Paper ID #37628Protein Molecules as Robotic Mechanisms: An InterdisciplinaryProject-Based Learning Experience at the Intersection of Biochemistryand RoboticsProf. Alireza Mohammadi, University of Michigan-Dearborn Alireza Mohammadi is an Assistant Professor in the Electrical and Computer Engineering Department at the University of Michigan–Dearborn. He is the principal investigator of the Robotic Motion Intelligence (RMI) Lab, which he established in 2018. He received the Ph.D. degree in Electrical and Computer En- gineering from the University of Toronto, Canada in 2016. During his Ph.D. studies, he collaborated with the
, it supports the creationof personalized medical reports, assists in interpreting medical imaging, and enhances diagnosticworkflows. In journalism, it automates the production of news articles and streamlines editorialprocesses. In education, it facilitates the generation of personalized learning materials andenables the development of interactive teaching aids, thereby enhancing student engagement andunderstanding.ChatGPT (Chat Generative Pre-Trained Transformer) is a notable example of a generative AItool designed to interpret and respond to text inputs based on the Generative PretrainedTransformer (GPT) architecture1. GPTs are large language models (LLMs) trained on extensivedatasets, enabling them to perform tasks such as text generation
dataacquisition, audio processing, and communication systems. Key topics include programming inC, interfacing with analog sensors, real-time debugging, and understanding communicationprotocols like UART. The course also explores system timing, noise analysis, and the use of IDEtools for embedded system design. ECE 48500 – Embedded Real-Time Operating Systemsintroduces students to embedded real-time operating systems (RTOS) with a focus on softwaredevelopment tasks, inter-task communication, synchronization, and network software. Studentslearn to program embedded systems using C and assembly, explore RTOS concepts like taskscheduling and communication mechanisms (e.g., semaphores, mutexes), and design systemsincorporating RTOS. The course also provides
accommodate varying learning paces and allow deeper engagement with complex concepts. ● Resource Allocation: Directing institutional resources toward developing accessible learning materials and adaptive technologies that support diverse learning needs. ● Partnership Development: Establishing collaborative relationships with industry partners committed to neurodivergent inclusion, integrating job coaching and mentorship opportunities into program design.Research and Evaluation FrameworkTo ensure continuous program improvement and contribute to the broader field of inclusive AIeducation, we recommend implementing: ● Longitudinal Assessment: Systematic evaluation of program outcomes through extended timeframes
prestigious journals and international conferences. She was the recipient of the Best Paper Award for three international conferences WASA2009, ChinaCom2016 and ICMIC2019. She has been actively organizing international conferences by serving as TPC chairs, publicity chairs and TPC members. She is an IEEE Senior Member.Dr. Shaobo Huang, University of Saskatchewan Dr. Shaobo Huang received a Ph.D. degree in Engineering Education from Utah State University. She has over eight years of teaching and/or research experience in engineering education. She is currently an Assistant Professor in the Ron and Jane Graham School of Professional Development with a joint appointment in the Department of Mechanical Engineering at the
. Wehave systematically evaluated how advanced LLMs perform on various assessments in our subsetof courses. Our results, though preliminary and covering only a subset of our courses, providevaluable insights into the current capabilities of AI in tackling engineering education tasks. Thesefindings suggest areas where our curriculum may need to evolve to both leverage AI capabilitiesand teach skills that remain uniquely human.The contributions of this work are: 1. An applied methodology for benchmarking LLM performance against engineering course assessments. 2. Initial performance data of an advanced LLM on EE and CpE course materials. 3. Insights into potential curriculum adjustments in light of AI advancements. 4. A framework
, sophomore) and require the students to learn the basics ofprogramming and Arduino syntax, while occurring early enough in the student’s career that theyare introduced to these exciting topics while still discovering their interests [3].In contrast, Electrical and Computer Engineering (ECE) students typically learn C/C++ from theComputer Science department before later learning how to use with a focus on low-levelprogramming of embedded systems [4]. Many ECE departments lack a course with a low barrierto entry that introduces the exciting topics covered in Mechanical Engineering’s mechatronicscourse. Although there has been debate in the academic community about the effectiveness ofusing Arduinos to teach embedded programming, many universities have
machine learning applications; energy management; hybrid energy systems; microgrid protection ©American Society for Engineering Education, 2025 Analysis of the Impact of Tower Footing Impedance on the Low Voltage Ride Through Capability of Wind Farm SystemsIntroductionThis work seeks to integrate the results of technical research into engineering curriculum,thereby closing the divide between research and teaching. The investigation of tower footingimpedance and its influence on LVRT capability will serve as a practical case study forstudents, enhancing their comprehension of wind energy systems. Preliminary research wasdone to analyze the educational impact, utilizing the material in classroom
