Conference Session

Educational Research and Methods Division (ERM) Technical Session 22

Collection

2024 ASEE Annual Conference & Exposition

Authors

Dhruv Gambhir, Nanyang Technological University; Yifan Xie, University College London; Ibrahim H. Yeter, Nanyang Technological University; Junaid Qadir, Qatar University; Andy Khong, Nanyang Technological University

Tagged Divisions

Educational Research and Methods Division (ERM)

learning analytics, acoustic signal processing, and recommendation systems. ©American Society for Engineering Education, 2024 Perceptions of Engineering College Instructors and Their Students Towards Generative Artificial Intelligence (GenAI) Tools: A Preliminary Qualitative AnalysisAbstractGenAI tools, such as ChatGPT, have gained significant traction in engineering colleges and arerevolutionizing how students approach each assignment and project. However, integrating theminto the education system introduces challenges to the core assessment criteria and the traditionalgrading system that has been used in these institutions for decades. To achieve a betterunderstanding of the

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ahmed Ashraf Butt, Carnegie Mellon University; Eesha tur razia babar, University of California, Irvine; Muhsin Menekse, Purdue University, West Lafayette; Ali Alhaddad, Purdue University, West Lafayette

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

Comparative Analysis of Large Language Models and NLP Algorithms to enhance Student Reflection SummariesAbstractThe advent of state-of-the-art large language models has led to remarkable progress incondensing enormous amounts of information into concise and coherent summaries, benefitingfields like education, health, and public policy, etc. This study contributes to the current effort byinvestigating two NLP approaches’ effectiveness in summarizing students’ reflection text. Thisapproach includes Natural Language Processing (NLP) algorithms customized for summarizingstudents’ reflections and ChatGPT, a state-of-the-art large language model. To conduct the study,we used the CourseMIRROR application to collect students’ reflections from

Conference Session

Architectural Engineering Division (ARCHE) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Alexander Campbell, Oklahoma State University

Tagged Divisions

Architectural Engineering Division (ARCHE)

aspreadsheet in less time by utilizing artificial intelligence (AI)?This paper will discuss incorporating the use of AI Chatbots, such as ChatGPT, Claude 3, andGemini (formerly known as Bard), into an advanced steel design course. The course is centeredaround a semester long project where Architectural Engineering students design and analyze a multi-story steel structure. Students throughout the semester will use an AI Chatbot to create spreadsheetsby asking it to develop Visual Basic for Applications (VBA) code that can then be inserted into Excelspreadsheets. The resulting spreadsheet will be compared to hand-calculations and RISA output todetermine the accuracy of the VBA code and error reduction produced by AI Chatbots.IntroductionIt is a common

Conference Session

Design in Engineering Education Division (DEED) - Use of Technology in Design Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

David Prohofsky, South Dakota School of Mines and Technology; Micah Lande, South Dakota School of Mines and Technology

Tagged Divisions

Design in Engineering Education Division (DEED)

and making processes to their work. He is interested in the intersection of designerly epistemic identities and vocational pathways. Dr. Lande received his B.S. in Engineering (Product Design), M.A. in Education (Learning, Design and Technology) and Ph.D. in Mechanical Engineering (Design Education) from Stanford University. ©American Society for Engineering Education, 2024 Affordances of Large Language Models in Design ActivityAbstractLarge language models and AI tools such as ChatGPT have possible benefits within designprocess and design activity across design courses in higher education. With the advent and rise inuse of large language models (LLM’s) we seek to better understand the

Conference Session

The Best of Computers in Education Division (COED)

Collection

2024 ASEE Annual Conference & Exposition

Authors

Yutong Ai, University of Michigan; Maya Baveja, University of Michigan; Akanksha Girdhar, University of Michigan; Melina O'Dell, University of Michigan; Andrew Deorio, University of Michigan

Tagged Divisions

Computers in Education Division (COED)

. The overall survey data indicatedhigh rates of correctness and helpfulness in the Bot responses. We found that hallucination wasnot common, and most incorrect responses were identifiable by students. The Bot also performedbetter than general purpose bots for project-specific help.Our experience can provide insights for faculty using GenAI to assist students in their courses. Acustomized chatbot can be helpful to students and augment traditional course resources.2 Introduction and Related WorkGenerative AI tools, such as ChatGPT [1], have become increasingly prevalent for studentsthroughout the past year [2][3]. A study has shown that the use of ChatGPT in education has had apositive impact on students’ learning and educators’ teaching, with

