Conference Session

Multidisciplinary Engineering Division (MULTI) Technical Session 9

Collection

2024 ASEE Annual Conference & Exposition

Authors

Rackan Sami Mansour, Texas A&M University at Qatar; Osama Desouky, Texas A&M University at Qatar; Marwa AbdelGawad, Texas A&M University at Qatar

Tagged Divisions

Multidisciplinary Engineering Division (MULTI)

evaluation methodologies identified from the literature. These methodologies focus ontools for assessing the effectiveness of AI-generated educational content. Drawing upon insightsfrom an investigation into the application of AI in educational settings, a framework for evaluatingthe quality and pedagogical value of AI-generated assessments, like MCQs and case studies, isproposed [2]. These tools are crucial for refining AI-generated content to meet the curriculum'sspecific needs and the diverse learning profiles of students in material science education, validatingthe utility and enhancing the effectiveness of AI-generated materials.The unveiling of AI-powered tools like ChatGPT has sparked considerable debate regarding theirimpact on the

Conference Session

Engineering Management Division (EMD) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Raymond L. Smith III, East Carolina University; Henry Lester, University of Dayton

Tagged Divisions

Engineering Management Division (EMD)

GenerativeAdversarial Networks (GANs) by Ian Goodfellow, which set the stage for rapid growth ingenerative models like Variational Autoencoders (VAEs), transformers, and diffusion models,culminating in the creation of versatile foundation models and tools for various applications [5].Figure 1: The evolution timeline for generative AI technology [3], [4].At the heart of generative AI's evolution is the development of large language models (LLMs),such as ChatGPT by OpenAI, Bard by Google, and Bing Chat and Copilot by Microsoft. Thesemodels are trained on vast datasets, enabling them to understand and generate human-like textacross various languages and contexts. LLMs can perform a multitude of tasks, including writingessays, summarizing texts, translating

Conference Session

Engineering Libraries Division (ELD) Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Mark Chalmers, University of Cincinnati; Aja Rachel Bettencourt-Mccarthy, University of Cincinnati

Tagged Divisions

Engineering Libraries Division (ELD)

instruction andsupport.With the release of ChatGPT in November 2022, generative artificial intelligence exploded inpopularity [14] and raised the question of whether this tool could be leveraged by researchers toassist with data extraction and formulation. Although the tool has potential to change the natureof work, research, and education [15] much of its practical utility in academic libraries remainsunderexplored, especially in the multimodal space.The following research study aims to answer two interrelated questions: what do the citationpatterns of Mechanical Engineering Technology (MET) capstone students reveal about theirinformation behavior and can new AI technologies assist researchers in analyzing these citationdata?Since 2017, librarians

Conference Session

Spotlight on Diverse Learners

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sung Je Bang, Texas A&M University; Saira Anwar, Texas A and M University

Tagged Divisions

Computers in Education Division (COED)

, interrogative, imperative, exclamative, andinvalid.Figure 1 provides the illustrated design of the model. Fig. 1. Sentence type detection model.DatasetThe dataset used to test this model contains 500 sentences, all generated by ChatGPT, an NLP-powered chatbot [21]. Every sentence within the dataset has been verified to be correctlyclassified as its respective type of sentence. All sentences were designed to be simple, with nocompound or complex sentences. Out of the 500 sentences, 100 sentences were simpledeclarative sentences, 100 sentences were interrogative, 100 were imperative, and 100 wereexclamative. The last 100 sentences were invalid, incomplete sentences that were none of thefour types of sentences. The created

Conference Session

ML and Generative AI Tools and Policies

Collection

2024 ASEE Annual Conference & Exposition

Authors

Alyson G. Eggleston, Pennsylvania State University; Robert J. Rabb P.E., Pennsylvania State University

Tagged Divisions

Computers in Education Division (COED)

papers may be subject tohigher standards of review and scrutiny, however, due to the propensity for false or misleadinginformation to appear in LLMs. Given that higher bar, some may be tempted to not provideattribution to AI-assisted technical writing. LLM watermarking, a process whereby resultingsyntactic patterns in AI-generated text mathematically ‘signal’ an AI source (as opposed to ahuman source) have been embedded in GPT-4 and other LLMs. These so-called watermarksallow for ‘detectors’ to provide the statistical likelihood of AI use. Some examples sourced fromindustry, academia, and students follow: 1) GPT-2 Output Detector [23]: (From Open AI, the makers of ChatGPT) Claims a detection rate of 95% for machine-generated text using