assignments. They were there, building on each other, and gradually we did it all. Because of the games, I was never worried about the tests, I was confident that I know them and could do them. They made me think, I could eventually do them. Eac h test would help me push myself a bit further, so I would even learn during the tests. I have decided to think about going to graduate school and work on a connection between Electromagnetism and Mechanical Engineering I hated Electromagnetism! I am a circuit and electronics student. This class is required otherwise I would never take it. I did not like this material in Physics. I did well in all parts of Physics II. This part was terrible and confusing. In this class
retention and performance inengineering disciplines such as statics and mechanics [1-4]. Some Universities have addedrecitation hours to several foundation engineering courses or recitation courses have beendesigned to guarantee the recitation hours [1, 4]. In the recitation sessions, no new materials arecovered. Instructors use the recitation hours to answer questions, solve example problems,involve students in cooperative learning. Problem solving recitations offer students more practiceopportunities to correct their own core conceptual understanding and problem-solvingtechniques.Peer instruction [5-10] is also a well-documented pedagogical method to improve students’conceptual performance in engineering courses such as introductory computing
number of students to succeed. The school learning theoryof J. B. Carroll presents a learning theory that undergirds mastery learning, especially flexibilityconcerning the time available for learning. Under Carroll’s theory, learning is based on the ratioof time needed to time spent on learning, with high-aptitude students needing less time. This de-emphasizes the role of innate ability, promotes hard work, and provides guidance for retainingless prepared students in engineering without lowering standards.In the author's approach to mastery learning, no partial credit is given on 75% of test problems,however, students are able to repeat those problems, possibly with some penalty. Students mustdemonstrate mastery of basic material by the end of
model will stillwork because the approach provides a lot of structured guidance and peer support. As opposed to a flippedmodel of active learning where students are expected to watch lecture recordings or read material on theirown before coming to class and then do in-class problem solving, the instructor also goes over the materialin detail in-class in the gradual release model. This provides a good support mechanism for students.While it might be of interest, we can’t say whether the non-native English speakers or disadvantagedstudents will benefit more or less from this intervention. Even though this approach reinforces the conceptsand provides opportunities to learn from peers yet we don’t expect to see much of a difference. This isbecause
users to our framework and measure theperformance overhead associated with scalability.10. References[1] Lin, Y., & Morton, T. D., & Schoeneck, S. C. (2024, June), “Board 84: A Teamwork-based Electrical & Computer Engineering Introductory Lab Course”, 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2—48384[2] Z. Putra and M. Dewi, "The application of problem-based learning in Mechanical Engineering," in IOP Conference Series: Materials Science and Engineering, 2018, vol. 306, no. 1, p. 012140: IOP Publishing.[3] E. A. Van Vliet, J. C. Winnips, and N. J. C. L. S. E. Brouwer, "Flipped-class pedagogy enhances student metacognition and collaborative-learning strategies in
of the physical system. Blockdiagram of the laboratory experiment is illustrated in Figure No.1. ● Preventive and Proactive Cyber-Physical SecurityIn this course, the students will learn and implement a variety of security mechanisms. Studentswill be capable of understanding the costs, benefits, and limitations of security mechanismsdepending on the application, starting with best practices of IT network security, and thenincluding more sophisticated defense mechanisms. Particularly, students will learn the basicprinciples of machine learning and AI to develop supervised and unsupervised applications forthe detection and localization of cyber attacks using cyber and physical data. Students will beexposed to emerging proactive security
is an associate professor of mechanical engineering at Embry-Riddle Aeronautical Uni- versity in Daytona Beach, Fla. Her current research in engineering education focuses on cognitive load theory, deliberate practice, and effective pedagogicalJessica Gonzales, The University of Texas at San Antonio Jessica Gonzales received her MA in Learning, Design, and Technology from the University of Texas at San Antonio (UTSA). She currently works as a Learning Experience Designer with Academic Innovation at UTSA focusing on culture, identity, emergent technologies, and multimodal learning. ©American Society for Engineering Education, 2023Identify Challenges of Inclusive Practices at the Course Level1
