Conference Session

ML and Generative AI Tools and Policies

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jason M. Keith, Mississippi State University; Amin Amirlatifi, Mississippi State University; Shahram Rahimi; Subash Neupane, Mississippi State University; Sudip Mittal

Tagged Divisions

Computers in Education Division (COED)

Paper ID #41009Bark Plug: The ChatGPT of the Bagley College of Engineering at MississippiState UniversityDr. Jason M. Keith, Mississippi State University Jason Keith is the Dean and Earnest W. and Mary Ann Deavenport, Jr. Chair in the Bagley College of Engineering at Mississippi State University, a position he has held since March, 2014. Keith received his B.S. in Chemical Engineering from The University of Akron and his Ph.D. from the University of Notre Dame. Keith is Fellow of ASEE.Amin Amirlatifi, Mississippi State UniversityShahram RahimiSubash Neupane, Mississippi State UniversitySudip Mittal

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Zoe Wood, California Polytechnic State University, San Luis Obispo; Miguel Manoah Refugio Greenberg

Tagged Divisions

Computers in Education Division (COED)

Paper ID #41661Board 43: AP-CS, ChatGPT and Me: a High School Student PerspectiveDr. Zoe Wood, California Polytechnic State University, San Luis Obispo Whether it is creating computer graphics models of underwater shipwrecks or using art and creativity to help students learn computational thinking, Professor Zoe Wood’s projects unite visual arts, mathematics and computer science.Miguel Manoah Refugio Greenberg ©American Society for Engineering Education, 2024 AP-CS, ChatGPT and Me: a high school student perspectiveAbstractWith the creation of openAI’s ChatGPT system, a problem has arisen in

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Trini Balart, Texas A&M University; Kristi J. Shryock, Texas A&M University

Tagged Divisions

Computers in Education Division (COED)

Paper ID #43499Board 48: Perceptions of ChatGPT on Engineering Education: A 2022-2023Exploratory Literature ReviewTrini Balart, Texas A&M University Trinidad Balart is a PhD student at Texas A&M University. She completed her Bachelors of Science in Computer Science engineering from Pontifical Catholic University of Chile. She is currently pursuing her PhD in Multidisciplinary Engineering with a focus in engineering education and the impact of AI on education. Her main research interests include Improving engineering students’ learning, innovative ways of teaching and learning, and how artificial intelligence can

Conference Session

Teaching with ML and Generative AI

Collection

2024 ASEE Annual Conference & Exposition

Authors

Anthony Cortez, Point Loma Nazarene University; Paul Daniel Schmelzenbach, Point Loma Nazarene University

Tagged Divisions

Computers in Education Division (COED)

Paper ID #44437Integrating ChatGPT in an Introductory Engineering Undergraduate Courseas a Tool for FeedbackDr. Anthony Cortez, Point Loma Nazarene University Dr. Cortez is currently an Assistant Professor in the department of Physics and Engineering at Point Loma Nazarene University. He received his BS in Physics from University of California San Diego (UCSD). He went on to complete his MS and Ph.D. in Mechanical Engineering from University of California Riverside (UCR). His research interests include technology as a tool in the classroom, high temperature superconductivity, superconducting detectors, nanofabrication, and

Conference Session

Teaching with ML and Generative AI

Collection

2024 ASEE Annual Conference & Exposition

Authors

Han Kyul Kim, University of Southern California; Aleyeh Roknaldin, University of Southern California; Shriniwas Prakash Nayak, University of Southern California; Xiaoci Zhang, University of Southern California; Muyao Yang, University of Southern California; Marlon Twyman, University of Southern California; Angel Hsing-Chi Hwang, Cornell University; Stephen Lu, University of Southern California

Tagged Divisions

Computers in Education Division (COED)

Manufacturing Engineering at University of Southern California. His current professional interests include design thinking, collaborative engineering, technological innovation, and education reform. He has over 330 ©American Society for Engineering Education, 2024 ChatGPT and Me: Collaborative Creativity in a Group Brainstorming with Generative AIIntroductionThe emergence of generative AI (genAI), exemplified by ChatGPT, offers unprecedentedopportunities to the education system. However, as this technological advancement gainsmomentum, concerns surrounding hallucination [1, 2] and academic integrity [3, 4] have beenraised, casting doubt on its applicability in educational