Conference Session

Engineering Libraries Division (ELD) Technical Session 4

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sarah G. Park, University of Illinois at Urbana - Champaign; Monica Carroll, University of Illinois at Urbana - Champaign; Lucy Marie Alice Esteve, Duke University; Karnika Singh, Duke University

Tagged Divisions

Engineering Libraries Division (ELD)

one's regularexpertise (White, 2009). This process of digesting a body of text and identifying patterns seemsideally suited to automation. In 2009, Ananiadou et al., [18] discussed using text mining toextract terms and expand queries. Text mining applies statistical analysis to a specific body oftext to identify patterns, including associated terms. Natural language processing (NLP) is aclosely related concept where computer programs (i.e., machine learning) extract and utilizethese patterns on unstructured text to aid understanding. NLP is a field that interacts withartificial intelligence (AI) and employs machine learning (ML) techniques. ChatGPT is an AIapplication that leverages NLP principles to understand user inputs and generate

Conference Session

Charting Inclusivity: Advancing Diversity, Equity, and Technology in Engineering and Computing Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Clay Walker, University of Michigan

Tagged Topics

Diversity

Tagged Divisions

Culture & Social Justice in Education Division (EQUITY), Equity

technology, but also reported theoutputs generated by the algorithm were not sophisticated enough to be useful for completingcoursework. The question of sophistication is difficult to pin down due to the rapid developmentof the technology, for within the first year of public access, the power of widely availablecommercial platforms like ChatGPT have continued to develop in power and sophistication withthe problems of hallucination and accuracy diminishing as many of the algorithms now haveaccess to the internet, thus further edifying the outputs generated by the AI.Despite these nascent discussions of student impacts, one issue missing from conversationsaround GenAI are the impacts they are likely going to have on how students develop

Conference Session

Software Engineering Division (SWED) Technical Session #2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Maura Lyons, Codio; Elise Deitrick, Codio; Joshua Richard Coughlin Stowell Ball, Codio

Tagged Topics

Diversity

Tagged Divisions

Software Engineering Division (SWED)

work.Notably, students who were taught how AI works had significantly different views on AI tools’impact on academic integrity concerns.Computing students’ use of Generative AI is growing, and thoughts on academic integrity are farfrom decided – but there does seem to be an opportunity to teach students the variety of ways itcan be used effectively for programming tasks.IntroductionChatGPT, a Generative AI product developed by OpenAI, was released in November 2022 andalmost immediately, its popularity began to surge worldwide, as illustrated by its steep increaseas a search term on Google. Teachers and administrators took notice – “‘plagiarism’ was rankedin two out of the top five related search queries alongside ‘ChatGPT’” [1]. The popularization

Conference Session

Educational Research and Methods Division (ERM) Technical Session 19

Collection

2024 ASEE Annual Conference & Exposition

Authors

Trini Balart, Texas A&M University; Jorge Baier, Pontificia Universidad Católica de Chile; Catalina Cortazar, Pontificia Universidad Católica de Chile; Kristi J. Shryock, Texas A&M University

Tagged Divisions

Educational Research and Methods Division (ERM)

it and discussing whether working on this problem could induce them to Flow. Thedesign of this activity was based on the relationships between identification of skills (e.g.,[10]) and flow state (e.g, [11]) in the development of a sense of purpose in life. Finally there was an interaction with ChatGPT, where students had to use it tobrainstorm how they could apply their skills to each of the three global challenges listed.They included screenshots of these interactions in their presentation, and critically analyzedthe answers given by ChatGPT, expressing their agreement or disagreement and suggestingimprovements based on their criteria, preferences and common sense.Purpose in Life - Short Form (PIL - SF) Questionnaire This