Conference Session

Engineering Libraries Division (ELD) Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Uri Feldman, Wentworth Institute of Technology; Callie Cherry, Wentworth Institute of Technology

Tagged Divisions

Engineering Libraries Division (ELD)

grown its user base exponentially. In particular, largelanguage models in the form of “chatbots” have become widely popular across industries anddemographics. In the first two months since its release in November 2022, OpenAI’s ChatGPT,the most popular AI chatbot surpassed 100 million users worldwide; as of May 2023, over halfof Americans are familiar with the concept of AI chatbots [5]. This popularity is changing theway that information is created and shared, especially among young people and more highlyeducated people. According to Pew Research Center, the groups most likely to know about anduse these chatbots are adults ages 18-29, and likelihood of use increases with education level [5].This poses both a unique challenge – and opportunity

Conference Session

Engineering Management Division (EMD) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Renee Rottner, University of California, Santa Barbara

Tagged Divisions

Engineering Management Division (EMD)

Management Science and Engineering from Stanford University, and her Ph.D. in Management from UC Irvine. ©American Society for Engineering Education, 2024 Iterative Learning: Using AI-bots in Negotiation TrainingNegotiation skills are essential in management education and in engineering practice. Traditionalteaching methods, centered around role-playing activities. have often struggled to fully engagestudents or provide the personalized feedback necessary for mastering such a complex skill set.To addressing this pedagogical gap, I developed AdVentures with chatGPT [1] by leveragingartificial intelligence to create a dynamic, interactive learning experience that adapts to eachstudent's needs and performance

Conference Session

Using technology in engineering ethics education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ronald P. Uhlig, National University; Shatha Jawad, National University; Phillip Zamora, National University; Elizabeth Niven, National University

Tagged Divisions

Engineering Ethics Division (ETHICS)

. It was concluded that it depended onspecific circumstances, but it was noted that students might potentially undermine their ownlearning by relying on tools like ChatGPT to answer questions and compose papers. This paperaddresses how to enable students to use these tools in a way that students are not cheatingthemselves.The introduction of calculators into the classroom in the early 1970s stimulated discussion onethical use of technology in teaching. A similar revolution is occurring with the introduction ofGenerative Artificial Intelligence tools such as ChatGPT, Bard (now Gemini), and many others,and a similar set of opportunities is emerging. A key issue is how to use GenAI toolsconstructively to encourage critical thinking in the solving

Conference Session

Technical Proficiency and Cybersecurity Awareness in ECE Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Doug W. Jacobson, Iowa State University of Science and Technology

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

tools that are authoritativeand adaptable to the needs of different learners.In the spring of 2024, we held a CyberEd-Expo where student ambassadors presented materialsthey had developed to the CyberEd group for feedback. They first presented a plan in the fall of2023 of what types of materials and lessons they were planning, and we provided initialfeedback. The goal is to make these materials available to other ambassadors.The CyberEd group utilized ChatGPT to develop the framework and some content for theambassador program materials, as described above. Below is a description of how ChatGPT wasused for the various parts of the program. I also want to acknowledge that ChatGPT helpedcreate the description below of how ChatGPT supports the

Conference Session

First-Year Programs Division Technical Session 2: AI, Computation, and Electronics

Collection

2024 ASEE Annual Conference & Exposition

Authors

Lakshmy Mohandas, Purdue University ; Nathan Mentzer, Purdue University

Tagged Divisions

First-Year Programs Division (FYP)

, research focusing on the student experience is critical. As universities grapple with AIpolicies and practices, this study emphasizes the need to include student voices. Findings providekey insights that can inform faculty pedagogy, course design, campus policies, and strategicintegration of AI. Centering student perspectives allows for human-AI collaboration in educationthat maintains academic integrity while supporting creativity and learning.IntroductionArtificial intelligence (AI) tools like ChatGPT can produce remarkably human-like text. Astechnological barriers to developing advanced conversational AI rapidly diminish, thesetechnologies have disseminated across society with explosive growth anticipated in the comingyears. However, concerns

Conference Session

Software Engineering Division (SWED) Technical Session #2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ben Arie Tanay, Purdue Engineering Education; Lexy Chiwete Arinze, Purdue University, West Lafayette; Siddhant Sanjay Joshi, Purdue University, West Lafayette; Kirsten A. Davis, Purdue University, West Lafayette; James C Davis, Purdue University, West Lafayette

