Paper ID #49641Hands-On Fluid Mechanics: A Laboratory Course Development StoryDr. Matthew Kuester, University of Mary Hardin-Baylor Dr. Kuester is an Assistant Professor at the University of Mary Hardin-Baylor in the Computer Science, Engineering, and Physics Department. His research interests include renewable energy, aerodynamics, fluid mechanics, and engineering pedagogy. ©American Society for Engineering Education, 2025 1 Session XXXX Hands-On Fluid Mechanics: A
programs. He has research experience with programming, developing online programs in technology, and has several refereed papers on online education, recycling and innovation. ©American Society for Engineering Education, 2025 1 Session XXXX Improving Retention in STEM Programs Raj Desai McCoy School of Engineering Midwestern State University AbstractScience, Technology, Engineering, and Math (STEM
infrastructure, construction education, and workforce development.Dr. Jiannan Cai Dr. Jiannan Cai is an Assistant Professor of the School of Civil & Environmental Engineering, and Construction Management at the University of Texas at San Antonio (UTSA). She teaches Construction Materials and Testing, and Construction Estimating II, both at undergraduate levels. Her research interests are construction automation and robotics, artificial intelligence and its applications in construction, infrastructure, and built environment. ©American Society for Engineering Education, 2025 1
Measures, LLC, Combs is committed to fostering continuous improvement and ensuring that programs achieve their intended outcomes. Her expertise in stakeholder engagement and communication ensures that evaluation findings are disseminated and utilized for maximum impact. ©American Society for Engineering Education, 2025 1 Session XXXX Closing the Gap through Guided Pathways into the Engineering and Computer Science Workforce Nandika Anne D’Souza Mechanical Engineering Department
Paper ID #49625Integrating Artificial Intelligence in Engineering Education: A Work-in-ProgressSystematic Review of Applications and ChallengesMr. Thomas Franklin Hallmark, Texas A&M University ©American Society for Engineering Education, 2025 1 Integrating Artificial Intelligence inEngineering Education: A Work-in-Progress Systematic Review of Applications and Challenges Thomas F. Hallmark, Ph.D. Student Jaehee L. Park, Ph.D. Student Ashlynn W
construction, sustainable materials and infrastructure, construction education, and workforce development.Dr. Jiannan Cai Dr. Jiannan Cai is an Assistant Professor of the School of Civil & Environmental Engineering, and Construction Management at the University of Texas at San Antonio (UTSA). She teaches Construction Materials and Testing, and Construction Estimating II, both at undergraduate levels. Her research interests are construction automation and robotics, artificial intelligence and its applications in construction, infrastructure, and built environment. ©American Society for Engineering Education, 2025 1
his teaching excellence with the Accessibility Champion Award (Fall 2022 and 2023) by the Disability and Access Office and the Disability Cultural Center. Additionally, he was honored as the Professor of the Year (2023-2024) by the Biomedical Engineering Society, UT Austin Chapter. ©American Society for Engineering Education, 2025 1 Session XXXX Integrating Biological Context into Computing Education: Enhancing Interdisciplinary Learning in Biomedical Engineering Ernesto A. B. F. Lima Oden
Paper ID #49493Integrating Conference Poster Presentations into a Data Science ClassDr. Matthew Fendt, Baylor University Dr. Matthew Fendt is a Senior Lecturer of Computer Science at Baylor University. His research interests include video game and app development for education, pedagogical practices, AI, and machine learning. ©American Society for Engineering Education, 2025 1 Session XXXX Integrating Conference Poster Presentations into a Data Science Class
(NHGIS) and the United States Census Bureau. The data was compiled into a spreadsheet and used to calculate variables needed to calculate a series of Monte Carlo simulations to generate 10 participant profiles for each census tract or block group. The profiles for each of these simulated individuals were then entered into a python program to apply the decision making matrix for car transactions to predict their adoption of the various levels of CAV technology for analysis. The results show the predicted adoption of varying levels of CAV technology over the next 16 years for residents at the census tract and block group level. Levels 1 and 2 technology appear to make up a majority of the technology
Paper ID #49649Integrating Peer-Led-Team Learning (PLTL) and Design Thinking to improvestudent success in Engineering StaticsProf. Haiying Huang, The University of Texas at Arlington Prof. Haiying Huang is a professor of Mechanical and Aerospace Engineering and the Director of Engineering Education at the College of Engineering at the University of Texas Arlington. Her research interests include design thinking pedagogy, collaborative learning, and faculty development. ©American Society for Engineering Education, 2025 1
, Tarleton State UniversityLondon Knight, West Texas A&M UniversityVictoria June Vinzant, Texas A&M University - Kingsville ©American Society for Engineering Education, 2025 1 Intersection of Design and Society: Student and Faculty Reflection on an Interdisciplinary CourseJames K. Nelson Andrew S. CrawfordRELLIS Academic Alliance Mechanical Engineering Technology StudentTexas A&M University System Tarleton State UniversityCeleste A. Riley
