Paper ID #47248Resetting the Default: Welcoming New Engineering Faculty to Inclusive TeachingProf. David C. Mays, University of Colorado Denver David Mays is an Associate Professor in the Department of Civil Engineering at the University of Colorado Denver. He earned his B.S. from the University of Pennsylvania in 1995, then taught high school through Teach for America and worked as a contractor at Los Alamos National Laboratory before earning his M.S. and Ph.D. from the University of California Berkeley in 1999 and 2005, respectively. He has been at CU Denver since 2005, where he teaches fluid mechanics and hydrology
during the COVID-19 pandemic has spotlighted the need forflexible instructional strategies that accommodate remote settings without sacrificingeducational quality.In engineering curricula—particularly in fluid mechanics and thermodynamics courses—therehas been a longstanding reliance on laboratory-based, hands-on experimentation [17]. However,the recent shift to virtual simulations and digital resources has prompted questions about therelative efficacy of these modalities compared to traditional physical interactions [10, 14]. As in-person classes resumed, it became crucial to evaluate how these different instructional methodsimpact student engagement and learning outcomes [1, 5].The present study addresses this need by systematically examining
successful in their careers. Mastery learning is a promising approach for enablingmore students to succeed without lowering standards.References[1] B. S. Bloom, “Learning for Mastery. Instruction and Curriculum.” Regional Education Laboratory for the Carolinas and Virginia, Topical Papers and Reprints, Number 1,” Evaluation Comment Vol. 1 No. 2, May, 1968.[2] J. B. Carroll, “A Model of School Learning,” Teachers College Record, 64(8) , p. 723-733, 1963. https://doi.org/10.1177/0161468163064008[3] A. Essa, S. Mojarad, S. “Does Time Matter in Learning? A Computer Simulation of Carroll’s Model of Learning” in R.A. Sottilare, J. Schwarz, Eds. Adaptive Instructional Systems. HCII 2020. Lecture Notes in Computer Science, vol 12214
forunderrepresented groups in STEM [19, 20].Course Structure:A traditional lecture-based introductory Materials Science and Engineering course oftenincorporates laboratory activities such as XRD experimentation, tensile testing, and hardnesstesting. While these activities offer valuable hands-on experience, they are typically pre-designed,limiting student engagement in experimental design and data analysis. Even final projects, whichmay require students to design experiments, frequently lack a focus on computational modeling—a critical skill in modern engineering. It should also be noted that this is the introductory levelMaterials Science course with pre-requisites of Calculus III, Chemistry, and at least anintroductory level of programming course (either
conducted inthis study, provide students with practical exposure to welding principles, material science, andmechanical testing. Being engaged in experimental work allows students to bridge theoreticalknowledge with real-world applications, strengthening both their problem-solving and analyticalskills. The insights gained from this research not only contribute to technical advancements inspot welding but also highlight the role of laboratory-based learning in engineering education. While spot welding of similar materials such as two sheets of 1008 carbon steel isstraightforward, introducing an intermediate layer can enhance or hinder the weld properties,depending on the intermediate material and application of the finished piece. This
, laboratories, and practical internships. Mr. Halkiyo has been teaching different Civil Engineering courses at Bule Hora University, Ethiopia, where he also served as a department head and conducted various research and community projects.Sultan Bedane Halkiyu Sultan Bedane Halkiyu pursued his Master of Science degree in Road and Transport Engineering and Bachelor’s degree in Civil Engineering at Hawassa University (2017) and Jimma University (2015) respectively. Mr. Halkiyu is working as a lecturer at Bule Hora University, Ethiopia, and teaching different Civil Engineering courses. He is a mixed methods researcher and pursuing his research interests: quality of road construction, and transport/traffic mobility in urban
skills includingreasoning, creativity and open problem solving . The learners experience difficulty understandingthe basic knowledge and skills in understanding physics. Lecture classes, problem-solvingsessions, and laboratory activities deliver these fundamental physics topics to learners. The lackof organization creates many difficulties in the comprehension of basic concepts and in solvingcomplex problems. This leads to the common complaint that students' knowledge of physics isreduced to formulas and labels of the concepts, which are unable to significantly contribute tomeaningful reasoning processes [4]. To address students’ learning difficulties in physics, the subject needs to be made enjoyableand the learning content needs to be
Laboratory at Texas A&M University, a state-of-the-art facility for education and research in the areas of automation, robotics, and Industry 4.0 systems. He was named Honorary International Chair Professor for National Taipei University of Technology in Taipei, Taiwan, for 2015-21. Dr. Hsieh received his Ph.D. in Industrial Engineering from Texas Tech University, Lubbock, TX. ©American Society for Engineering Education, 2025 Incorporating Hybrid Virtual Simulators and Physical Tools for Angle Measurement in High School GeometryAbstractUnderstanding geometric angles is crucial for students, as angles are the basis for more advancedmathematical concepts and real-world
Students,” Preminente.[17] Barell, J. (1995). Critical issue: Working toward student self-direction and personal efficacy as educational goals. Naperville, IL: North Central Regional Educational Laboratory. Retrieved September 12, 2005.[18] Huitt, W. (1999). Conation as an important factor of mind. Educational psychology interactive, 9.[19] Boyatzis, R. E. (2006). An overview of intentional change from a complexity perspective. Journal of management development.[20] Yeager, D. S., & Walton, G. M. (2011). Social-psychological interventions in education: They’re not magic. Review of Educational Research, 81(2), 267-301.