Tagged Topics

Diversity

Tagged Divisions

Software Engineering Division (SWED)

) have begun to influence software engineeringpractice since the public release of GitHub's Copilot and OpenAI's ChatGPT in 2022. Tools builton LLM technology could revolutionize the way software engineering is practiced, offeringinteractive “assistants” that can answer questions and prototype software. It falls to softwareengineering educators to teach future software engineers how to use such tools well, byincorporating them into their pedagogy.While some institutions have banned ChatGPT, other institutions have opted to issue guidelinesfor its use. Additionally, researchers have proposed strategies to address potential issues in theeducational and professional use of LLMs. As of yet, there have been few studies that report onthe use of LLMs

Conference Session

Educational Research and Methods Division (ERM) Technical Session 19

Collection

2024 ASEE Annual Conference & Exposition

Authors

Wei Lu, Texas A&M University; Behbood Ben Zoghi P.E., Texas A&M University

Tagged Divisions

Educational Research and Methods Division (ERM)

Consortium and teaches application of emerging technologies. Over the past 35 years ©American Society for Engineering Education, 2024ASEE 2024 Educational Research and Methods (ERM) Division Using Generative AI for A Graduate Level Capstone Course Design -A Case Study Abstract This WIP paper aims at exploring the pros and cons of using the newly released,advanced generative artificial intelligence (AI) tool, ChatGPT, to design the curriculum for aCapstone course, which is completed towards the end of the Master of Engineering TechnicalManagement (METM), a 21-month online graduate program for working professionals in theengineering

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ibukun Samuel Osunbunmi, Pennsylvania State University; Stephanie Cutler, Pennsylvania State University; Viyon Dansu, Florida International University; Yashin Brijmohan, University of Nebraska, Lincoln; Bolaji Ruth Bamidele, Utah State University; Abasiafak Ndifreke Udosen, Purdue University, West Lafayette; Lexy Chiwete Arinze, Purdue University, West Lafayette; Adurangba Victor Oje, University of Georgia; Deborah Moyaki, University of Georgia; Melissa J Hicks, Pennsylvania State University; Bono Po-Jen Shih, Pennsylvania State University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

Boundaries of Engineering Education.AbstractGenerative artificial intelligence (GAI) has long been used across various fields; however, itsusage in engineering education has been limited. Some areas where GAI tools have beenimplemented in education include intelligent tutoring, assessment, predicting, curriculum design,and personalized student learning. The recent proliferation of CHATGPT and other GAI toolspresents limitless possibilities for transforming engineering pedagogy and assessment. At thesame time, there are challenges associated with implementation. Consequently, there is a need toconduct an empirical study to evaluate these tools' strengths, limitations, and challenges tohighlight potential opportunities for their application in

Conference Session

Educational Research and Methods Division (ERM) Technical Session 19

Collection

2024 ASEE Annual Conference & Exposition

Authors

Hudson James Harris, University of Oklahoma; Javeed Kittur, University of Oklahoma

Tagged Divisions

Educational Research and Methods Division (ERM)

: Articles pertaining exclusively to the teaching of deep learning algorithms(III) The articles that made it to the final phase were reviewed in detail. (IV) This information wasconsolidated, synthesized, and examined to find the emergent themes.Keywords: ChatGPT, engineering education, GenAI, large language models, undergraduateengineeringIntroductionThe dawn of the Fourth Industrial Revolution heralds an unprecedented era of technologicalconvergence, where the integration of digital, physical, and biological systems becomes a definingcharacteristic of societal and economic transformations. Artificial Intelligence (AI), especiallygenerative AI, stands at the vanguard of this revolution, driving innovations that blur the traditionalboundaries across

Conference Session

Computing and Information Technology Division (CIT) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Barry M. Lunt, Brigham Young University; Mudasser Fraz Wyne, National University; David A Wood, Brigham Young University

Tagged Divisions

Computing and Information Technology Division (CIT)

. This paper looks at these 427 papers as a whole, providing descriptive statistics, givingthe top institutions and authors that have contributed to these papers, and providing informationregarding the impact of the top ten papers, as measured by their citations and downloads. We havealso used the ChatGPT version 4.0 to provide categories for the 427 papers, providing insight intothe most popular topics for papers in the CIT division.Introduction The American Society for Engineering and Education (ASEE) Computing & InformationTechnology (CIT) Division's existence spans several decades, and it continues to be a stalwartadvocate for numerous research papers and sessions featured at the ASEE Annual Conference andExposition. The ability

