several domains already. Largecomplex systems are being fitted with appropriate sensors and actuators to enable thistechnology. Manufacturing is one of the early adopters of this technology, but DT are beingsuccessfully implemented in a variety of domains including production systems[1, 2],agricultural systems[3], utility systems [4], healthcare systems [5], and military systems[6].While there are discussions on the use of digital twins in systems engineering [7], there is nocourse or textbook and few instructional materials are available outside of articles about thepromise of the technology or a specific implementation.DT technology is rapidly growing into its own field, straddling data science, computer science,artificial intelligence
-assessing their teaching effectiveness (self-voice), gathering and analyzing constructive feedbackfrom student evaluations (student voice), and collaborating with colleagues to assess teachingthrough a multi-dimensional observational approach (peer voice). Additionally, templates areprovided to compile assessment data and feedback for both formative uses, such as enhancingcourse delivery or curriculum revision, and summative uses, including annual facultyevaluations, as well as tenure and promotion decisions. This initiative is a work in progress, withfurther discussions of implementation strategies to come.IntroductionTeaching is at its core the transfer of knowledge (i.e., information) from teacher to learner [1].Thus, success in the engineering
at ASEE in June, suggested that this approach with weeklyquizzes might also show higher grades, as did the ONU research.2 Last fall the practice quizzeswere required, but this semester they are completely optional. The quizzes do form a backstopfor the grades on the weekly quizzes: a student who scores 100% on the three practice quizzesfor the week is guaranteed at least a 50 on the weekly quiz.MethodsThis paper presents exam scores for the fall semesters 2019, 2021, 2022, 2023, and 2024. Thevarying requirements for Statics are shown in Table 1. The elements: ● On-paper homework (OPHW): daily problems were written by the author new each semester. Solutions provided to undergraduate graders who graded each homework. Due the
students inmodeling activities can pique students interest and improve their learning experience [1], [2].Also, SIMIODE [3] provides a rich resource of suggestions and ideas for modeling activities andscenarios.Using Torricelli’s law to model the height of falling water using a first-order differential equation(as in the next section) is frequently taught in the mathematical modeling course at our college. Inthe introductory differential equations course, students are sometimes given the first-orderdifferential equation directly due to the time constraint and the focus of the course is on thetechniques of solving the equations. However, since the objective of the modeling activities is toestimate the parameter in the model, instructors who teach
of English to Speakers of Other Languages (TESOL). ©American Society for Engineering Education, 2025 Work in Progress: Understanding How ECE Senior Undergraduates Perceive Their Strengths and Weaknesses in Individual vs. Collaborative WritingThis paper revisits research begun in a work-in-progress paper published by Barton et al. in the2022 ASEE Annual Conference & Exposition proceedings [1] and presents additional findingsrelevant to that work.Introduction and backgroundIn [1], the authors asked junior- and senior-level engineering undergraduates representing alleight engineering departments within Mississippi State University’s Bagley College ofEngineering to self
learning in higher education.The rapid advancement of these technologies presents both opportunities and challenges foreducators, raising critical questions about the integration of AI into undergraduate classrooms.When systems such as ChatGPT were first introduced, many scholars, such as Noam Chomsky,demonstrated a visceral negative reaction to AI generated text. [1] Generative AI tools were, andlargely still are, seen as a threat to the creative process—ultimately something that academicsshould reject. While these sentiments are perfectly valid, there is a growing body of researchevaluating AI’s benefits. What if there was a way to harness this technology to improve studentengagement and outcomes? Can generative AI personalize learning, automate
assessment, align with industry requirements,and enhance the professional identity of Construction Engineers.Introduction and BackgroundThe construction industry is a critical pillar of economic growth and societal development. Theconstruction sector significantly impacts national economies, from shaping urban landscapes tobuilding essential infrastructure. According to the Bureau of Labor Statistics [1], employment inconstruction-related occupations is projected to grow faster than the average for all fields overthe next decade, creating 663,500 annual job openings from industry growth and retirements.This underscores the rising demand for professionals who have both engineering and projectmanagement skills.Construction Engineering (CONE) programs