requires future engineers to learn and master the essential elements of thesedomains during their undergraduate curriculum. However, the electrical and computerengineering curricula is still catching up with the rapid growth in technology. Many institutionsof higher education lack adequate laboratory facilities and expert faculty in this area. It isessential that the emerging field of machine learning be integrated into the electrical andcomputer engineering curricula. The following are examples of how various universities areintegrating machine learning into their curricula.Loyola Marymount University (LMU)At LMU, to introduce ML concepts to freshman engineering students, they have combined activelearning and authentic learning into an
partners,and regional innovation ecosystem organizations such as incubators and accelerators. Industrymentoring is performed as a volunteer activity with low demands on their time, and mostactivities are performed via video conferencing for greater reach and engagement.Customer Discovery Interview Utilizing a Flipped Classroom PedagogyAs part of the Innovation Fellows Program, the fellows receive specialized customer discoverytraining tailored for biomedical scientists and engineers. This training builds from the U.S. NSFI-Corps Program launched in 2011. I-Corps is to prepare “scientists and engineers to extend theirfocus beyond the laboratory to increase the economic and societal impact of NSF-funded andother basic research projects” [16]. This
future activities. The program adopted a multi-pronged approach to mentorship andresearch training, incorporating varied research environments to support students’ academic andprofessional development. In 2019, an additional faculty-student research model wasimplemented, where students were sent to national laboratories alongside faculty mentors for animmersive three-month research experience. This provided students with direct exposure tocutting-edge research, interdisciplinary collaboration, and real-world STEM applications.However, due to funding redirection, this component was discontinued in subsequent years.All mentors were selected based on their research expertise, mentoring experience, andwillingness to participate in the program. All
engineering concepts such asthermodynamics and mechanics who had cited that their methods of delivery are based onexperience and the general situation of student's receptiveness in learning. As Alfred noted,“Teaching thermodynamics is about understanding core principles; AI doesn’t change that.”Others in the Sciences fields have stated that with technological progression, AI image analysingsoftware and tools have been integrated for practical laboratory sessions, providing students witha better visualisation of their analysis. As Edward remarked, “For practical lab sessions, AI helpsstudents visualize their analysis better,” illustrating AI’s role in enhancing experimental learningexperiences. Non-STEM instructors were more open to AI’s role in
data between institutions, and promotion ofa sense of belonging in students [3], [13], [14], [16], [17], [18]. Additionally, GE@SF includesshared investment in student support services, physical collaboration and laboratory spaces onthe SF campus; UF faculty engagement and instruction at SF; and high-impact experientiallearning [19], [20]. Details of program structures are discussed below. These structures, whichrequired 4 years of careful collaborative planning between the two institutions, allow SF and UFto establish meaningful relationships, guidance, and support of students two or more years beforematriculation on the UF campus.Academic Transition and Support StructuresTo assist with the academic transition from high school to SF and from
?BackgroundProgram Context The broader project involved a partnership between a small Mid-Atlantic college and aNortheastern educational non-profit to design and execute an innovative, immersive engineeringeducation “study away” program. The focus on the pilot semester in Fall 2023 was to deliver aninnovative hands-on engineering curriculum and allow students to engage in career exploration.On the curriculum side, this was conducted through project-based learning and mastery-assessment. Students took five engineering courses during the semester including: CircuitsAnalysis, Circuits Analysis Laboratory, Statics, Calculus III, and Physics II. On the careerexploration side, the students engaged in site visits, called “career treks,” to local
Paper ID #45878Creating Public Resources to Diversifying Content in Mechanical Engineering:Fostering Awareness and Ethical ConsiderationsDr. Siu Ling Leung, Pennsylvania State University Dr. Siu Ling Leung is an Associate Teaching Professor, the Associate Head for Undergraduate Programs, and the Director of Undergraduate Laboratories in the Mechanical Engineering Department at Pennsylvania State University. Her work focuses on renovating the engineering curriculum to enhance students’ cognitive skills, raise awareness of diverse problems around the world, and equip them to address real-world challenges. She employs