Conference Session

Computing and Information Technology Division (CIT) Technical Session 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Venkata Alekhya Kusam, University of Michigan, Dearborn; Larnell Moore, University of Michigan, Dearborn; Summit Shrestha, University of Michigan, Dearborn; Zheng Song, University of Michigan, Dearborn; Jin Lu, University of Georgia; Qiang Zhu, University of Michigan, Dearborn

Tagged Divisions

Computing and Information Technology Division (CIT)

2 School of Computing, University of GeorgiaAbstractProject-Based Learning (PBL) is a pedagogical method that combines theory and practice byinvolving students in real-world challenges. Continuous feedback is crucial in PBL, guidingstudents to improve their methods and foster progressive thinking. However, PBL faceschallenges in widespread adoption due to the time and expertise needed for effective feedback,especially with increasing student numbers. This paper presents a novel approach usingGenerative AI, specifically an enhanced ChatGPT, to provide effective PBL feedback. For anundergraduate Web Technology course, we integrated three methods: 1) fine-tuning ChatGPTwith feedback from various sources; 2) using additional course-specific

Conference Session

NSF Grantees Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ahatsham Hayat, University of Nebraska, Lincoln; Sharif Wayne Akil, University of Nebraska, Lincoln; Helen Martinez, University of Nebraska, Lincoln; Bilal Khan, Lehigh University; Mohammad Rashedul Hasan, University of Nebraska, Lincoln

Tagged Topics

Diversity, NSF Grantees Poster Session

ChatGPT and Google’s Gemini, for the early prediction of studentperformance in STEM education, circumventing the need for extensive data collection orspecialized model training. Utilizing the intrinsic capabilities of these pre-trained LLMs, wedevelop a cost-efficient, training-free strategy for forecasting end-of-semester outcomes based oninitial academic indicators. Our research investigates the efficacy of these LLMs in zero-shotlearning scenarios, focusing on their ability to forecast academic outcomes from minimal input.By incorporating diverse data elements, including students’ background, cognitive, andnon-cognitive factors, we aim to enhance the models’ zero-shot forecasting accuracy. Ourempirical studies on data from first-year college

Conference Session

First-Year Programs Division Technical Session 2: AI, Computation, and Electronics

Collection

2024 ASEE Annual Conference & Exposition

Authors

Yume Menghe Xu, Tufts University; Ethan E. Danahy, Tufts University; William Church

Tagged Divisions

First-Year Programs Division (FYP)

and educational researchers todesign venues that empower students to have ownership in constructing their views of generativeAI as engineers-to-be.Introduction “I didn’t realize how helpful AI could be and how it could be used in an education setting without it seeming like a way to cheat. At the beginning of the semester, the fact that we were told to use AI was crazy to me, but now I can’t see how the class would’ve run without it.”This excerpt from an exit survey was written by a first-year undergraduate student whoparticipated in an introductory engineering course re-designed to support students' tinkering withgenerative Artificial Intelligence (AI).As the use of AI tools such as OpenAI’s ChatGPT and DALL-E grows more

Conference Session

Civil Engineering Division (CIVIL) Technical Session - Instructional Technology 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Joel Lanning, University of California, Irvine; Matthew W Roberts, Southern Utah University; Brandon K Wiggins, Southern Utah University

Tagged Divisions

Civil Engineering Division (CIVIL)

structural content delivered to all students. Finally, schools within the same system with identical course descriptions were treated as one course and were not counted twice in the results. Based on these criteria, 264 distinct course descriptions were analyzed for this study. 2. Selecting Common Course Topics Using the OpenAI API The 264 course descriptions were used as input to the gpt-3.5-turbo model [18] (ChatGPT) to identify common topics such as influence lines, moment distribution, etc. The first 20 course descriptions were analyzed by hand to verify that the 15 common topics identified by ChatGPT were helpful in identifying the content taught in the courses. Some refinements to the list of

Conference Session

DSA Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

Isil Anakok, Virginia Polytechnic Institute and State University; Kai Jun Chew, Embry-Riddle Aeronautical University, Daytona Beach; Holly M Matusovich, Virginia Polytechnic Institute and State University; Andrew Katz, Virginia Polytechnic Institute and State University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

ondesigning assessments, and communication strategies with students. The study ultimatelyadvocated for the inclusion of GAI in the assessment landscape, calling for the development ofGAI assessment literacy among instructors [10]. A recent systematic literature review also foundthe need for new skills, interdisciplinary teaching methods, and policy implications, highlightingGAI's transformative impact on school education that aligned with their findings in theirliterature review [2]. Following up on the review, Chiu [1] conducted a study to exploreperceptions of AI from the teachers’ point of view and found that tools such as ChatGPT haveinfluenced schools, with the viewpoints of teachers being particularly significant, withconcerning elements such