1 Session XXXX Laser Cutters versus 3D Printers for Mechanical Engineering Projects Dani Fadda, Wooram Park, PL Stephan Thamban, and Oziel Rios Mechanical Engineering Department The University of Texas at Dallas AbstractThe use of laser cutters versus 3D printers for mechanical engineering projects is discussed in thispaper. Projects with a physical build are often included in lecture-based classes and 3D printing is aviable option to efficiently fabricate plastic models for the prototypes. 3D printing is also an
Paper ID #49651Learning Languages through Interactive GamingMr. Colby Edward Kurtz, Houston Christian University ©American Society for Engineering Education, 2025 1 Learning Languages through Interactive Gaming 1Colby E. Kurtz, 2Matthew Z. Blanchard, 3Marian K. Zaki 1,2 Undergraduate Cyber Engineering Students, 3Assistant Professor of Computer Science College of Science and Engineering Houston Christian University kurtzce, blanchardmz, mzaki @hc.edu
Paper ID #49439LLM-Assisted Performance Indicators for Student Outcome AssessmentDr. Rahul Sharan Renu, Austin College Dr. Renu is the Founding Director of Engineering at Austin College. He has several years of experience with ABET accreditation having seen two programs through initial accreditation and one program through re-accreditation. His research interests include investigating 1) methods to maximize student potential in engineering programs, 2) approaches to better educate K-12 students on the undergraduate engineering experience, and 3) data-driven approaches to link product design to manufacturing process design
& biomedical data measurement, and educational robotics development. ©American Society for Engineering Education, 2025 1 Session 1 Machine learning and Vision Based Embedded Linux System Education Byul Hur Department of Engineering Technology and Industrial Distribution Texas A&M University, College Station AbstractA course with practical applications of machine learning and vision processing can be stacked with thetraditional
Associate Professor in the Department of Mechanical Engineering at the University of North Texas (UNT). He earned his Ph.D. in 2015 from Southern Methodist University in Dallas, Texas, and holds both bachelor’s and master’s degrees in Aerospace Engineering from Italy. Dr. Manzo’s research spans several areas within mechanical engineering, including experimental optics, photonics, sensing, and experimental fluid mechanics. He has authored over 45 peer-reviewed journal papers and conference proceedings, and he holds 3 US patents (1 utility and 2 provisional). Dr. Manzo has been successful in securing over $2.3 million in research funding from prestigious sources such as the National Science Foundation (NSF), the Department
aerospace. Dr. Lynch now serves as an Associate Teaching Professor in the Applied Engineering department and as an Adjunct in ISME at WSU. His research interests include Engineering Education, Leadership, Mentoring and Lean Six Sigma.Ridge Daniel Towner, Wichita State University ©American Society for Engineering Education, 2025 1 Project-Based Learning: Finite Element Analysis of CNC Tooling Surfaces Oliver Harrison Applied Engineering – Process Automation Undergraduate Student Wichita State University Adam Carlton Lynch, Ph.D
Paper ID #49661Proof of Concept: Offshore Workforce Development Using YouTube MethodsDr. Heidar A Malki, University of Houston - COE Heidar A. Malki is currently a Professor and chair of Engineering Technology Department at the College of Technology. He also has a joint appointment with Electrical and Computer Engineering Department at UH. He holds a PhD. degree in Electrical Engineeri ©American Society for Engineering Education, 2025 1 Session: Enhancing the Student Experience Proof of
), Irbid, Jordan. Dr. Aliedeh worked as an operation engineer for Jordan Sulphochemical Company, Zarqa, Jordan. His basic research interests include Multi-phase Flow, Turbulence Modeling, Heat Transfer, Phosphogypsum Recycling Process, and Engineering Education. He published numerous research papers in those fields in international journals. The added value of his basic research is manifested in by achieving two shifts in Phosphogypsum conventional research: (1) Shifting from lab scale to the pilot plant scale and (2) Shifting from one variable at a time (OVAAT) to factorial design research methodology. The courageous attempt to shift our PG conventional research from lab scale to the pilot plant scale was the most
testing, measurement automation, environmental & biomedical data measurement, and educational robotics development. ©American Society for Engineering Education, 2025 1 Session 10 Python-based Microcontroller Architecture and Microcontroller Application Education in Engineering Technology Byul Hur Department of Engineering Technology and Industrial Distribution Texas A&M University, College Station AbstractPython gained
