Paper ID #43011WIP: The Impact of Formative Assessment on Students’ Attitude, AnticipatedAcademic Performance, and Design Skills: Insights from Three Design-OrientedElectrical Engineering CoursesDr. Muhammad S Zilany, Texas A&M University at Qatar Dr. Muhammad Zilany earned his Ph.D. in Electrical and Computer Engineering from McMaster University, Ontario, Canada, in 2007. He held academic positions at the University of Malaya and the University of Hail before joining the Electrical and Computer Engineering Program at Texas A&M University at Qatar in 2019. His research focuses on signal processing in the auditory system
Paper ID #45709Work In Progress: Remote FPGA Lab - An Interactive Online Environmentfor Teaching FPGA Development FundamentalsMr. Ze Yang, University Of Toronto A master of engineering student at University of Toronto.Dr. Hamid S Timorabadi P.Eng., University of Toronto Hamid Timorabadi received his B.Sc, M.A.Sc, and Ph.D. degrees in Electrical Engineering from the University of Toronto. He has worked as a project, design, and test engineer as well as a consultant to industry. His research interests include the application of digital signal processing in power systems. ©American Society for
Paper ID #42249Board 97: Work-in-Progress: TextCraft: Automated Resource Recommendationfor Custom Textbook CreationXinyuan Fan, University of Toronto Xinyuan (Elva) Fan is currently pursuing a Master’s degree in Electrical & Computer Engineering at the University of Toronto, following her Honours Bachelor in Computer Science from the University of Waterloo. At the University of Toronto, she worked on a research project focusing on web crawler-driven automated textbook creation. She can be reached at elva.fan@mail.utoronto.ca or elvafan625@gmail.com.Dr. Hamid S Timorabadi P.Eng., University of Toronto Hamid Timorabadi
problems in computer networking algorithms. Currently, her research focuses on developing pedagogical practices to enhance debugging skills for beginner programmers and utilizing natural language processing in engineering education. She believes that engineers learn by doing, which makes her committed to engaging students through in-class activities and problem-solving assignments and projects. She strives to create inclusive learning environments for all students from different backgrounds.Dr. Fatemeh Jazinizadeh, University of TorontoDr. Hamid S Timorabadi P.Eng., University of Toronto Hamid Timorabadi received his B.Sc, M.A.Sc, and Ph.D. degrees in Electrical Engineering from the University of Toronto. He has worked
algorithms to solve problems in computer networking algorithms. Currently, her research focuses on developing pedagogical practices to enhance debugging skills for beginner programmers and utilizing natural language processing in engineering education. She believes that engineers learn by doing, which makes her committed to engaging students through in-class activities and problem-solving assignments and projects. She strives to create inclusive learning environments for all students from different backgrounds.Dr. Hamid S Timorabadi P.Eng., University of Toronto Hamid Timorabadi received his B.Sc, M.A.Sc, and Ph.D. degrees in Electrical Engineering from the University of Toronto. He has worked as a project, design, and
Image Processing and Video Prediction, Neuromorphic Computing Systems and its applications. and Innovation in Engineering Education.Dr. Ahmed Dallal, University of Pittsburgh Dr. Dallal is an assistant professor at the department of electrical and computer engineering, Unversity of Pittsburgh, since August 2017. Dr. Dallal’s primary focus is on education development and innovation. His research interests include biomedical signal processing, biomedical image analysis, and computer vision, as well as machine learning, networked control systems, and human-machine learning.Mr. Mohamed A. S. Zaghloul, Mohamed A. S. Zaghloul was born in Cairo, Egypt, in 1987. He received his B.E. degree in Electronics and Electrical
, and early childhood educa- tion which have been published in scholarly and practitioner journals, including Teachers College Record, Early Child Development and Care, Journal of Educational Research, Young Children, and Teaching Chil- dren Mathematics. At Magnolia Consulting, Dr. Banse leads a portfolio of studies in STEM, early childhood, and prek-20 education products and tools. She is a methodological expert in multiple regression, logistic regression, multilevel modeling, and structural equation modeling, as well as in mixed-method study designs. She also oversees Magnolia’s internship program for BIPOC researchers and evaluators.Dr. Chris S Ferekides, University of South FloridaDr. Carol Haden, Northern
