Paper ID #49521Welcome Letters to Families of New Graduate StudentsProf. Mia K. Markey, University of Texas at Austin Dr. Mia K. Markey is a Professor of Biomedical Engineering and Cullen Trust for Higher Education Endowed Professorship in Engineering #1 at The University of Texas at Austin as well as Adjunct Professor of Imaging Physics at The University of Texas MD AndAnakaren Romero Lozano, University of Texas at AustinKristin M Connelly, University of Texas at Austin ©American Society for Engineering Education, 2025 1
courses are offered during the 10-week summer session, allowing students to catch upon missing prerequisites.In recent years, we have observed significant variations in the percentage of DFW grades acrossdifferent sections of the same courses, primarily depending on the instructor. This study presents acomparative analysis of grade distributions in selected courses, highlighting these discrepancies andexploring potential causesGrade Distribution in Selected CoursesA. Statics (Lower-Division General Engineering Course)During the Fall 2023 and Spring 2024 semesters, six sections of Statics were offered by three differentinstructors. Statics is a required course for the civil, industrial, and mechanical engineering BS degreeprograms. Table 1
recommendations for holistic partnerships tosupport students, strengthen local industries, and contribute to regional workforce development. IntroductionRecently, with the introduction of the Texas Chips Act [1] and the growth of the semiconductorindustry, the demand for engineers has increased significantly. However, a shortage of skilledprofessionals remains, and providing semiconductor education requires substantial infrastructureto adequately prepare students for the industry. Various approaches have been developed toaddress these challenges and accommodate the diverse needs of semiconductor education. Theserange from initiatives at the high school level [2, 3, 4] to two-year community colleges [5
that go beyond traditional lecture-based teaching. By using collaborative projects,structured assessments, and reflective practices, students can engage in both technical learning andthe development of critical soft skills. Below is a breakdown of instructional methods designed tointegrate teamwork, communication, critical thinking, and ethical decision-making inThermodynamics, Fluid Mechanics, and Electrical Circuits courses. Proceedings of the 2025 ASEE Gulf-Southwest Annual Conference The University of Texas at Arlington, Arlington, TX Copyright 2025, American Society for Engineering Education Table 1: Instructional Methods for Professional Skills
, Process-Structure-Property Relationships, Finite Element Stress Analysis Modeling & Failure Analysis, ASME BPV Code Sec VIII Div. 1 & 2, API 579/ASME FFS-1 Code, Materials Testing and Engineering Education. Professionally registered engineer in the State of Texas (PE).Dr. Joanna Tsenn, Texas A&M University Joanna Tsenn is an Associate Professor of Instruction in the J. Mike Walker ’66 Department of Mechanical Engineering at Texas A&M University. She earned her B.S. from the University of Texas at Austin and her Ph.D. from Texas A&M University. She coordinates the mechanical engineering senior capstone design program and teaches senior design lectures and studios. Her research interests include
and vibration analysis have also been carried out to evaluate theflying cars are promising future transportation systems. They dynamic characteristics [11].can erase traffic congestion by providing on-demand, point-to-point transportation with reduced/zero-emission [1]. Driven by This project aims to design and develop a Jetson One stylethe recent advancements in batteries, motors, and power personal eVTOL aircraft. This paper focuses on the design of aelectronics, and flight control technologies, hundreds of new lightweight frame that is strong and safe for flight. The creationeVTOL projects are in the development stage by many
opportunities structures in vast datasets as in [1] and continuouslyacross multiple domains, including education, it also raises improving through fine-tuning and prompting.ethical concerns around issues such as copyright,misinformation, and bias. This paper explores the potential of Generative AI operates in three phases:generative AI to revolutionize teaching and learning, with a focuson its impact on student outcomes. Through an examination of • Training, to create a foundation model that can serveselective platforms such as ChatGPT, Character AI, Gemini, and as the basis of multiple gen AI applications.Deep Seek, this paper aims to introduce students to thefundamentals of building AI-powered applications
. Many AI-powered educational tools require soft skills that employers seek. As AI continues to shapesubstantial computing power, subscription fees, or institutional the future of work, its strategic integration into engineeringsupport, which may create barriers for students from under- curricula will be a crucial step in preparing students for theprivileged backgrounds. Institutions must consider providing demands of an AI-enhanced workforce.subsidized access to AI platforms or integrating open-sourcealternatives to ensure inclusivity in AI-driven education[8]. R EFERENCES Another major consideration is ethical concerns, particularly [1] A. Alberola, E. del Val, V. Sanchez