-worldapplication enhances educational experience by demonstrating the societal impact of engineeringresearch.KeywordsUndergraduate research, prosthetic hand, actuator, tensile testIntroductionInterdisciplinary undergraduate research provides a great avenue for students to exploreexperiential learning, enrich their academic life, and pursue academic success [1]. Manyengineering problems require a collective effort across multiple disciplines to be solved. It is ofgreat importance to engage students in undergraduate research projects, promote collaborationbetween students majoring in different engineering fields. The four-year undergraduateengineering degree programs at Mercer University School of Engineering have always emphasizedundergraduate research in
and21st centuries, leaving their mark on human history with their levels of innovation and rapidprogress [1]. These fields have not only revolutionized the way we interact with the worldaround us, but have also become attractive career prospects, supplying high-paying opportunitiesand intriguing projects [2].Among the various branches of these disciplines, Computer Vision has recently garneredsignificant attention due to its ability to mimic human-like perception using computingtechnology. By employing algorithms and processing data, it enables machines to comprehendand engage with the visual world. This has broadened the use of computers in fields that aretypically reliant on human visual and processing skills such as transportation
involves characterizing the time response oftemperature sensors. Briefly summarized, the sensor response is characterized by a time constant𝜏 based on the lumped capacitance method of evaluating conduction (a standard topic in heattransfer textbooks, e.g., [1]). In this model, the time response of the mass (i.e., the sensor) isgoverned by the equation 𝜃 𝑡 = exp (− ) (1) 𝜃𝑖 𝜏where 𝜃 represents the difference between the sensor and ambient temperatures, 𝜃𝑖 is the initialtemperature difference, and 𝑡 is time. Time constant 𝜏 is considered to be a function of
Paper ID #45557Boosting Programming Success for Diverse, Large Engineering Classes: Game-BasedVisualization and Phased Assessment in Computing EducationMs. Chaohui Ren, Auburn University [1] Mohamed, Abdallah. ”Designing a CS1 programming course for a mixed-ability class.” Proceedings of the western Canadian conference on computing education. 2019. [2] Shettleworth, Sara J. Cognition, evolution, and behavior. Oxford university press, 2009.Dr. Cheryl Seals, Auburn University Dr. Cheryl Denise Seals is a professor in Auburn University’s Department of Computer Science and Software Engineering. She graduated with a B.S. C.S
in Engineering ClassesIntroductionThe ability to work well in teams is consistently one of the most sought-after skills byemployers, and so deserves serious attention in higher education courses [1]. To evaluate theeffectiveness of any program or module designed to teach teamwork requires a valid assessmenttool. This is particularly important in engineering disciplines which must assess teamwork aspart of their ABET accreditation. Because teamwork assessment is often subjective, it can bedifficult to evaluate rigorously.Assessing the work produced by a team is not necessarily a good indication of the teamworkitself [2]. Peer assessment offers a more direct measurement of teamwork, often done with asurvey of team members. Ideally, surveys
but were not used for mathplacement. There were many studies done prior to the pandemic that considered theeffectiveness of standardized tests and placement tests for math courses. Studies often concludedthat placement tests were not the best predictors of success in math [1].Most STEM majors at VMI, including Civil and Environmental Engineering (CEE), requirecalculus-based mathematics courses. In any given year, up to approximately 40% of cadetsentering the CEE department fail to obtain a 21 or higher on the placement test and are requiredto start in Precalculus. The CEE curriculum has been designed to allow cadets to remain ontrack for graduation in eight semesters even if a cadet is required to start in Precalculus.However, since the
shouldexplore the long-term effects of service-learning programs and identify factors that may enhancetheir impact on mental health.Key WordsService-learning, mental health, well-being, PGWBI, study abroadIntroductionMental health has become a critical global concern, affecting millions of individuals worldwideand influencing societal structures at large. Approximately 14% of the global disease burden hasbeen attributed to neuropsychiatric disorders, primarily stemming from the chronic and disablingnature of conditions such as depression, psychoses, and substance use disorders. These disordersnot only impede individual well-being but also pose significant challenges to public health byperpetuating cycles of poverty and health inequality [1].Poor mental
collection was followed by acomprehensive analysis to determine which specific educational areas would benefit from futureMOM Belize program projects. The main findings were presented to CJC faculty, staff, andstudents in a session where an interactive survey was administered to capture feedback on theeducational areas identified for future projects. Participants were asked to provide their input,suggest additional areas of need, and rank the proposed educational initiatives on a scale from 1to 5, with 1 being the highest priority. Study results indicated that the most critical needidentified by CJC participants was higher education and scholarship training, as well as hands-ontraining of laboratory/field equipment. These findings will guide future