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

David Reeping, University of Cincinnati; Aarohi Shah, University of Cincinnati

Tagged Divisions

Computers in Education Division (COED)

concepts, curricular complexity, and advancing quantitative and fully integrated mixed methods.Aarohi Shah, University of Cincinnati ©American Society for Engineering Education, 2024 WIP: A Systematic Review of Embedding Large Language Models in Engineering and Computing Education AbstractThis work-in-progress paper explores how students and faculty are employing large languagemodels (LLMs) like ChatGPT in engineering and computing education contexts through asystematic literature review (SLR) with Arxiv. We screened 717 preprint abstracts of emergingliterature related to LLMs, ultimately analyzing 63 papers. We extracted the educationalapplications

Conference Session

ML and Generative AI Tools and Policies

Collection

2024 ASEE Annual Conference & Exposition

Authors

Lucas J. Wiese, Purdue University at West Lafayette; Alejandra J. Magana, Purdue University at West Lafayette

Tagged Divisions

Computers in Education Division (COED)

Information Technology and Professor of Engineering Education at Purdue University. ©American Society for Engineering Education, 2024 A Department’s Syllabi Review for LLM Considerations Prior to University-standard GuidanceAbstractThe release and widespread use of generative artificial intelligence causes concern for the futureof teaching and learning. Since the release of ChatGPT, some institutions released guidance onits use in education, while other institutions waited for the technology to mature. This study iscontextually situated during the Fall 2023 semester at a single university; Unique because theuniversity had not published LLM guidance yet, but the technology had been out long

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

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

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

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

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

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

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

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

ML and Generative AI Tools and Policies

Collection

2024 ASEE Annual Conference & Exposition

Authors

Zifeng Liu, University of Florida; Rui Guo, University of Florida; Xinyue Jiao, New York University; Xueyan Gao, University of Florida; Hyunju Oh, University of Florida; Wanli Xing, University of Florida

Tagged Divisions

Computers in Education Division (COED)

language understanding, code summarization, andnatural language-based programming, where students learn to express programming concepts innatural language 48,49 . 29 outlined the use of dialogue-centric methods in AI-enhanced tutoringsystems, which aid students in formulating pseudocode answers in a natural language formattailored to particular challenges. Furthermore, NLP offers an additional advantage by enablingconversational student support, leveraging knowledge representation to depict a cohort of studentsand their communicative dynamics during collaborative learning in CS. More recently, largelanguage models like ChatGPT are used to assists users by clarifying intricate ideas andtechnologies, offering examples, and directing them to

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

Conference Session

Computers in Education Division (COED) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Syed Hasib Akhter Faruqui, Sam Houston State University; Nazia Tasnim, University of Texas at Austin; Iftekhar Ibne Basith, Sam Houston State University; Suleiman M Obeidat, Texas A&M University; Faruk Yildiz, Sam Houston State University

Tagged Divisions

Computers in Education Division (COED)

Madriaga, Rimel Aggabao, Giezel Diaz-Candido, James Maningo, et al. Performance of chatgpt on usmle: Potential for ai-assisted medical education using large language models. PLoS digital health, 2(2):e0000198, 2023.[13] Enkelejda Kasneci, Kathrin Seßler, Stefan K¨uchemann, Maria Bannert, Daryna Dementieva, Frank Fischer, Urs Gasser, Georg Groh, Stephan G¨unnemann, Eyke H¨ullermeier, et al. Chatgpt for good? on opportunities and challenges of large language models for education. Learning and individual differences, 103:102274, 2023.[14] Ramteja Sajja, Yusuf Sermet, Muhammed Cikmaz, David Cwiertny, and Ibrahim Demir. Artificial intelligence- enabled intelligent assistant for personalized and adaptive learning in higher education

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

Teaching with ML and Generative AI

Collection

2024 ASEE Annual Conference & Exposition

Authors

Abdulrahman AlRabah, University of Illinois Urbana-Champaign; Sophia Yang, University of Illinois Urbana-Champaign; Abdussalam Alawini, University of Illinois Urbana-Champaign

Tagged Divisions

Computers in Education Division (COED)

context of SQL query feedback?Our research questions aim to evaluate the feasibility and effectiveness of utilizing a GenerativeAI model to provide semantic error feedback without revealing the correct solution. We targetprecise error detection and insightful feedback to enhance the educational experience by makingit more tailored to each student. The effectiveness of our fine-tuned model was assessed throughcomparative analyses with the outputs from the standard ChatGPT model. This validation processwas crucial in establishing the refined model’s advancement and distinction in providing preciseand contextually appropriate feedback for SQL queries.2 Related WorkResearch on SQL learning has explored various types of errors and student challenges