torquedistribution. These failures not only reduced the drill's operational efficiency but also causedoverheating and increased wear on other components. By focusing on gear design and materials,as well as optimizing torque ratios, the Lean Six Sigma approach enabled the team to propose aredesign that improved energy transfer, reduced downtime, and enhanced the tool's lifespan.Addressing these root causes through Lean Six Sigma not only improved the power drill'sefficiency but also provided valuable insights into the importance of systematic analysis in productdevelopment. Below shows the FMEA and Pareto Chart for each of the two failures.Figure 1: FMEA focused on the Chuck and Motor systemBoth failures are assessed in terms of their severity, occurrence
undergraduate recruiting, student activities, engineering K -12 outreach, and scholarships forShanna E Banda, The University of Texas at ArlingtonDr. Karthikeyan Loganathan, The University of Texas at Arlington Dr. Karthikeyan Loganathan is an Assistant Professor of Instruction in the Department of Civil Engineering and serves as Graduate Advisor for the Master of Construction Management program. His research areas are Wastewater Pipelines’ Condition Assessment, Non-Destructive Testing and Condition Assessment of Flexible Pavements.Nila Veerabathina, The University of Texas at Arlington ©American Society for Engineering Education, 2025 1
location. Figure 1: Completed Example MESA Bot with Arduino Circuit 5150 Gram Combat Bots150g robot kits are sent out upon request which include electronic speed controls, a remote,motors, and all the components necessary to build a small scale combat bot. There are twolessons for the 150g combat bots: Combat Robot Safety and Wiring Your 150g Bot. These lessonsare instruction manuals with pictures that a team can follow along with. Constructing a 150grobot requires the use of a soldering iron, so these robot lessons are geared toward high schooland college teams. While more resources are necessary to build 150g robots, the kits and
IntroductionGenerative AI (GenAI) has fundamentally altered the educational landscape, bringing bothadvantages and challenges. In engineering education, the rapid adoption of GenAI tools hasfacilitated learning but has also spurred a notable increase in academic dishonesty. In the wake ofthis shift researchers have been quick to examine effects. Chan [1] explored this phenomena andintroduced the concept of “AI-giarism”, describing the misuse of AI tools to bypass traditionalplagiarism detection systems through a qualitative study of over 500 students. Li [2] emphasizesin their work the growing ethical dilemmas stemming from hard to monitor usage of GenAI inassessments, ultimately calling for adaptive educational policies to address this issue. It is clearthat
Economic Technical students are highly receptive to AI integration in educationimplementation initiatives. Our approach combines descriptive statistics, Impact, which collectively assess various dimensions of students' and there is minimal resistance to AI adoptiocorrelation analysis, and pattern recognition techniques to develop a perceptions and interactions with AI in education. As shown in Table 1
San AntonioPatricia Rodriguez Ann Rodriguez, The University of Texas at San Antonio ©American Society for Engineering Education, 2025 1 Session XXXX Summer Pre-Engineering Program Builds Student Confidence and Motivates Interest in STEM Araceli Martinez Ortiz, PhD The University of Texas at San Antonio Gabriela Gomez, Ed.D. The University of Texas at San Antonio
3 75%• Solution: Exploring the role of Unified Modeling Structural Behavioral Defective products Language (UML) in improving processes [1] per 1,000 units 5 1 80% Class Object Package Activity State Time spent manual• Research Gap: Diagrams Diagrams
equips students with essential skillsfor modern hardware design challenges [1].A major component of this work is the integration of hands-on lab assignments to reinforcetheoretical concepts. The labs focus on key hardware modules such as Barrel Shifters, CarryLookahead Adders, and Wallace Tree Multipliers, allowing students to develop a deeperunderstanding of digital design. This paper also discusses the educational impact of thesemodules, evaluating student engagement and comprehension improvements.Background and MotivationStudents learn SystemVerilog more effectively when they engage in challenging and interestingdigital design examples. Providing students with meaningful projects enhances their problem-solving abilities and prepares them for
Paper ID #49596Teaching Science and Engineering undergraduates with a liquid droplet solidificationtoolMr. Alexander Hernandez, West Texas A&M University Senior Mechanical Engineering student at West Texas A&M University.Dr. Sanjoy Bhattacharia, West Texas A&M University Assistant Professor of Mechanical Engineering, College of Engineering, West Texas A&M University, Canyon, TX-79016 ©American Society for Engineering Education, 2025 1 Teaching Science and Engineering undergraduates with a liquid
classroomsize on student engagement, academic achievement, and overall learning experiences has becomea topic of increasing interest and significance. This research paper embarks on a journey tocomprehensively investigate the relationship between classroom learning and smaller classroomsizes. Wang et al. [1] explored the impact of class size on student engagement and satisfaction byutilizing a comparative analysis of small and large classes, revealing that smaller class sizessignificantly enhance teacher supportiveness and overall student satisfaction. By delving into themultifaceted effects of class size reduction, we aim to shed light on the potential benefits andchallenges associated with this critical dimension of the learning environment. Benton