12 years. He is married with two children.Dr. Theodore Orrin Grosch, Kennesaw State University Dr. Grosch earned his BSEE in 1982, MSEE in 1987, and Ph.D. in Electrical Engineering at The Pennsylvania State University in 1993. He have worked at Hughes Aircraft, General Electric, M.I.T. Lincoln Laboratory two start-ups. Dr. Grosch has taught at UnivDr. Austin B. Asgill P.E., Kennesaw State University Dr Austin B. Asgill received his B.Eng.(hons) (E.E.) degree from Fourah Bay College, University of Sierra Leone, his M.Sc. (E.E.) degree from the University of Aston in Birmingham, and his Ph.D. in Electrical Engineering from the University of South Florida. He is currently a Professor of Engineering Technology
semester, the final design was reviewed and approved, and a constructionpermit was granted by the Pikes Peak Regional Building Department. The remainder of thespring semester was focused on the procurement of materials and construction activities. Theteam prefabricated some portions of the bridge, such as the abutment formwork and the railingposts, on campus in a laboratory environment but completed most of the construction on site.The bridge was completed prior to the end of the semester at a cost of just under $12,000. About30 members of the town, including the mayor, attended a ribbon cutting ceremony to “officially”open the bridge at the end of April 2024. A few images of the construction process and thecompleted bridge are shown
Paper ID #48595Development of a Virtual Reality Game to Enhance Understanding of 3Dproblems in Engineering Mechanics StaticsMr. Osama Desouky, Texas A&M University at Qatar Osama Desouky is a Technical Laboratory coordinator at Texas A&M University in Qatar. Osama is currently pursuing his Ph.D. in interdisciplinary engineering from Texas A&M University at College Station. He is responsible for assisting with experimental method courses, 3D printing, mechanics of materials, material science, senior design projects, and advanced materials classes. Osama’s professional interests include manufacturing
Engineering at Iowa State University. Her research group iMED (Interdisciplinary Manufacturing Engineering and Design) laboratory specializes in research to design scalable hybrid manufacturing techniques of a wide array of material systems ranging from biopolymers, metal alloys, and concrete. Her research expertise is in additive and hybrid manufacturing processes, and biomanufacturing. Applications of her research extend to applications ranging from in-situ nondestructive testing of manufacturing processes to design of Additive Manufacturing alloys for aerospace and biomaterials for tissue engineering. She was a fellow at NASAs Marshall Space Flight Center. She has over 100 peer-reviewed publications and over 100
, tosupport student writing and plain language skills. Students were assigned several major writingassignments in the class, including: a variety of laboratory writeups, including 3 traditional “experiment” type writeups, and 3 “field report” type writeups based around field trips to a wastewater treatment plant, a drinking water treatment plant, and a waste-to-energy plant; a 2-page (approximately 750-1000 words) ‘white paper’ regarding an environmental regulation; and a 5-6 page (at least 2000 words, before references) ‘research paper’ regarding an environmental engineering topic of the student’s choosing.The librarian visited the class early in the semester to review how to use the library’s website
Paper ID #48147Democratizing the Analysis of Unprompted Student Questions Using Open-SourceLarge Language ModelsBrendan Lobo, University of Toronto An MASc candidate in the Integrative Biology and Microengineered Technologies Laboratory at the University of Toronto.Sinisa Colic, University of Toronto Sinisa Colic is an Assistant Professor, Teaching Stream with the Department of Mechanical and Industrial Engineering. He completed his PhD at the University of Toronto in the area of personalized treatment options for epilepsy using advanced signal processing techniques and machine learning. Sinisa currently teaches
-Menéndez, A. Vallejo Guevara, J. C. Tudón Martínez, D. HernándezAlcántara, and R. Morales-Menéndez, “Active learning in engineering education: A review offundamentals, best practices, and experiences,” International Journal on Interactive Designand Manufacturing (IJIDeM), vol. 13, pp. 909–922, 2019.21. L. Zhang and Y. Ma, “A study of the impact of project-based learning on student learningeffects: A meta-analysis study,” Front. Psychol., Sec. Educational Psychology, vol. 14, Jul.2023.22. M. J. Zhang, C. Newton, J. Grove, M. Pritzker, and M. Ioannidis, “Design and assessmentof a hybrid chemical engineering laboratory course with the incorporation of student-centredexperiential learning,” Education for Chemical Engineers, vol. 30, pp. 1–8, 2020.23