Conference Session

Faculty Development Division (FDD) Technical Session 8

Collection

2024 ASEE Annual Conference & Exposition

Authors

Michaela Harper, Utah State University; Cassandra McCall, Utah State University

Tagged Divisions

Faculty Development Division (FDD)

, 2024 Faculty perspectives on undergraduate use of Generative Artificial Intelligence (GAI) assistance: A work-in-progressAbstractThis work-in-progress paper explores faculty perspectives regarding student use of GenerativeArtificial Intelligence (GAI) assistance tools, such as ChatGPT, to complete engineeringcoursework. A common debate in engineering and computer science exists about how facultyshould address GAI tools (i.e., prevent their usage in order to maintain academic integrity, teachstudents the new technologies, or establish regulatory guidelines in higher education). WhileGAI continues to disrupt traditional educational paradigms, its full impacts on teaching andlearning are currently unknown. Such work is

Conference Session

Principal Skinner's Secrets: Cultivating STEM in Remote Locations, Steamed Hams!

Collection

2024 ASEE Annual Conference & Exposition

Authors

Monsuru O Ramoni, Navajo Technical University; Calsey T Nez, Navajo Technical University

Tagged Topics

Diversity

Tagged Divisions

Pre-College Engineering Education Division (PCEE)

, 2022, and 2023. A total of 78 students and 3 teachers participated in the program during thistime period.Each team of students submits a project report at the end of the spring semester as part of the programrequirements.3.3 Data Collection Instrument(s)For this study, a total of 10 reports were randomly selected from the participants' submissions. Thesereports were analyzed using Open ChatGPT to explore the students' experiences in the Dual-CreditEngineering program.Open ChatGPT was utilized to conduct a thematic analysis of the reports. Each report was inputted intoOpen ChatGPT, which generated codes based on its content. These codes were then combined to formoverall themes across all 10 reports.The procedure for thematic analysis with Open

Conference Session

Unique Pedagogies for Mechanics Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Marguerite Matherne, Northeastern University

Tagged Topics

Diversity

Tagged Divisions

Mechanics Division (MECHS)

objectives on theunderstand level of Bloom’s taxonomy and multiple-choice questions for learning objectives onthe analyze level are shown to moderately achieve this goal. The feedback loop between studentsand instructor was instrumental in determining how to best use class time to support studentlearning. Recommendations for best practices, including how ChatGPT can be leveraged toquickly summarize student responses, based on the instructor’s experience and student feedback,are given.IntroductionStudies have shown that students who read assigned textbook sections before coming to classfind it beneficial for their learning. They have also shown that today’s engineering studentsrarely read the textbook [1]. Just-In-Time-Teaching (JiTT) is a pedagogy

Conference Session

Faculty Development Division (FDD) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Helen Choi, University of Southern California

Tagged Divisions

Faculty Development Division (FDD)

Paper ID #41793WIP: Developing a Framework for Ethical Integration of Technology in InstructionProf. Helen Choi, University of Southern California Helen Choi is a Senior Lecturer in the Engineering in Society Program at the USC Viterbi School of Engineering. She teaches courses in writing, communication, and information literacy. ©American Society for Engineering Education, 2024 Work in progress: Developing a framework for ethical integration of technology in instructionBackgroundIn a university setting where the adoption of large language models (LLMs) like ChatGPT seemslike a

Conference Session

Panel: AI and Engineering Technology Education: What, Why, How?

Collection

2024 ASEE Annual Conference & Exposition

Authors

Meenakshi Narayan, Miami University; Lokesh Kumar Saharan, Gannon University

Tagged Topics

Diversity

Tagged Divisions

Engineering Technology Division (ETD)

Reshaping Engineering Technology Education: Fostering Critical Thinking through Open-Ended Problems in the Era of Generative AIAbstractAcademic integrity breaches and plagiarism existed long before the rise of Generative Artificialintelligence (G-AI), where students used paid online tutoring platforms like Chegg to obtain helpwith homework assignments, take-home exams, and course projects. Additionally, G-AIplatforms such as ChatGPT provide students with immediate support in understanding conceptsand improving problem-solving abilities. However, it also opens up possibilities for students toimproperly use the technology for homework and exams. This necessitates a revision in howeducators design curricula and