material through lectures and readings, and then they are evaluatedindividually [5]. The traditional approach has been especially difficult to sustain in engineeringeducation, as students frequently struggle with complex concepts that require deepcomprehension [5]. Furthermore, conventional lectures may not sufficiently prepare students toeffectively utilize their knowledge and skills in practical situations [5]. The constraints of thisapproach have sparked a significant increase in enthusiasm for collaborative learning strategiesin engineering education, in part aiming to tackle these difficulties and shortcomings [6][7].Collaborative learning represents a pedagogical shift that encourages students to actively engagewith their peers, working
. Dutson et al. [7]reviewed the literature on engineering design in capstone courses. They found that a liaisonengineer from the industry embedded in the capstone was critical to determining the successof the projects. The liaison engineer’s participation was noted to have made the “students feelresponsible and accountable to an industrial customer” (p. 22), an essential learning outcomefor engineering practice. An industry-sponsored mechanical engineering capstone designprogram at Purdue University-Fort Wayne demonstrated quality, practical, and real-worldprojects [8] with an active role taken by industry representatives during the design andevaluation of the projects.Goldberg et al. [9] highlighted the industry involvement via guest lectures
students’ ability to learnfrom their mistakes and improve over time. Without mechanisms for feedback, students miss outon valuable insights that could enhance their understanding and application of engineeringprinciples, particularly when this knowledge is relied upon in future courses.In paper, we report on a study of the alignment between course intended learning outcomes,indicative content, and final examination questions in an electrical circuits course withapproximately 100 students. Examination paper questions were analyzed for their coverage ofthe course intended learning outcomes and indicative content, as well as how these related to thedistribution of marks across questions. Questions were further categorized using Bloom’staxonomy to
multimeter-like hardware that allow DC voltage, current,and power measurements. The measured voltage, current and power values are fetched directly tothe computer during an experiment. Another advantage of using the programmable electronic loadsis that maximum power point tracking (MPPT) algorithms can be implemented easily withoutrequiring any additional hardware. The total estimated cost for all hardware used in thedevelopment of this lab facility was around $5,000. This cost includes materials and supplies, suchas PV modules, aluminum mounting brackets, PV extension cables, marine grade wires, stainlesssteel U-channel posts, concrete blocks, electronic loads, fixed resistor banks, PV combiner boxes,electromechanical relays, MPPT charge controller
, and psychophysical studies. Dr. Zilany developed a computational model of the responses in the auditory nerve for testing our understanding of the underlying mechanical and physiological processes in the auditory periphery, which has been utilized extensively by the prominent auditory neuroscience labs in the field. Dr. Zilany is currently the chair of the ABET and Curriculum committee in the Electrical & Computer program. His commitment to nurturing the next generation of engineers and researchers underscores his role as a mentor and educator. Dr. Zilany is currently a Chartered Engineer with the Institution of Engineering and Technology (IET) in the UK, and he is also a member of the Association for Research
are obvious to the faculty but may bedifficult to comprehend for a student immersed in the activities of a course and the stresses ofcourse deadlines. Reality shows that retention of fundamental information is a challenge for moststudents with only a minority starting with sufficient prerequisite knowledge [1]. It might beleveraged that students benefit from reflection exercises on materials from current and priorterms [2]. The idea of an integrated approach to curriculum design with opportunities for activelearning has been proposed in the past [3–11]. In [3], a mechanical engineering curriculumproposed using a desktop steam engine to help achieve the objectives of curriculum integrationand providing hands-on learning opportunities for
tounderstand the crystal structure of silicon and other materials used, which is vital for growinghigh-quality crystals and controlling their orientation.There have been some industry endeavors to create training courses on these topics. Forexample, Intel, a leading semiconductor chip manufacturer, has partnered with communitycolleges in Ohio to create a one-year semiconductor technician certificate program [5]. A similarprogram is the Semiconductor Technician Quick Start program initiated by the Maricopa CountyCommunity College District (MCCCD) in Phoenix, Arizona.We also note that the semiconductor design company Arm has founded a global initiative titledthe Semiconductor Education Alliance, to develop educational materials, including resources
ofWashington, Seattle, during the Autumn quarter of 2024 as a test case for our initial study. Thiscross-departmental course registered an enrollment of 283 students. Of these, 35% weremajoring in Electrical and Computer Engineering, 50% in Mechanical Engineering, and theremaining 15% were distributed among various other engineering disciplines, such as IndustrialEngineering, Material Science and Engineering, Computer Science, Civil Engineering,Aeronautics and Astronautics, with a small proportion being undeclared engineering majors. Fig. 1. Distribution of Students by Engineering Discipline in EE 215 during Autumn 2024From prior experience and anecdotal feedback, students who participated in AGOH haveexpressed that these sessions were
