., [1999]. "Static and Dynamic Configurable Systems," IEEE Trans. On Computers, Vol. 48, Issue. 6, pp. 556-563, June 1999. 7Author biographiesSYED S. RIZVI is a Ph.D. student of Computer Engineering at the University of Bridgeport. He received a B.S. inComputer Engineering from Sir Syed University of Engineering and Technology and an M.S. in ComputerEngineering from Old Dominion University in 2001 and 2005 respectively. In the past, he has done research onbioinformatics projects where he investigated the use of Linux based cluster search engines for finding the desiredproteins in input and outputs sequences from multiple databases
processingis becoming an integral part of science and engineering for this very reason: visualizationaids immensely in the understanding of large data sets. Furthermore, an intuitiveunderstanding of abstract systems-related topics such as convolution and Fouriertransform theory can be acquired when these algorithms are applied to images. Often,these concepts are taught to electrical engineering students in a signals and systems coursewhich deals exclusively with 1-D signals. However, the data smoothing effect of a lowpassfilter can be better visualized by comparing an input image to the corresponding blurryfiltered image. Similarly, seeing the edges detected by a 2-D highpass filter applied to animage is a far more dramatic visual effect than that
Paper ID #10842Mapping the curriculum around student learning outcomes and assessmentof learningDr. Ihab Mohammad Hamdi Saad P.E., Northern Kentucky University Dr. Ihab Saad is Department Chair and Professor of Construction Management and an alumnus of the University of Kentucky in Lexington where he received his Ph.D. in 1996 from the department of Civil Engineering and Construction. He has over 25 years of experience in the construction industry primarily in the civil/construction project management area. Dr. Saad received his Bachelor of Science and Master’s degrees in Civil Engineering from Cairo Uni- versity in
thin edges in low-contrast regions”, Image Processing, The [18] J. A. Sethian. “Level Set Methods and Fast Marching Methods: Institution of Engineering and Technology (IET), vol. 1, no. 3, pp. Evolving Interfaces in Geometry, Fluid Mechanics, Computer 269-277, 2007. Vision and Materials Sciences,” Cambridge Univ. Press, 1996[11]S. Narita, K. Asakura, and A. Kataura, ” Effects of thromboxane [19] D. Enright, F. Losasso, and R. Fedkiw, “A fast and accurate A2 receptor antagonist (Bay u 3405) on nasal symptoms after semi-lagrangian particle level set method, ” ACM Computer and antigen challenge in sensitized guinea pigs,” Int. Arch. Allergy
ASEE 2014 Zone I Conference, April 3-5, 2014, University of Bridgeport, Bridgeport, CT, USA. On the Mutual Information of Sensor Networks in Underwater Wireless Communication: An Experimental Approach Raju Shrestha, Mahmoud Elsayed Dr. Paul Cotae Department of Electrical and Computer Engineering Department of Electrical and Computer Engineering University of the District of Columbia University of the District of Columbia Washington, DC 20008 Washington, DC 20008
the mind of Brutus, a StoryTelling Machine," Lawrence Erlbaum Associates, Hillsdale, NJ, 1999.[9] A. Badiru and J. Cheung, Fuzzy Engineering Expert Systems with Neural Network Applications, Wiley-Interscience, 2002, p. Chapter 2 Fundamentals of Experts Systems.[10] A. L. Za and G. J. Nalepa, "A study of methodological issues in design and development of rule-based systems," WIREs - Data Mining and Knowledge Discovery, Vols. Volume 1, March/April, pp. 117 - 137, 2011.[11] "Wordnet - A lexical database for English," Princeton University, [Online]. Available: http://wordnet.princeton.edu/. [Accessed 02 February 2014][12] "ConceptNet 5," Massachusetts Institute of Technology, [Online
specialized and directed than most collegiate content,allowing for more input from industrial employers of students [4] [5]. A stated need of the agencyfunding this effort was to improve the employability of graduating students on “day one,”providing skill training that would allow the new students to contribute meaningfully and quicklyupon hire, minimizing onboarding training needed. As practices and theories used in engineeringand industry change rapidly as new manufacturing technologies develop, micro-credentialpathways are set to emerge as an agile and rapid way to address these skill gaps as they emergefor graduating and mature workers. [4] While several undergraduate programs in engineering andtechnology at the University of Maine provide