Conference Session

Civil Engineering Division (CIVIL) Technical Session - Instructional Technology 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Mary Kay Camarillo P.E., University of the Pacific; Luke S. Lee P.E., University of the Pacific; Ciara Swan MFA-W, University of the Pacific

Tagged Divisions

Civil Engineering Division (CIVIL)

theSCOPUS database using the query [“artificial intelligence” OR AI] indicates that annualpublications on AI have increased by almost an order of magnitude from 2004 to 2023. Therelease of ChatGPT by OpenAI in November 2022 and then Google’s release of Bard in March2023, along with other similar chatbots, has resulted in more direct access to AI tools. Despitethe accessibility of tools such as ChatGPT, the use of generative AI is variable among differentpopulations and industries [1, 2].The influence of AI has extended to civil engineering although adoption into professionalpractice appears cautiously slow [3, 4]. Available AI models are well-suited for civil engineeringapplications [3]. In scientific literature, there are many examples of AI and

Conference Session

NSF Grantees Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Yanxia Jia, Arcadia University; Tiantian Wang, The University of Texas at San Antonio; Chaomei Chen, Drexel University; Yu-Fang Jin, The University of Texas at San Antonio

Tagged Topics

NSF Grantees Poster Session

grant data in a CSV format through a converting tool. This feature enables the creationof a network of clusters based on keywords and/or terms (noun phrases) extracted from titles andabstracts of REU awards. Specifically, for each REU award, two different approaches wereadopted to extract terms and keywords. Terms were extracted from the titles and abstracts usingCiteSpace. Technical keyword phrases focusing on research contents of REU awards wereextracted by use of ChatGPT Application Programming Interface (API). Subsequently, anetwork of clusters was created based on the extracted terms and keywords. These clusters revealthe main topics of all REU projects in the dataset.Based on the above-mentioned clusters generated from REU and WoS

Conference Session

Teaching with ML and Generative AI

Collection

2024 ASEE Annual Conference & Exposition

Authors

Bobby F Hodgkinson, University of Colorado Boulder; Nathan Eric Whittenburg, University of Colorado Boulder

Tagged Divisions

Computers in Education Division (COED)

adding section labels that indicate to the graderswhich prompt the report addresses in each section of text. It is worth noting that this approachmay be overly complicated with the recent deployment of ChatGPT 4.0, where PDFs can beuploaded and modified directly by the LLM. Nevertheless, the course under investigation hasupward of 40 submissions which could quickly reach any ChatGPT data limits. Additionally, thisapproach is mostly automated so dozens to even hundreds of group reports could be analyzed andhighlighted with minimal user interaction.Results - Sentiment AnalysisWe present findings from the application of our sentiment analysis technique on two lab activitieseach lasting about seven weeks. Despite the limited scope, the participation

Conference Session

Student Success in ET

Collection

2024 ASEE Annual Conference & Exposition

Authors

Kenan Baltaci, University of Wisconsin, Stout; Monika Herrmann, University of Wisconsin, Stout; Ahmet Turkmen

Tagged Topics

Diversity

Tagged Divisions

Engineering Technology Division (ETD)

Critical EngagementIn this study, students were invited to participate in a survey to share their experiences using AItools during one semester in four courses. Thirty-five (35) Computer and Electrical Engineering(CEE) students at the University of Wisconsin-Stout responded to the survey describing their useof AI tools such as ChatGPT in their studies. The group included 15 sophomores and 20 seniorsenrolled in 4 different CEE courses titled “CEE-215 Electronics”, “CEE-405 Capstone I:Computer Engineering Design”, “CEE-410 Capstone II: Computer Engineering Design”, and“CEE-355 Applied Electromagnetics”. The survey featured nine questions, seven using a Likertscale to measure students' opinions about AI tools in their education. The Likert scale

Conference Session

Pre-College Engineering Education Division (PCEE) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Daniel Loke, Nanyang Technological University; Jeffrey D Radloff, SUNY, Cortland; Ibrahim H. Yeter, Nanyang Technological University

Tagged Divisions

Pre-College Engineering Education Division (PCEE)