-icant results and analysis, followed by the conclusion and futureattention in recent years due to its ability to work in Section 6.capture detailed spectral information across numerous narrowand contiguous spectral bands. This characteristic allows for II. R ELATED W ORKSmore precise identification and differentiation, making HSIa valuable tool in various fields such as bio-medical [1], The field of HSI classification has seen significant ad-agriculture [2], mineral exploration [3], and environmental vancements through various machine learning models aimedmonitoring [4]. However, the high dimensionality and large at
hijack user sessions leading adversarial testing are used. These techniques aim to min-to unauthorized use and data leakages [1]. Common attack imize false positives and enhance the accuracy of vulnera-vectors are session hijacking, where a malicious attacker bility identification [6]. Effective testing frameworks, modelsteals or sniffs away a user’s session cookie in order to gain decision-making transparency, and continuous monitoring forunauthorized access, and session fixation, where an attacker identifying any possible drifts or degradations in performancemaps a user’s session ID to one they know in order to allow are involved in valid evaluation of LLMs. Rigorous cross-them to
decision-makers tools to leverage data for strategic planning, I. I NTRODUCTION and optimum resource utilization, providing the universities International student enrollment in the United States has and the policymakers with intelligence they need to predictsteadily increased since 1948, but COVID-19 travel & student future trends and make educated decisions.visa restrictions caused a slight dip. The data shows thatenrollment began recovering in the 2022/2023 academic year II. L ITERATURE R EVIEWand continues to rise [1]. Predicting accurately these trends According to recent estimates
., [1]), mentioned inpassing (e.g., [2, 3, 4, 5, 6]), or as a lead in to a discussion of how to foster these connections(e.g., [7]). The role of these relationships in fostering student success has been discussed inseveral works as well, e.g., [8, 9, 10]. These works indicated that community college studentswith stronger instructor relationships were more likely to seek support, that relationship-richclassrooms promote mentoring, and that even minimal efforts can have a positive impact onclassroom climate.It is also well established that forming connections between professors and students was difficultwhen COVID-19 disrupted in-person education. In addition to professors’ and students’ livedexperiences, evidence is provided in several studies
investigated how transdisciplinarity has been integrated in engineering educationby delving into the existing challenges and future opportunities that transdisciplinarity offersengineering education. Moreover, we aimed to analyze how transdisciplinary approaches canreshape engineering curricula to better prepare students for real-world, complex challenges.For this paper, we searched for literature related to transdisciplinarity in engineeringeducation. Through our research, we identified several relevant studies, which we groupedinto three primary themes: 1) Integration of real-world problems, 2) Transdisciplinarycompetencies, and 3) Engagement with non-academic stakeholders. These themes werederived from key concepts that are widely acknowledged in
expedite training, they often come at a high cost, making them less accessible toresearchers with limited resources. Finding methods to incorporate assisted labeling has shownto drastically improve accuracy , with Gregorio et al. seeing a 15% increase over manual labelingmethods [1]. In this study, we propose a method that offers an effective and cost-efficientalternative to mainstream AI-assisted features. Specifically, we applied this method to detectfaults within railroad systems, focusing on insufficient ballast—missing gravel between railroadtracks—and plant overgrowth. These faults can disrupt railroad traffic and pose safety risks. Railroad fault detection has been extensively studied in the literature and continues to evolvewith advances
administrators, aligning with Ohio Northern University’s (ONU) IT policies, andmaintaining technical feasibility within the given infrastructure. 1. Learnability and Usability ○ The platform must be highly intuitive for administrators, allowing efficient management of course offerings and scheduling. ○ The interface should enable users to complete tasks efficiently with minimal training. 2. Technical Constraints ○ The app must be easily integrable within ONU’s existing systems. ○ It should require minimal effort from the IT department for implementation and maintenance.Evaluation MetricsKey evaluation metrics include: ● Accuracy: The app should provide the most
