College of Engineering and Integrated Design, University of Texas at San Antonio; Thuy Khanh Nguyen, University of Texas at San Antonio; Chunjiang Qian, The University of Texas at San Antonio

Tagged Topics

Diversity

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

students might help to gainmeaningful insight from students’ viewpoints to improve the AI certificate program. Finally, thelow number of student samples and institutional and regional effects may also be considered fora complete study in the future.6. AcknowledgmentThis work was funded and supported by the National Science Foundation (#2051113) andUSDOT Transportation Consortium of the South-Central States (TRAN-SET) (# 21-034, and#21-049) to YFJ.References[1] B. D. Lund and T. Wang, "Chatting about ChatGPT: how may AI and GPT impact academia and libraries?," Library Hi Tech News, 2023.[2] R. R. Murphy, Introduction to AI robotics. MIT press, 2019.[3] K. Siau and W. Wang, "Building trust in artificial intelligence, machine learning, and

Conference Session

Track 6: Technical Session 1:Technology Students' Recognition of Algorithmic Data Bias through Role-Play Case Studies

Collection

2024 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Ashish Hingle, George Mason University; Aditya Johri, George Mason University

Tagged Topics

CoNECD Paper Sessions, Diversity

activities' interactive nature. They would muchrather engage in these topics in this format rather than write another essay (this isalso becoming tougher with the commercialization of large language models and XAItools like ChatGPT and Bard).We generally use an iterative design process that brings together real-world examplesof the topic we want to discuss with students. We include articles, publications,videos, and other resources to establish the roles and build a conversation. Someroles are designed not to agree with each other – the values of different perspectivesare set up to foster conversation. Ultimately, we hope to facilitate a conversation anddirect students into recognizing the principles at play

Conference Session

Track 4: Technical Session 5: Using a Summer Bridge Program to Develop a Situational Judgment Inventory: From Year 1 to Year 2

Collection

2024 Collaborative Network for Engineering & Computing Diversity (CoNECD)

Authors

Malini Josiam, Virginia Tech Department of Engineering Education; Walter C. Lee, Virginia Polytechnic Institute and State University

Tagged Topics

CoNECD Paper Sessions, Diversity

level category structure that these options fell intousing ChatGPT and prior research. Categorized Response Developing Options Response Items Situational Judgement Inventory (SJI) 25Finally, we sorted the organized responses into each response option category,making sure that each response option was only one action. Given the varyingdomains of scenarios and relevant responses, some of the scenarios have severalresponse options within the same response option category and/or some responseoption categories are skipped altogether

Collection

ASEE Zone 1 Conference - Spring 2023

Authors

Buket D Barkana, University of Bridgeport; Ioana A. Badara, University of Bridgeport; Navarun Gupta, University of Bridgeport; Junling Hu, University of Bridgeport; Ausit Mahmood, University of Bridgeport

Tagged Topics

Diversity

creating a laboratory course wherestudents learn the applications of AI and get to play and experiment with concepts that they can right away see beingapplied through concepts of simple Calculus and Python programming.Deep Convolution based networks with the Triplet loss were quite successful (e.g., FaceNet) in face recognitionresulting in greater than 99% accuracy on benchmarks such as LFW. With the recent success of Transformer basedNatural Language Processing architectures (e.g., ChatGPT), transformers have been attempted in Computer Visionapplications. They have shown considerable success with better computational efficiency than CNN-basedarchitectures. In this project, we compare the FaceNet and transformer-based architecture for face

Conference Session

Engineering Ethics Division (ETHICS) Technical Session _ Monday June 26, 1:30 - 3:00

Collection

2023 ASEE Annual Conference & Exposition

Authors

Umair Shakir, Virginia Polytechnic Institute and State University; Justin L. Hess, Purdue University at West Lafayette (COE); Matthew James P.E., Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University

Tagged Topics

Diversity

Tagged Divisions

Engineering Ethics Division (ETHICS)

Improving Decisions in Engineering Education Agents and Systems (IDEEAS) Lab, a group that uses multi-modal data to characterize, understand, a ©American Society for Engineering Education, 2023 Pushing Ethics Assessment Forward in Engineering: NLP-Assisted Qualitative Coding of Student ResponsesAbstractRecent headlines have featured large language models (LLMs), like ChatGPT, for their potentialimpacts throughout society. These headlines often focus on educational impacts and policies. Weposit that LLMs have the potential to improve instructional approaches in engineering education.Thus, we argue that as an engineering education community, we should aim to leverage LLMs tohelp resolve

Conference Session

Multidisciplinary Engineering Division (MULTI) Technical Session 6

Collection

2023 ASEE Annual Conference & Exposition

Authors

Darcie Christensen, Minnesota State University, Mankato; Lauren Singelmann, Minnesota State University, Mankato; Rob Sleezer, Virginia Tech; Emilie A. Siverling, Minnesota State University, Mankato

Tagged Topics

Diversity

Tagged Divisions

Multidisciplinary Engineering Division (MULTI)

more learner-centered and focusedon formative feedback rather than summative evaluation [1].As the world of technology continues to advance, a shift and embracement of new assessmentmethods is appropriate and necessary. For example, as of early 2022, the New York Timesreported that universities are now having to change the way they are teaching and assessingstudents because of the widespread availability of A.I. Chatbots such as ChatGPT [12]. WithinIE at Minnesota State University, Mankato, differential methods of assessment have beenemployed for over a decade and we want to share our experiences with oral exams to supportothers in embracing the changing world, better preparing engineering students for their futurepositions.Overview of

Conference Session

Educational Research and Methods Division (ERM) Technical Session 18

Collection

2024 ASEE Annual Conference & Exposition

Authors

Navarun Gupta, University of Bridgeport; Junling Hu, University of Bridgeport; Ioana A. Badara, Post University; Buket D. Barkana, The University of Akron; Deana A. DiLuggo, University of Bridgeport

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods Division (ERM)

they can right away see being applied through concepts ofsimple Calculus and Python programming.Deep Convolution-based networks with the Triplet loss were quite successful (e.g., FaceNet) inface recognition, resulting in greater than 99% accuracy on benchmarks such as LFW. With therecent success of transformer-based Natural Language Processing architectures (e.g., ChatGPT),transformers have been attempted in Computer Vision applications. They have shown considerablesuccess with better computational efficiency than CNN-based architectures. In this project, wecompared the FaceNet and transformer-based architecture for face recognition. We also providedan insightful understanding of the face recognition process, its limitations, and future

Conference Session

College Industry Partnerships Division (CIP) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Chun Kit Chan, The University of Hong Kong; H.H. Cheung, University of Hong Kong; Match Ko, University of Hong Kong; Chun Kit Chui, University of Hong Kong; LEI YANG, The University of Hong Kong

Tagged Topics

Diversity

Tagged Divisions

College Industry Partnerships Division (CIP)

University of Hong Kong, "InnoShow," in Tam Wing Fan Innovation Wing 2023. [Online]. Available: https://innoacademy.engg.hku.hk/innoshow/[24] Innovation Academy, Faculty of Engineering, the University of Hong Kong, "From Ground to Air," in Tam Wing Fan Innovation Wing 2023. [Online]. Available: https://innoacademy.engg.hku.hk/20231106_workshop/[25] Innovation Academy, Faculty of Engineering, the University of Hong Kong, "Build Your IoT Smark Clock," in Tam Wing Fan Innovation Wing 2023. [Online]. Available: https://innoacademy.engg.hku.hk/iotclock/[26] Innovation Academy, Faculty of Engineering, the University of Hong Kong, "Unleash Creativity with Generative AI through Open AI Engine and ChatGPT - Build Your Personalized