Paper ID #37239Predicting Academic Performance for Pre/Post-Intervention onAction-State Orientation SurveysProf. Ismail Uysal, University of South Florida Dr. Ismail Uysal has a Ph.D. in Electrical and Computer Engineering from the University of Florida. He is an Associate Professor and the Undergraduate Director at the University of South Florida’s Electrical En- gineering Department. His research focuses on theory and applications of machine learning and machine intelligence for sensor applications.Paul E. SpectorDr. Chris S. Ferekides, University of South FloridaMehmet Bugrahan AyanogluRania Elashmawy, University of South
received the Dean’s Achievement Award to recognize his contribution to the Texas A&M-Qatar campus in 2021. He also received the Texas A&M University-STAR Award in 2013 and 2016.Dr. Muhammad S. Zilany, Texas A&M University at Qatar Dr. Muhammad Zilany earned his Ph.D. in Electrical and Computer Engineering from McMaster University, Ontario, Canada, in 2007. He held academic positions at the University of Malaya and the University of Hail before joining the Electrical and Computer Engineering Program at Texas A&M University at Qatar in 2019. His research focuses on signal processing in the auditory system employing a comprehensive approach that integrates computational modeling, physiological recordings
professor (lecturer) in the electrical and computer engineering department at the University of Utah. She completed a PhD focused on engineering education at Stanford University in 2021.Daniel S. Drew, University of UtahJacob A. George, University of Utah ©American Society for Engineering Education, 2024 MATLAB Tool Allowing Wireless Control of Arduino Robot for Early Introduction of Robotics into Curriculum Connor D. Olsen, Amy V. Verkler, Daniel S. Drew, Jacob A. GeorgeAbstractIn modern Electrical Engineering degree programs, MATLAB is often one of the first codingexperiences a student is exposed to. Most introductory robotics courses that combine hardwareand software
Paper ID #39414Power Engineering Curriculum Update with Situative Pedagogy and ConceptMaps as Evaluation ToolDr. Valentina Cecchi, University of North Carolina at Charlotte Valentina Cecchi is an Associate Professor and the Graduate Program Director in the Electrical and Com- puter Engineering Department at the University of North Carolina Charlotte. She received her PhD in electrical engineering from Drexel University in 2010.Dr. Courtney S Smith-Orr, University of North Carolina at Charlotte Courtney S. Smith,PhD is a Teaching Assistant Professor at UNC Charlotte. Her research interests span the mentoring experiences of
Paper ID #39059Take responsibility to understand engineering (TRUE): A qualitativeinvestigation of student’s engineering self-efficacy as a result ofparticipation in a multi-stakeholder programDr. Dhinesh Balaji Radhakrishnan, Purdue University at West Lafayette (COE)Dr. Wilfrido A. MorenoProf. Jennifer Deboer, Campbell University Jennifer DeBoer is currently Assistant Professor of Engineering Education at Purdue University. Her research focuses on international education systems, individual and social development, technology use and STEM learning, and educational environments forDr. Chris S. Ferekides, University of South Florida
Associate Professor with the University of Tennessee, Knoxville, TN, USA. He is also a member of CURENT and a Fulbright Fellow.Francisco Zelaya-Arrazabal, University of Tennessee, Knoxville Francisco Zelaya-Arrazabal is a Ph.D. candidate in Electrical Engineering at the University of Tennessee, Knoxville. He received his B.Sc. in Electrical Engineering from ’Jos´e Sime´on Ca˜nas’ Central American University, El Salvador, and his M.Sc. in Electrical Engineering from the National Autonomous University of Mexico (UNAM), Mexico.Dr. Erick S. Vasquez-Guardado, University of Dayton Erick S. Vasquez-Guardado is an Associate Professor in the Department of Chemical and Materials Engineering at the University of Dayton. Dr. Vasquez
Paper ID #47761Assessing ChatGPT 4o for AI-Assisted Problem Solving in Electric CircuitsTeachingDr. Bin Chen, Purdue University Fort WayneDavid S Cochran, Purdue University Fort WayneJeffrey Andrew Nowak Ph.D., Purdue University Fort WayneGuoping Wang, Purdue University Fort Wayne Guoping Wang, Ph.D. is an Associate Professor in the Department of Electrical and Computer Engineering at Purdue University Fort Wayne. He earned his Ph.D. from the University of Oklahoma in 2003, following a Master’s from Nanjing University and a Bachelor’s from Tsinghua University. Dr. Wang’s research interests include the Internet of Things, edge
of South FloridaDr. Rania Sherif Elashmawy, University of South Florida Dr. Rania Elashmawy has a Ph. D in Electrical Engineering from the University of South Florida, USA. Her research interests include smart agriculture, precision agriculture, and time-series data.Rifatul Islam, University of South FloridaPaul E. Spector, University of South FloridaDr. Chris S. Ferekides, University of South Florida ©American Society for Engineering Education, 2024 Tracking and predicting student performance across different semesters with matched action-state orientation surveys and interventions Ismail Uysal, Mehmet Ayanoglu, Rania Elashmawy, Rifatul Islam, Paul Spector* &