diverse materials,facilitating the selection of the most appropriate material for their courses and learning goals.Furthermore, TextCraft has an advanced search mechanism powered by a robust search enginethat effectively recommends textbooks. This feature allows users to search by starting with broadtopics and then narrowing the results by selecting more precise subtopics. This approach resultsin targeted and relevant search results, allowing users to efficiently locate the most relevanttextbook materials for their specific educational needs. The process of receiving textbookrecommendations through TextCraft, as shown in Fig. 1 and Fig. 2, starts when users log into theapplication and search for content pertinent to their courses, from broad
Electrical Engineering from Texas A&MDr. Xiaobin Le, Wentworth Institute of Technology Professor, Ph.D, PE., Department of Mechanical Engineering and Technology, Wentworth Institute of Technology, Boston, MA 02115, Phone: 617-989-4223, Email: Lex@wit.edu, Specialization in Computer Aided Design, Mechanical Design, Finite Element Analysis, Fatigue Design, Reliability Analysis. ©American Society for Engineering Education, 2024 PLC in Industrial Controls CourseAbstract:Electrical and computer engineering programs typically help students learn fundamental conceptsand skills, but also desire to help the students become exposed to and learn some industrialapplications. For example, many
while recording reflections to capture initialimpressions and emerging questions. These insights informed the development of a detailed code book.In the second cycle, the coders applied the code book to reassess the data and ensure consistency intheir analyses. The inter-coder reliability was evaluated using Cohen’s Kappa, yielding a score of 0.80,which reflects a high level of agreement and consistency. Five overarching themes emerged from the analysis: (1) student background and preparation, (2)course materials, (3) learning engagement, (4) assessments and outcomes, and (5) teaching methodol-ogy. Theme 1: Student Background and Preparedness The course required prior knowledge of quantum mechanics and quantum physics, creating chal
Delivery,”Technical Session 3659, ASEE 1998 Annual Conference, Seattle, WA, June 28 – July 1, 1998.[2] Alexander, D., & Smelser, R. (1999, June), Overcoming Barriers To Deliver A Quality HandsOn Mechanics Of Materials Laboratory Course At A Distance Paper presented at 1999 AnnualConference, Charlotte, North Carolina. 10.18260/1-2—7875.[3] https://engineering.purdue.edu/virtual-labs, accessed 6 February 2024[4] Ma, G.G., Voccio, J.P., Perkins, D.E., and Greene, T., “Introduction to Engineering VirtualLabs – Challenges and Improvements,” ASEE Virtual Meeting, July 26-29, 2021, Paper ID#34995.[5] Astatke, Y., & Scott, C. J., & Connor, K. A., & Ladeji-Osias, J. O. (2012, June), OnlineDelivery of Electrical Engineering Laboratory
differentconditions. This approach was meticulously designed with Universal Design for Learning (UDL)principles in mind [7], aiming to promote inclusivity and engagement among all students. UDLemphasizes providing multiple means of representation, expression, and engagement to cater todiverse learners, facilitating success in specific tasks and measurable achievements, therebyenhancing overall performance outcomes. Throughout the module, we incorporated theseprinciples by offering students various pathways to access information, express theirunderstanding, and engage with the material effectively. For example, instead of relying solelyon traditional lectures, we began each lesson with hands-on explanations of the sensor devices,followed by data collection
. Based on his experience in working with students and his academic background in electrical engineering, he is trying to find suitable methods of learning for engineering students especially in the electrical engineering field.Mr. Ibrahim Nihad Awartani, University of Cincinnati Ibrahim Awartani is a fresh first-year international doctoral student pursuing Engineering Education in the Department of Engineering and Computing Education at the College of Engineering and Applied Sciences at University of Cincinnati. His bachelors background is a Mechanical Engineering degree from Philadelphia University in Jordan. His masters background is a Master’s of Sciences in Engineering Management. He has had a few years of
are periodic with varying frequency and amplitude. A variety of wave energyconversion (WEC) technologies can be used to harvest the energy of ocean waves. Studentslearn about four types of WEC technologies: point absorbers, attenuators, overtopping devicesand oscillatory water column terminators. Point absorbers extract energy from the rise and fallof waves with a floating buoy. The flexing of attenuators by waves yields mechanical powerfrom a hydraulic motor which is converted to electric power by a generator. In overtoppingdevices, ocean water fills a reservoir which is drained through a hydroelectric turbine similar to ahydroelectric dam. Finally, an oscillatory water column terminator acts as a piston forcing air inand out of a chamber