Paper ID #49042WIP: Integrating Student-developed Applications and In-class Learning Gamesto Optimize Learning Outcomes: A Case Study in An Introductory StatisticalLearning and Programming CourseProf. Heze Chen, University of Virginia Heze Chen is an assistant professor in the Center for Applied Mathematics at the University of Virginia, USA, since the August of 2023. He is involved in teaching several applied mathematics courses at the School of Engineering and Applied Science. His research focuses on enhancing the mathematical learning experience for engineering students and developing numerical simulation methods in
Paper ID #32929WIP: Detection of Student Misconceptions of Electrical Circuit Conceptsin a Short Answer Question Using NLPProf. James P Becker, Montana State University, Bozeman James Becker is a Professor of electrical and computer engineering at Montana State University. His pro- fessional interests include microwave circuits, radio frequency electronics, nanoelectronics, pedagogical research, and distance education.Dr. Indika Kahanda, University of North Florida Dr. Indika Kahanda is an Assistant Professor in the School of Computing at the University of North Florida, where he directs the bioinformatics, biomedical
Paper ID #17853verilogTown - Improving Students Learning Hardware Description LanguageDesign - Verilog - with a Video GameDr. Peter Jamieson, Miami University Dr. Jamieson is an associate professor in the Electrical and Computer Engineering department at Miami University. His research focuses on Education, Games, and FPGAs. c American Society for Engineering Education, 2017 verilogTown - Improving Students Learning Hardware Description Language Design - Verilog - with a Video Game Abstract In this work, we present our game
Paper ID #18834FEAL: Fine-Grained Evaluation of Active Learning in Collaborative Learn-ing SpacesMs. Sixing Lu, University of Arizona Sixing Lu is a PhD candidate of Electrical and Computer Engineering department of University of Ari- zona.Prof. Loukas Lazos, University of Arizona Loukas Lazos is a faculty member of the Electrical and Computer Engineering Department at the Univer- sity of Arizona. Before joining the University of Arizona, he was a co-director of the Network Security Lab at the University of Washington. He received my PhD. and M.S. degrees in Electrical Engineering at the University of Washington. he
into Computer and Electronics Engineering Programs. A final evaluation report for the National Science Foundation. 3. Gilmore, Chen, and Grandgenett, “Using Robotics to Equip K-12 Teachers: The Silicon Prairie Initiative for Robotics in Information Technology”, ASEE 2009 4. Gilmore, Detloff, “Assessing Senior Student Experiences with a Novel Mobile Robotics Learning Platform in a Computer and Electronics Engineering Program”, ASEE 2010 5. Gilmore, Santos, and Mills, “Computer Interface Innovations for an ECE Mobile Robotics Platform Applicable to K-12 and University Students”, ASEE 2011-2200 6. Chen, B., Grandgenett, N., Ostler, E., “Silicon Prairie Initiative for Robotics in Information
Paper ID #6480Feeling Like a Grad Student: A Survey of Undergraduate Researchers’ Ex-pectations and ExperiencesDr. Katy Luchini-Colbry, Michigan State University Katy Luchini-Colbry is the Director for Graduate Recruiting at the College of Engineering at Michigan State University, where she completed degrees in political theory and computer science. A recipient of a NSF Graduate Research Fellowship, she received her Ph.D. and M.S.E. in computer science and engineering from the University of Michigan. She has published nearly two dozen peer-reviewed works related to her interests in educational technology and enhancing
acrossdifferent entities within an institution and across institutions. To increase skills in data analysisfor staff and faculty, our institution, The University of Texas at El Paso (UTEP), started aninitiative to institutionalize the systematic use of data and knowledge to develop and implementinitiatives designed to increase the success of students in Science, Technology, Engineering, andMathematics (STEM) disciplines, particularly those from underserved communities. Theories ofchange note the complex set of factors that influence such outcomes [1] [2]. Our institutionidentified key progress metrics related to STEM programs and began diagnosing emergent issuesthat arose from data analysis. In addition, UTEP administers a student climate survey with
