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2024 South East Section Meeting

Authors

John Aaron Louis Grimes, Mississippi State University; Amy K Barton, Mississippi State University

Paper ID #40907Preparing for ChatGPT: Comparing Student Attitudes on Generative AI inContrasting Class InstructionMr. John Aaron Louis Grimes, Mississippi State University John Aaron Grimes is an instructor in the Shackouls Technical Communication Program at Mississippi State University. He holds bachelor’s and master’s degrees in English from Mississippi State University, where he has taught various writing and communication-based courses since 2014.Ms. Amy K Barton, Mississippi State University Amy Barton is the coordinator of the Shackouls Technical Communication Program in the Bagley College of Engineering at

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2024 South East Section Meeting

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Bryn Elizabeth Seabrook, University of Virginia

-level nontechnical engineering classrooms. The purpose of this study is to underscorethe importance of nontechnical engineering skills that are learned through the lens of Science,Technology, and Society (STS). The author builds on previous scholarship to demonstrate howdiscussion-based courses challenge undergraduate engineering students to think more criticallyabout the integration of the social dimensions of engineering problems into the engineeringdesign process. Active learning modules like “Tinkering with ChatGPT” demonstrate theimplications and applications of AI inside and outside the classroom.KeywordsProfessional SkillsSTSGenerative AIChatGPTIntroductionGenerative artificial intelligence (AI) has the capability to produce various

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2024 South East Section Meeting

Authors

Stephen Strain, University of Memphis; Andrew Blass Watson, The University of Memphis; Matthew Hale, The University of Memphis

Tagged Topics

Diversity

proactively navigating challenges.[Note: We asked ChatGPT to compose a conclusion to this paper. Below is its response,unaltered, with which we thoroughly agree.]Looking ahead, the dynamic landscape of Artificial Intelligence (AI) in education demandscontinuous exploration and adaptation. Future research should focus on developing robustframeworks for AI integration that balance technological advancement with ethicalconsiderations. This includes creating guidelines that prevent academic dishonesty whileencouraging innovative uses of AI. Furthermore, there is a need for longitudinal studies to assessthe long-term impacts of AI on learning outcomes, critical thinking, and problem-solving skills.Educational institutions must also consider the evolving

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2024 South East Section Meeting

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Andrew Jeremiah Lance, Francis Marion University; Gregory Michael Mocko, Clemson University; Venkat Jaya Deep Jakka, Clemson University; Rahul Sharan Renu, Francis Marion University

DSE and Shah’s definitions ofideation effectiveness metrics.Oman and colleagues [10] refer to the SV metrics [3] to quantify concept design by mechanicalengineering students. The researchers adapted these metrics to present a modified definition ofNovelty, Variety, Quantity, and Quality. Research from Oman and colleagues [10], and itemsfrom the IPIP [11] were adapted considering SV metrics of ideation effectiveness. This resultedin the sixteen original DSE statements (see the first column in Table 1 to Table 4). Table 1. Development of novelty-focused statements for survey. Original statements extracted from [11]Original statement DSE Survey Statements – First ChatGPT

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2024 South East Section Meeting

Authors

Ayse Tekes, Kennesaw State University; Razvan Cristian Voicu, Kennesaw State University; Coskun Tekes

Jeffrey D Karpicke. Assessing the impact of educational video on studentengagement, critical thinking and learning. A SAGE white paper, 2018.[10] Kevin Fuchs. Exploring the opportunities and challenges of nlp models in higher education: is chat gpt a blessingor a curse? In Frontiers in Education, volume 8, page 1166682. Frontiers, 2023.[11] Brady D Lund and Ting Wang. Chatting about chatgpt: how may ai and gpt impact academia and libraries?Library Hi Tech News, 40(3):26–29, 2023.[12] Margaret Bearman, Juliana Ryan, and Rola Ajjawi. Discourses of artificial intelligence in higher education: Acritical literature review. Higher Education, 86(2):369–385, 2023.[13] Aida Aryani Shahroom and Norhayati Hussin. Industrial revolution 4.0 and education

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2024 South East Section Meeting

Authors

John W. Brocato, University of Georgia

Tagged Topics

Diversity

• Public Perceptions: Examining the Movie Versions of Jeffrey Wigand and CBS News • Edward Tufte's Analysis of Statistical Storytelling: John Snow and the London Cholera Epidemic of 18544On the seemingly ubiquitous subject of AI/ChatGPT, students in BIOE 2100 are required to usethis technology for their major writing assignments, as follows: In addition to your own final version of this assignment, you must also submit an AI- rendered version; i.e., (1) input a prompt to some form of AI software; (2) submit the response it gives you here (separate file) along with the assignment you created yourself; and (3) include a brief (6-8 sentences) analysis of the differences between your submission

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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

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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