locations. The centralized platform will capture multimedia data (audio, video, text)from the two locations listed above for display and analysis on monitor(s) in the chosen locationand will be used to store the data at regular intervals such as hourly, daily, and weekly recordsfor future retrieval and analysis.Product RequirementsThe product requirements are: 1) Primary or main display monitor setup to provide (a) the overview of each remote location (b) key real-time multimedia data captured. 2) Secondary display of room-level, workbench-level, device-level status from each remote location. 3) Controls to navigate across primary and secondary displays at different visual resolutions/zoom features
Grant that established the Center of Excellence in Signal Integrity at Penn State Harrisburg, a $440K MRI NSF grant, a Volvo industrial grant and DURIP grant.Dr. Sedig Salem Agili, Pennsylvania State University, Harrisburg, The Capital College Sedig S. Agili received his BS, MS, and Ph.D. in Electrical and Computer Engineering from Marquette University in 1986, 1989, and 1996, respectively. Currently he is a Professor of Electrical Engineering teaching and conducting research in signal integrit ©American Society for Engineering Education, 2025 Further Signal Integrity Experiences in Undergraduate Education 1AbstractSignal integrity has been identified as one of the key areas for scientific
Program”, Proceedings of the2020 American Society for Engineering Education conference and exposition, 2020.[3] Hawkins, N., Lewis, J., Robinson, B., and Foreman, J., “Computational Instruction through PLCs in a Multi-Disciplinary Introduction to Engineering Course”, Proceedings of the 2019 American Society for EngineeringEducation conference and exposition, 2019.[4] Otieno, A., and Mirman, C., “A Laboratory Based Programming Logic Controller (PLC) Course for aManufacturing Curriculum”, Proceedings of the 2003 American Society for Engineering Education conference andexposition, 2003.[5] Jack, H., and Rowe, S., “Teaching Industrial Control with Open-Source Software”, Proceedings of the 2023American Society for Engineering Education conference and
/PFE:RED 2234256. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect the views ofthe National Science Foundation. We would also like to thank Redwood Consulting Collectivefor their work in adapting and administering the survey, and our student respondents forcompleting it.References[1] National Science Board, “Science & Engineering Indicators 2016,” National Science Foundation, 2016.[2] K. Beddoes and A. Danowitz, “In Their Own Words: How Aspects of Engineering Education Undermine Students’ Mental Health,” in ASEE 2022 Annual Conference & Exposition, Minneapolis, 2022.[3] A. Danowitz and K. Beddoes, “Characterizing Mental Health and
Sacramento State and by an NSF grant (DUE # 2235774).References [1] C. L. Dym, A. M. Agogino, O. Eris, D. D. Frey, and L. J. Leifer, “Engineering design thinking, teaching, and learning”, J. Eng. Educ., vol. 94, no. 1, pp. 103–120, Jan. 2005. [2] S. Rodenbusch, et al. “Early engagement in course-based research increases graduation rates and completion of science, engineering, and mathematics degrees,” CBE life sciences education, vol. 15, 2016, doi:10.1187/cbe.16-03-0117. [3] C. D. Wilson, J. A. Taylor, S. M. Kowalski, and J. Carlson, “The relative effects and equity of inquiry-based and commonplace science teaching on students’ knowledge, reasoning, and argumentation,” J. Res. Sci. Teach., 2009. [4] C. Katie, M. Blum Michelle, M. Julie, and S.-C. C
intervention. By leveraging these findings, educators, policymakers, and industrystakeholders can work collaboratively to strengthen the talent pipeline and drive innovation inthe semiconductor sector.References[1] A. Deichler, “Help Wanted: Manufacturing Sector Struggles to Fill Jobs,” SHRM, Jun. 2021,accessed: 2023-7-6. [Online]. Available: https://www.shrm.org/topics-tools/news/talent-acquisition/help-wanted-manufacturing-sector-struggles-to-fill-jobs[2] S. Alam, “Addressing the talent gap,” Accenture, Feb. 2023, accessed: 2023-6-30. [Online].Available: https://www.accenture.com/us-en/insightsnew/high-tech/semi-talent-shortage[3] C. Richard, K. Ramachandran, and I. Pandoy, Deloitte, “Looming Talent Gap ChallengesSemiconductor Industry,” Semi.org
(KPIn ) we used in this effort are listed below and we developedfunctions to drive our algorithms in our custom database dashboard. 1. 100% 1st article 2. Inventory each kit 3. On-Time Delivery 4. Percentage of revenueIn equation 1, KPI1 is defined as how much time (T ) it takes to get a final working product that istested. For example, we can compute the time between dates such as physical work start (P W S)date, material procurement dates, 1st article test (1AT ) dates, and final article test dates. KP I1 = TP W S − T1AT . (1)In equation 2, KPI2 is defined as how long it takes to inventory each kit. For example, we candetermine the function by comparing timestamps