Conference Session

Aerospace Division (AERO) Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Tim Drake, Saint Louis University; Srikanth Gururajan, Saint Louis University

Tagged Divisions

Aerospace Division (AERO)

) classes, they are taught from the perspective of developingand executing algorithms, and there are no classes to teach the actual building of a computingcluster. This is another prime example of our need to learn outside the classroom to accomplishour goals. As most students do, we turned to Artificial Intelligence (AI)/ChatGPT [6] for help – tobe used as an interpreter or editor rather than a coder.Following a tutorial from a website [10], I learned the basics of setting up a multiple-node clusteron Ubuntu. I checked that each PC had adequate RAM, a hard drive, and a simple graphics card.The cluster hardware consists of 20 desktops, each with an Intel i7-4790 quad-core 3.60 GHzprocessor and 16GB of RAM, running Ubuntu 22.04.3 LTS connected to a

Conference Session

Industrial Engineering Division (IND) Technical Session 3

Collection

2024 ASEE Annual Conference & Exposition

Authors

Enas Aref, Western Michigan University

Tagged Divisions

Industrial Engineering Division (IND)

McKinsey& Company. ChatGPT, the infamous creation by OpenAI, unleashed theaccessibility of Gen AI to everyone that has access to the internet. ChatGPT and similar platforms likeGoogle-Bard and Claude 2.0 are classified as a Large Language Model (LLM). Deep learning neuralnetwork, a type of machine learning, is the algorithm used to develop those LLM models [25]. Theultimate objective of Gen AI models is “to generate human-like content in response to complex andvaried prompts” [24]. Gen AI capabilities are extensive and are continuously growing and improving.Gen AI is capable of answering questions, solving difficult problems, and in some models like GPT-4 canexhibit human-level performance on some academic exams [26]. These capabilities paired

Conference Session

Engineering Management Division (EMD) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sakhi Aggrawal, Purdue University ; Paul J. Thomas

Tagged Topics

Diversity

Tagged Divisions

Engineering Management Division (EMD)

quantitative data.Concurrently, qualitative data was thematically analyzed to gain insights into usage andperceptions surrounding AI.Results: The study revealed a growing trend among project management professionals inleveraging AI tools for a variety of tasks, including project planning, task assignment, tracking,and crafting emails, reports, and presentations. A strong correlation was observed betweenfamiliarity with ChatGPT and its likely usage in project management tasks. While someparticipants found AI tools convenient and efficient, they were frustrated with potentialinaccuracies and the need for specific input prompts. Overall, industry professionalsdemonstrated the usage of AI in project management, with a notable emphasis on taskautomation

Conference Session

DSA Technical Session 8

Collection

2024 ASEE Annual Conference & Exposition

Authors

Paula Francisca Larrondo, Queen's University; Brian M Frank P.Eng., Queen's University; Julian Ortiz, Queen's University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

(NLP) technologies, through the use of artificialintelligence (AI) agents and Large Language Models (LLM), have already provided significantadvantages in the holistic assessment of high-order features such as argumentation, use ofevidence or scientific thinking [4-6]. With the evolution of Automated Feedback Systems (AFS)[7-9] and, more recently, the release of Open AI’s ChatGPT, LLMs have become commonplacein higher education among students and instructors [10, 11]. The emergence of LLMs in higherand secondary education has triggered an influx of publications on the opportunities andchallenges of incorporating these technologies in instruction and evaluation [10, 12, 13].However, the unique nature of engineering design problems, characterized

Conference Session

Technological and Engineering Literacy/Philosophy of Engineering Division (TELPhE) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Steffen Peuker, California Polytechnic State University, San Luis Obispo

Tagged Divisions

Technological and Engineering Literacy/Philosophy of Engineering Division (TELPhE)

the subject and facilitates faculty learning communities and is the co-author of ”Studying Engineering – A Road Map to a Rewarding Career”. ©American Society for Engineering Education, 2024 Evaluation of the Utilization of Generative Artificial Intelligence Tools among First-Year Mechanical Engineering StudentsAbstractGenerative artificial intelligence tools, such as ChatGPT, are freely available to anyone,including college students. Some perceive these tools as a game changer for higher educationbecause they can enhance student learning experiences in various ways. The integration ofgenerative AI tools in higher education has the potential to revolutionize teaching and learning