Research and Practice in Technology Enhanced Learning. He is also the upcoming Program Chair-Elect of the PCEE Division at ASEE. His current research interests include STEM+C education, specifically artificial intelligence literacy, computational thinking, and engineering. ©American Society for Engineering Education, 2024 K-12 STEM Pre-Service Teachers’ Perceptions of Artificial Intelligence: A PRISMA-tic Approach (Work-in-Progress)AbstractRecent technological advancements have led to the emergence of generative artificialintelligence (GenAI) applications like Gemini and ChatGPT. Consequently, these applications ofAI and others have proliferated aspects of daily life. Notably, there is a growing

Conference Session

Student Engagement in Construction Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Hariharan Naganathan, Wentworth Institute of Technology; John Cribbs Ph.D., Wentworth Institute of Technology

Tagged Topics

Diversity

Tagged Divisions

Construction Engineering Division (CONST)

, software, andtools can positively impact construction projects by increasing productivity, improving safetyrates, and increasing the success rate of winning construction projects and bids. Interestingly, evenArtificial Intelligence (AI) has made its way into the construction industry, with tools likeChatGPT being utilized to realign project schedules and improve overall project efficiency .Researchers have used ChatGPT to explore integration with digital twins for healthcare, writingmanuscripts, and adapting classroom education to achieve student learning outcomes [18]-[20]. Itis worth noting that tools such as ChatGPT, which have emerged recently as AI-poweredassistants, are still in the process of gathering data to establish their reliability

Conference Session

ML and Generative AI Tools and Policies

Collection

2024 ASEE Annual Conference & Exposition

Authors

Sofia M Vidalis, Pennsylvania State University; Rajarajan Subramanian, Pennsylvania State University; Fazil T. Najafi, University of Florida

Tagged Divisions

Computers in Education Division (COED)

Perceptions: The Impact of AI Tools on Engineering Education Sofia M. Vidalis, Associate Professor at Pennsylvania State University - Harrisburg, Rajarajan Subramanian, Associate Teaching Professor at Pennsylvania State University – Harrisburg, and Fazil T. Najafi, Professor at University of Florida Abstract The rapid advancement of artificial intelligence (AI) has led to the integration of chatbots like ChatGPT or Chat AI into various sectors, including education. This study investigates the impact of many AI tools in engineering education, focusing on their potential to enhance learning

Conference Session

NSF Grantees Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

John Clay, University of Texas at Austin; Xingang Li, University of Texas at Austin; Molly H Goldstein, University of Illinois Urbana-Champaign; H. Onan Demirel, Oregon State University; Darya Zabelina; Charles Xie; Zhenghui Sha, University of Texas at Austin

Tagged Topics

NSF Grantees Poster Session

socioeconomic status [16]), whichmay negatively impact design performance. Additionally, the limits of human cognition begin tobe tested as the number and complexity of trade-offs, constraints, and user needs that must beconsidered grows [4], [13]. Finally, traditional/manual design approaches are resource intensivedue to the amount of time required for creating preliminary designs, and for manually correctingpotential errors made by the human designer during these tasks.Figure 1. (a) Genetic algorithms exploring possible solutions for renewable solar-energy systemsin the Aladdin CAD software [8]; (b) Variational autoencoders for structure-aware designgeneration [9]; (c) CAD model generation using large language models, such as ChatGPT [10].Thus

Conference Session

Engineering, Ethics, and Leadership

Collection

2024 ASEE Annual Conference & Exposition

Authors

B. Michael Aucoin P.E., Texas A&M University; Zhendi Zhang, Texas A&M University; Miles O. Dodd, Texas A&M University

Tagged Divisions

Engineering Ethics Division (ETHICS), Engineering Leadership Development Division (LEAD)

done on these topics. We conclude the paper witha discussion and recommendations for future work.IntroductionWhile generative artificial intelligence (Gen AI) first became available for widespread use in late 2022(in the form of OpenAI’s ChatGPT platform), this milestone is the latest in a long march ofincreasingly sophisticated developments in harnessing computational power [1] for a variety ofapplications. For this paper, we will generally address how computational power and the use of datais increasingly impacting the practice of leadership. We will speak broadly to the impact of big dataand more specifically to Gen AI, but all under the umbrella term of data-enhanced leadership. Weuse this phrase to capture the phenomenon that