cameras or specialized hardware [1] [2].Similarly, a team developed a method to image still objects through walls using Wi-Fi signals.Their approach applies the Geometrical Theory of Diffraction to interpret how Wi-Fi wavesinteract with object edges, allowing for high-quality imaging of objects, including complexshapes like the English alphabet, through walls [8]. Present research extends the capabilities of Wi-Fi imaging by integrating a machinelearning-based classification system and amplitude color [10]. By leveraging signal fluctuationscaptured through a dynamic network of Wi-Fi nodes, systems can infer object shapes andcharacteristics in real time. This represents a step beyond simple detection, aiming for higheraccuracy in object
for environmentally responsiblemanufacturing practices (Yu et al., 2020).In conclusion, the integration of AR and AI technologies in training and operational processes is crucialfor preparing students and professionals for the demands of smart manufacturing environments. Asindustries continue to evolve, the role of immersive technologies in enhancing training outcomes andresource efficiency will likely expand, paving the way for innovative solutions that meet the challengesof modern manufacturing (Casuso et al., 2021).3. Methodology Using the Miller MobileArc™ AR Welding System, students practiced making three types of welds–see Figure 1 for examples. The results for each weld were photographed during the lab session and later
treatments, uses thesetechnologies to identify and isolate distinct structures within complex medical images, ultimately aiding clinical decision-making [1]. In hematology, accurately distinguishing and analyzing blood cells using segmentation methods is crucial forearly disease detection and monitoring treatment effectiveness. Despite these advancements, integrating cutting-edge deep learning models into everyday medical practice remains chal-lenging for many professionals due to the steep learning curve associated with acquiring coding skills [2]. This gap highlightsthe need for more accessible tools that allow medical practitioners to apply advanced segmentation models without requiringextensive programming knowledge. This study aims to
provides the foundation for addressing sustainable material selection through thelens of systems thinking considering trade-offs between materials, making informed decisionssupported by data, and communication.The activity was integrated in the 1-credit Mechanics of Materials’ laboratory session atLawrence Technological University. Eighteen students were enrolled in the session and they met2 hours per week. The activity was presented to the students about 8 weeks into a 15-weeksemester. The students had gained theoretical and practical experiences in several topics throughapplications of the force-displacement relationship and the behavior of various materials.In week 8, the students were introduced to the EOP topic area of Material Selection
evolving to meet the dynamic needs of society. Traditional teachingmethodologies have long provided the foundation for knowledge transmission, fosteringacademic rigor and intellectual discipline. However, as the world undergoes rapid technological,economic, and social transformations, there is a growing need to enhance student engagementand preparedness [1]. Today’s students, raised in a digital era, require adaptable learningexperiences that integrate both traditional strengths and contemporary innovations in education.The increasing demand for adaptability, collaboration, and technological fluency in theworkforce calls for a thoughtful approach that enriches rather than replaces established teachingmethodologies, ensuring a well-rounded
-related professions through interactive mini-sessions and displays.This paper focuses on one specific mini-session, which introduced best management practices(BMPs) for stormwater design. The session was collaboratively designed and delivered bypracticing engineers and educators. In this mini-session, student teams developed cost-effectivesite solutions that adhered to county area specifications. After a brief introduction to the topic,teams were provided with a site plan, sheets representing BMP options, a worksheet, and othersupplies. The activity was structured into the following steps:1. Calculate the Impervious Area2. Calculate the BMP Area3. Design a Minimum of Two Alternative BMP Solutions4. Estimate the Cost of the Selected BMP
1 Department of Mathematics, Engineering, and Computer Science, West Virginia State University, Institute, WV, USA 2 Fractal Analytics Inc, USA 3 Department of Computer Sciences and Electrical Engineering, Marshall University, Huntington, WV, USA Corresponding author: jana@marshall.edu Abstract This study examines how large language models categorize sentences from scientific pa- pers using prompt engineering. We use two advanced web-based models, OpenAI’s GPT-4o and DeepSeek R1, to classify sentences into predefined
represents, performs simple gestures such as waving, and detects and mimics themovements of a nearby individual. The objectives of the project are to enhance outreach effortsby showcasing its represented college to prospective students and families, demonstrating thetechnical capabilities of current students, and inspiring interest in STEM fields.The project is characterized by five main design factors: (1) motor and power transmission,which drives limb and head movement. This is achieved through compact, efficient, servomotors which will generate the torque required to drive the limbs smoothly and safely. (2)structural design, which has a crucial role in the assembly of the robot’s physical structure,specifically the head, arms, and torso. The