, theiracademic records exhibit significant differences that warrant careful consideration. First, directlymatriculated students typically completed ECE 301’s core pre-requisites (such as Physic II andCircuit Analysis) at the focal institution. This provides a detailed record of their proficiency, re-flected through a range of letter grades. In contrast, transfer students often bring in credits for pre-requisites (shown in Figure 3), which are recorded as a “T” (transfer) on their academic records.This limits insights into their knowledge acquisition and retention. Second, the academic record’sability to capture students’ academic histories differs between groups. Transfer credits are recordedin the semester they are recognized by the focal institution
Vin G B S Vin B S B S B G S Fig. 4: The common source amplifier (left) and the resulting bugs from disconnecting thebody (center) and connecting a PMOS gate, drain, and source with the NMOS body (right) Page 1 Page 2
StudiesOur main objective was to find the interventions in circuits education and how they influencedundergraduate students in circuits courses, extracted information could be beneficial to determinewhich papers could be included in the study and which were not relevant or did not offer anyinterventions to students. The information was gathered from reading the title of the paper, theabstract, and the content with a particular focus on methods, discussions, and conclusions of thestudies. In summary, our closed coding scheme was as follows: author(s) and publication year,whether they were used before, during, or after COVID-19, intervention category, interventionsub-category, teaching mode, duration of intervention, and research method. We also
)References 1. Connor K, Kelly J, Scott C, Chouikha M, Newman D, Gullie K, Ndoye M, Dabipi I, Graves C, Zhang L, Osareh A, Albin S, Geddis D, Andrei P, Lacy F, Majlesein H, Eldek A, Attia J, Astatke Y, Yang S, Jiang L, Oni B, Zein-Sabatto S “Experiment Centric Pedagogy – Improving the HBCU Engineering Student Learning Experience,” ASEE Annual Conference, Salt Lake City, June 2018, USA. 2. Connor K, Scott C, Korte R, Sullivan B, Velez-Reyes M “Mini-Workshop Series for Minority Serving Institutions with ECE Programs,” ASEE Virtual Conference 2021 3. Connor K, Scott C, Chouikha M, Leigh-Mack P, Sullivan B, Kelly J, Goodnick S, Smith M, Klein M, Abraham S, Oni B, Ososanya E, Eldek A, Yang S, Erives H, Joslyn C
continue to collect survey data from electrical engineering students(sophomore to senior) and study how the feature rankings change after students go through in-class or Canvas interventions with mini-courses on acquiring better study habits founded uponthe theory of action-state orientation. Our next hypothesis will focus on whether low GPAstudents’ survey responses become more robust predictors of their academic success (asindicated by SHAP summary plots) as they go through such trainings.References Bakoban, R., & Aljarallah, S. (2015). Extracurricular Activities and Their Effect on the Student's Grade Point Average: Statistical Study. Educational Research and Reviews, 10(20), 2737-2744. Borup, D., Christensen, B. J., Mühlbach
more raw data than can be communicated throughlow-power radios; these systems, such as acoustic recorders, may filter, downsample, computefrequency spectra, etc., to reduce the volume of data to be transmitted down to its most salient.The growing popularity of machine learning suitable for edge computing, such as TinyML [5], isalso responsible for some modest computation resident on the wireless sensor node.Applications such as environmental sensing need only sample a single sensor at periods on theorder of hours and report that information to a base station. For wireless sensor systemsrecording environmental analytes, computation here is limited to housekeeping: scheduling andcontrol of sensor(s), temporary local storage, and management of
know and do,” Phi Delta Kappan, vol. 89, no. 2, pp. 140–145, 2007. [6] S. Abramovich, C. Schunn, and R. M. Higashi, “Are badges useful in education?: it depends upon the type of badge and expertise of learner,” Educational Technology Research and Development, vol. 61, pp. 217–232, 2013. [7] F. Khaddage, R. Baker, and G. Knezek, “If not now! when? a mobile badge reward system for k-12 teachers,” in Society for Information Technology & Teacher Education International Conference, vol. 2012, no. 1, 2012, pp. 2900–2905. [Online]. Available: http://www.editlib.org/p/40029 [8] J. L. Santos, S. Charleer, G. Parra, J. Klerkx, E. Duval, and K. Verbert, “Evaluating the use of open badges in an open learning environment,” in