Conference Session

AI and Tools for Transdisciplinary Work

Collection

2024 ASEE Annual Conference & Exposition

Authors

Elana Goldenkoff, University of Michigan; Erin A. Cech, University of Michigan

Tagged Topics

Diversity

Tagged Divisions

Liberal Education/Engineering & Society Division (LEES)

education (due to the COVID-19 pandemic) as well as a cohort of students whotook all their classes under standard post-pandemic in-person instructional protocols. The secondinterview period also coincided with launch and subsequent public debates around ChatGPT(OpenAI, San Francisco, USA) and other similar generative AI models.All interviews were conducted by the first author virtually using video conferencing. They wereoffered a $50 gift card as a token of gratitude for their time and participation. The interviewsbegan by gathering information about respondents’ educational and employment history andtheir prior training in ethics and public welfare responsibilities. After asking about theirexperiences in their current master’s program, we asked

Conference Session

Cybersecurity Topics

Collection

2024 ASEE Annual Conference & Exposition

Authors

Heena Rathore, Texas State University; Henry Griffith, San Antonio College

Tagged Divisions

Computers in Education Division (COED)

through the platform of Google Earth.Throughout the activity, they were actively encouraged to leverage a wide array of online tools,encompassing resources such as usage of large language models such as ChatGPT and variousothers, to collaboratively solve the questions. During the exercise, students encountered encryptedmessages at various stages and to progress in the activity had to apply cryptographic principles todecipher these messages. The proposed practical application of cryptography involved tasks likedecrypting codes, solving puzzles, or using ciphers to reveal clues led them closer to the final chal-lenge. By introducing scavenger hunt at the intersection of computer system security education,we open a gateway to experiential learning

Conference Session

International Division (INTL) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Fanyu F Zeng, Indiana Wesleyan University

Tagged Topics

Diversity

Tagged Divisions

International Division (INTL)

difficulty • Academic expectations • Learning styles • Assignment deadline • Attendance to class and meeting • Plagiarism, ChatGPT, copying from each other, using a material with a proper or no citation.Some of the challenges faced by students from India are surprising to us because many may notthink that those students may have such challenges in the areas below. • Cultural Adjustment: Many believe India is very close to Western countries because of its unique history over the last 100 years. But we still find that many students adapt to a new culture, lifestyle, and social norms after they arrive in the U.S. Like other international students, they may still experience culture shock, homesickness, and

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Gerry A Pedraza, Texas A&M University; Sunay Palsole, Texas A&M University

Tagged Divisions

Computers in Education Division (COED)

faculty, who are oftenconcurrently engaged in research, service duties, and mentoring activities [2], [3].To support instructional designers and faculty in this endeavor, we have leveraged the APIs ofOpenAI tools to create Transcriptto, a Python program that contains clever algorithms that aid inthe crucial steps in lecture preparation, allowing instructional designers and faculty to have abetter starting point when starting the development of an online course. Transcriptto utilizes astraightforward yet robust workflow, incorporating openly available technologies such asPymovie, FFmpeg, OpenAI’s Whisper, and ChatGPT. It transforms video lectures into polishedtext, supporting various input types, including audio files, and pre-existing scripts

Conference Session

Industrial Engineering Division (IND) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Priyadarshini Pennathur, University of Texas at El Paso; Arunkumar Pennathur, The University of Texas at El Paso; Amirmasoud Momenipour, Rose-Hulman Institute of Technology

Tagged Divisions

Industrial Engineering Division (IND)

Worker transparent systems for tracking safety training, incidents, and Safety and Compliance compliance with regulations, or platforms for workers to report issues anonymously. Research on integrating Generative AI like ChatGPT into the Generative AI workplace, focusing on opportunities, challenges, risks (socio- technical), and impacts on productivity, safety, and health.The materials and methods used in this course can be tailored for use in courses such as workmeasurement, work analysis and design, or operations management. These topics may also behelpful for other engineering majors and