organization within the university structure, hiring of studentmentors, recruiting other faculty, recruitment of students, and more. Strategies to overcome someof these issues will be presented.IntroductionA key challenge addressing many universities as well as the current workforce is the attraction ofstudents to the science, technology, engineering, and math (STEM) fields[1], [2]. This challengeneeds to be addressed at all levels of K-12 education. This is important especially due toincreased reliance on technology, and number of trained professionals not keeping up withdemand [3], [4]. As a result, it is imperative that we engage with K-12 students encouragingthem to pursue interests in STEM. STEM summer camps can lessen the impact of
efforts associated with reporting pedagogical effectiveness and the various challenges encountered when trying do so, • A systematic method that can be used to develop an ascending survey to determine the effectiveness of pedagogical techniques. • The quality of student feedback.The Excel workbook and Word document that the author developed to maximize efficiency willbe demonstrated and made available.1. BackgroundThe effectiveness of a pedagogical technique is often reported without considering studentfeedback. One method is to report faculty perception. In order to determine the effectiveness ofactive learning higher level learning and formative assessment, a peer observer uses
in the previous course. The course has more reports than theprevious course, and the reports are more involved. Some preliminary results indicate that thestudents can apply the material from the first course and extend it to mid-level course content.IntroductionEngineering jobs frequently involve design, testing, and construction / fabrication. Thoseactivities need to be completed correctly and in a timely manner. However, the results of theactivities must be communicated effectively.The Accreditation Board for Engineering and Technology (ABET) Program Outcome 3 indicatesthat engineering students need to be “able to communicate effectively” [1].In the consulting areas of engineering, written reports are the primary means of communication,but
the structuralintegrity of a rack upon impact thus protecting the general public in retail (big box) stores andwarehouses. The final phase includes impact testing and developing a sales and marketingstrategy – a collaborative effort between engineering students and the school of business. Theresults are presented in detail with emphasis on how engineering and business studentscollaborate.1. Introduction: This paper reports on a four-year, industry-sponsored design project involving the design anddevelopment of a column guard used to protect storage racks from forklift impacts. The projectwas used to support five separate undergraduate senior (capstone) projects spanning a time-period of approximately four years and involving sixteen
properties of the plastic products in injection molding process. The qualityof the final products is dependent on controlling these variables [1][2][3]. The cooling rate of thepolymer materials is influenced by the mold temperature. Higher mold temperature makes thecooling rate slower which can give better crystalline structure and good mechanical strength butmakes the product more brittle. Higher mold temperature also helps to get a better surface finishand lower residual stress but consumes more energy. [4]. On the other hand, lower moldtemperature results in faster cooling which compromises the mechanical strength due to lowcrystalline structure and dimensional instability due to higher shrinkage. Lower moldtemperature also can result in other
undergraduate research and service learning. Brief highlights of bothof these two techniques are provided next. This paper later describes involving undergraduatestudents in a project in a highway engineering course using a combination of both undergraduateresearch and service learning. It will present some findings and provide some recommendations.Importance of Engaging Undergraduate Students in Research Projects:Engaging undergraduate students in research activities has long been proven to be an effectivemeans of learning. Although this movement started in scientific academic programs [1] likeengineering, it quickly expanded to include other disciplines as well like arts and humanities.The literature is saturated with articles which are testifying to
morelikely to persist to graduation. By connecting first-year students with peer mentors, professionaldevelopment opportunities, and a sense of community, EngineerFEST lays the foundation fortheir success. Engineering festivals and events have become a dynamic approach to enhancingstudent engagement and learning in engineering education. Research highlights the role ofdiverse educational activities in fostering inclusion and feelings of belonging among students.For instance, Rambo-Hernandez et al. (2020) examined the impact of inclusion-awarenessactivities in first year engineering classes, revealing positive outcomes in student retention andbelongingness [1].Programmatic support tailored to facilitate student success has also been a cornerstone