Displaying all 6 results
- Conference Session
- Mechanics Division (MECHS) Technical Session 1A
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Ryan Carr, U.S. Air Force Academy; Phillip Cornwell, U.S. Air Force Academy
- Tagged Divisions
- Mechanics Division (MECHS)
Paper ID #45741Exploring the Effective Use of ChatGPT in a Sophomore-Level DynamicsCourseRyan Carr, U.S. Air Force Academy Ryan Carr received his PhD from the Air Force Institute of Technology (AFIT) in 2017 focused on optimal control theory in guidance, control, and navigation or aerospace systems. He was an engineer and branch chief at the Air Force Research Laboratory (AFRL), a flight test engineer the Air Force Test Center (AFTC), and a program manager at the Air Force Office of Scientific Research (AFOSR). He joined the faculty at the United States Air Force Academy in 2023 as an Assistant Professor of Mechanical
- Conference Session
- Understanding the Student Experience in Mechanics Courses
- Collection
- 2024 ASEE Annual Conference & Exposition
- Authors
- Milad Rezvani Rad, University of Southern Indiana; Julian Ly Davis, University of Southern Indiana
- Tagged Divisions
- Mechanics Division (MECHS)
regard, several engineering examples were explored for analyzing theaccuracy of quantitative results obtained from ChatGPT. In-class surveys were also conducted toassess the enthusiasm of students and enhanced interactivity of implementing ChatGPT-powerededucational platform in solving engineering problems. We discovered that students can noticeablybenefit from the key beneficial features offered by artificial intelligence including, but not limitedto, real-time assistance, personalized feedback, and dynamic content generation. Survey resultshighlight the positive impact of implementation of ChatGPT on engineering students' scholarlyperformance and their broader learning experience. Despite all the undeniable advantages AIoffers, it is essential
- Conference Session
- Mechanics Division (MECHS) Technical Session 1A
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Milad Rezvani Rad, University of Southern Indiana; Julian Ly Davis, University of Southern Indiana
- Tagged Divisions
- Mechanics Division (MECHS)
Paper ID #48464Leveraging ChatGPT 4.0’s Image Processing Feature for Enhanced Problem-SolvingSupport in Mechanical Engineering CoursesProf. Milad Rezvani Rad, University of Southern Indiana Dr. Milad Rad is an Assistant Professor in the Engineering Department at the University of Southern Indiana. He earned his Ph.D. in Mechanical Engineering from the University of Alberta in Canada. Besides his specialization in functional thermally sprayed coatings, he explores innovative AI-driven approaches to enhance student engagement in the classroom.Dr. Julian Ly Davis, University of Southern Indiana Jul Davis is an Associate
- Conference Session
- Mechanics Division (MECHS) Technical Session 1A
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Jacklyn Wyszynski, University of Pittsburgh; David Adam DeFrancisis, University of Pittsburgh; David Pabst, University of Pittsburgh; Lee Allen Dosse, University of Pittsburgh; Matthew M. Barry, University of Pittsburgh
- Tagged Divisions
- Mechanics Division (MECHS)
propulsion systems and Engineering Education. ©American Society for Engineering Education, 2025 ACE up your Sleeve: An Analysis of Student Generative AI Usage in an Engineering Statics CourseAbstractRapid technological advancements, including the emergence of computer-aided design andsimulation, have had a significant impact on the engineering industry. This, in turn, extends toengineering education, demonstrating a similar influential effect. The latest development to havesuch reverberations is the launch of a generative artificial intelligence (AI) chatbot known asChatGPT. ChatGPT utilizes a large language model (LLM) that trains the platform to understandand generate human-like responses
- Conference Session
- Mechanics Division (MECHS) Technical Session 1A
- Collection
- 2025 ASEE Annual Conference & Exposition
- Authors
- Dave Kim, Washington State University-Vancouver; Charles Riley P.E., Oregon Institute of Technology
- Tagged Divisions
- Mechanics Division (MECHS)
, particularly alarge language model (LLM), in writing education, the systematic studies related to the ethicaluse of GAI are limited. While grounded in the ethical adaptation of GAI in grading and feedbackfor engineering lab writing, we focus on GAI’s capability to assist with engineering lab reportassessment. Lab report grading is time-consuming for lab instructors and teaching assistants.Moreover, constructing impactful feedback can be challenging for many reasons. In this pilotstudy, we used Copilot and ChatGPT 4o to conduct evaluation and feedback on student labreports of past courses when the instructors did not use generative AI technologies. The studyspace was limited to the two engineering labs in two institutions: strength of materials
- 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