Conference Session

Design in Engineering Education Division (DEED) - Best in DEED

Collection

2024 ASEE Annual Conference & Exposition

Authors

Wangda Zhu, University of Florida; Rui Guo, University of Florida; Yuanzhi Wang, Cornell University; Wanli Xing, University of Florida; Eddy Man Kim, Cornell University; Chenglu Li, The University of Utah

Tagged Divisions

Design in Engineering Education Division (DEED)

can be integrated into CAD education and implies future directions forAI-supported design tools.Introduction In today's educational settings, Generative AI (GAI) has had a significant influence on the fields ofScience, Technology, Engineering, and Mathematics (STEM) education (Cooper, 2023). Among thesetechnological advancements, text-to-text models like ChatGPT have been particularly prominent, ashighlighted by Lo (2023). Furthermore, the impact of GAI extends into design and design education, wherethe advent of image-generative technologies such as Midjourney, DALL-E, and Stable Diffusion marks asignificant shift (Burlin, 2023). These technologies not only streamline the design process but also make iteasier for students to express

Conference Session

Educational Research and Methods Division (ERM) Technical Session 24

Collection

2024 ASEE Annual Conference & Exposition

Authors

Bradley J. Sottile, The Pennsylvania State University

Tagged Divisions

Educational Research and Methods Division (ERM)

), the third ethics scenariopresented respondents with a scenario featuring the issue of utilizing artificial intelligence. Thequantitative portion of the third scenario prompt was: Please consider the following scenario when answering questions on this screen: A major writing assignment is coming up for an engineering student’s capstone design course during a very busy part of the semester. There are a few major sections of the paper that require mostly formulaic responses. A student in the course decides to use ChatGPT, an artificial intelligence chatbot, to write those sections of the paper for them. [Question 06. Likert scale, responses choices: very unethical, somewhat unethical, neither ethical or unethical, somewhat ethical, very ethical

Conference Session

NSF Grantees Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ryan Hare, Rowan University

Tagged Topics

NSF Grantees Poster Session

implementation of more automatedsystems in a classroom helps to free up instructor time and resources, and to help raise overallclassroom performance.To achieve an automated educational support system that can stand without instructorintervention, intelligent tutoring systems (ITSs) offer a valuable avenue of research [2]. Thesesystems are well-established in the field, but have seen a surge in development in recent years dueto advancements in large language models like ChatGPT [3], better artificial intelligence methods[4], wider technology adoption, and the recent boom in e-learning [5]. However, a key aspect ofcomputer- or web-based ITSs often remains unaddressed; they are boring.For ITSs to function properly, it is necessary to perform regular

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

Conference Session

MECH - Technical Session 4: Innovation in Engineering Education Methods

Collection

2024 ASEE Annual Conference & Exposition

Authors

Karen Supan, Norwich University

Tagged Divisions

Mechanical Engineering Division (MECH)

Artificial Intelligence Case Studies in a Thermodynamics CourseIntroductionWith the explosion of ChatGPT in the past year, it seems that Artificial Intelligence (AI) iseverywhere, but engineering students may not realize its application beyond writing papers. Theaim of this study was to build an AI teaching module that could be implemented into existingMechanical Engineering Curriculum. Rather than teach students how to build neural networksor large language models, the module focused on how AI is utilized in Nuclear Power Plants.The module was then implemented into a Thermodynamics II course, directly following a uniton vapor power plants. The full course outline can be found in Appendix A, Table A1. Sevencase studies from AI and Nuclear Energy

Conference Session

Modern Teaching Strategies in Engineering

Collection

2024 ASEE Annual Conference & Exposition

Authors

Dirk Joel-Luchini Colbry, Michigan State University

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

students understand the importance ofexploring and using current and emerging tools as part of their lifelong education. The specifictools can vary a lot depending on individual classroom learning goals, resulting in a wide rangeof student-authored tutorials. Some examples from the author’s classes include:  Setting up ChatGPT to help write code in Jupyter notebooks.  Building and deploying your own Shiny App.  Accessing the US census API in Python.  Downloading and installing Seaborn to make more robust figures.Students are tasked with creating in-depth tutorials designed to help their peers learn to use thesoftware tools effectively. Creating successful tutorials requires that student authors bothunderstand the tools and

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