, 2011. [8] Linda B Nilson. Specifications grading: Restoring rigor, motivating students, and saving faculty time. Stylus Publishing, LLC, 2015. [9] Kate J McKnelly, William J Howitz, Taylor A Thane, and Ren´ee D Link. Specifications grading at scale: Improved letter grades and grading-related interactions in a course with over 1,000 students. 2022.[10] William J. Howitz, Kate J. McKnelly, and Ren´ee D. Link. Developing and implementing a specifications grading system in an organic chemistry laboratory course. Journal of Chemical Education, 98(2):385–394, 2021. doi: 10.1021/acs.jchemed.0c00450.[11] Dennis Earl. Two years of specifications grading in philosophy. Teaching Philosophy, 45(1):23–64, 2022.[12] Ella Tuson and Tim Hickey
research in the Hatton group at MIT before joining the faculty of Chemical Engineering at Virginia Tech in 2006. Dr. Martin’s research focuses on advanced materials and processes for separations, including water purification and carbon capture. The Martin group’s research has been funded by the National Science Foundation, the Department of Energy, the ACS-Petroleum Research Fund, 3M, and the Office of Naval Research. Dr. Martin has taught across the chemical engineering curriculum, including Mass & Energy Balances, Fluid Dynamics, and Mass Transfer. He has directed the Chemical Engineering Unit Operations Laboratory at Virginia Tech since 2007. He has been the recipient of multiple teaching awards, including the
PlatformThe grading platform was tested on two sets of 50 assignments graded by the GPT-4 and Qwen.AI-generated grades were compared with the human-graded benchmarks. Figure 4 shows the meanscores and variability (mean ± standard deviation) for Labs 2 and 5, with human scores serving asthe reference for comparison. In Lab 2, the human reference mean was 16.89, with Qwen scoring16.07 and GPT-4 scoring 15.72. Qwen's score was closer to the human reference, indicating betterperformance than GPT-4 in this laboratory. In Lab 5, the human reference mean was 20.44, andQwen achieved a mean score of 22.67, whereas GPT-4 scores were 21.17. Although both LLMsscore higher than the human reference, GPT-4's score is closer, suggesting that it performs betterthan
laboratory courses, they do not necessarilyapply spreadsheets in an engineering context.To better align spreadsheets with the practical experiences of civil engineering students [1], aseries of statics-related assignments were incorporated into a second-year civil engineeringcourse at Saint Louis University, Missouri, United States. Students utilized spreadsheets to solveproblems related to centroids and moments of inertia, equilibrium of a particle, shear force andbending moment diagrams, and truss analysis. Most students were concurrently enrolled in astatics course where they solved similar problems using pen and paper calculations andsubmitted their work.This research assessed student work, evaluated learning outcomes, and analyzed
research study, where we will recordoutdoor temperature and barometric pressure alongside other experimental parameters.References [1] Peter Dunne. “Demonstrating Cosmic Ray Induced Electromagnetic Cascades in the A- Level Laboratory.” 1999 Phys. Educ. 34 19 [2] Frederiksen Scientific. “The Interaction Between Cosmic Rays and Matter”. https://www.frederiksen-scientific.dk 2017-01-18 [3] American Society for Quality. https://asq.org Richard Boddy, “Statistical methods in practice: for scientists and technologists”, (2009), John Wiley and Sons, ISBN 978-0-470- 74664-6 [4] Bruno B. Rossi’s work is described in a Wikipedia article: http://en.wikipedia.org/wiki/Bruno_Rossi. [5] Navitski, P., Gregg, E. “Physics teaching at Oral
Practices Research into effective mentoring practices reveals that successful mentoring programsshare key components, including structured training for both faculty mentors and students alongwith adequate resources including funding and research space. In the current study, the process ofimplementing effective mentorship is broken down into planning and execution phases. During UR mentoring, faculty mentors are involved in a broad range of activities, as notedby Brace et al. [18]. These include setting project expectations and timelines, introducing studentsto laboratory settings, discussing career opportunities, managing resources, teaching scientificresearch methods, holding weekly progress meetings, guiding students to prepare
; Universidad Andres Bello, Santiago,Chile Dr. Genaro Zavala is Associate Director of the Research Laboratory at the Institute for the Future of Education, Tecnol´ogico de Monterrey. He collaborates with the School of Engineering of the Universidad Andr´es Bello in Santiago, Chile. A National Researcher Level 2 (SNI-CONACYT), he has over 20 years of experience in educational research. His work spans conceptual understanding in physics, active learning, AI in education, and STEM interdisciplinarity. He leads initiatives on faculty development, competency assessment, and technology-enhanced learning. With 100+ publications, he integrates educational psychology, digital transformation, and sustainability. Dr. Zavala also