. Huang, Shaobo, and Ning Fang. “Predicting Student Academic Performance in an Engineering Dynamics Course: A Comparison of Four Types of Predictive Mathematical Models.” Computers and Education, vol. 61, 2013, pp. 133–45 11. Howard, E., Meehan, M., & Parnell, A. (2018). Contrasting prediction methods for early warning systems at undergraduate level. The Internet and Higher Education, 37, 66–75 12. Ben Said, M., Hadj Kacem, Y., Algarni, A., & Masmoudi, A. (2024). Early prediction of Student academic performance based on Machine Learning algorithms: A case study of bachelor’s degree students in KSA. Education and Information Technologies, 29(11), 13247–13270. 13. Parmar, A., Katariya, R., Patel, V
Session NO. 2642 How to Initiate Dialogue in Student Research Teams Bonnie D. Burrell and Clark K. Colton Department of Chemical Engineering Massachusetts Institute of Technology, Cambridge, MA 02139AbstractIn the process of integrating teambuilding training into a chemical engineering projectslaboratory, we concluded that a pedagogical tool was needed to move the student teams throughthe early team life cycle and communication stages in order to create the needed trust to begineffective communication. The tool we developed consists of two parts: (1) an
necessarily reflectthe views of the National Science Foundation.References [1] G. Herman, K. Varghese, and C. Zilles, “Second-chance testing course policies and student behavior,” in 2019 IEEE Frontiers in Education Conference (FIE). IEEE, 2019, pp. 1–7. [2] C.-L. C. Kulik and J. A. Kulik, “Mastery testing and student learning: A meta-analysis,” Journal of Educational Technology Systems, vol. 15, no. 3, pp. 325–345, 1987. [3] C. D. Schmitz, G. L. Herman, and T. Bretl, “The effects of second-chance testing on learning outcomes in a first-year stem course in engineering,” in 2020 ASEE Virtual Annual Conference Content Access, 2020. [4] G. L. Herman, Z. Cai, T. Bretl, C. Zilles, and M. West, “Comparison of grade replacement and weighted
in a number of K-20 educational initiatives designed to increase and broaden participation in STEM fields.Carissa B. Schutzman (Senior Research Associate)Keren Mabisi © American Society for Engineering Education, 2022 Powered by www.slayte.com Description, assessment, and outcomes of three National Science Foundation Research Traineeship (NRT) components: transferable skills course, interdisciplinary research proposal and project, and multidisciplinary symposium1. IntroductionThe University of Kentucky (UK) NRT aims to enhance graduate education by integratingresearch and professional skill development within a diverse
Paper ID #29852Usability of Data Visualization Activity Worksheets in the Context of aCritical Data Visualization Workshop: Findings from a Usability SurveyDr. Vetria Byrd PhD, Purdue University-Main Campus, West Lafayette (College of Engineering) Dr. Vetria Byrd is an assistant professor in the Department of Computer Graphics Technology in the Polytechnic Institute at Purdue University in West Lafayette, Indiana. Dr. Byrd is the founder and orga- nizer of the biennial Broadening Participation in Visualization (BPViz) Workshop. Dr. Byrd has given numerous invited talks on visualization and has been featured in HPC Wire online
Developing Strategies to Improve Student Engagement, Learning and Enjoyment of Introductory Computer Science CoursesProfessor Heather Marriott – Computer, Electrical and Software Engineering DepartmentEmbry-Riddle Aeronautical UniversityAbstract - Introductory computer science courses have traditionally been taught using a lecture-based style, and this is perpetuated by the computer science community continuing to teach inthe style in which they were taught. While educational research has proven the effectiveness ofactive learning in the classroom, many computer science professors find it difficult in incorporatethese techniques into their classrooms. Today’s generation of students get bored quickly with thetraditional
Paper ID #243622018 ASEE Mid-Atlantic Section Spring Conference: Washington, District ofColumbia Apr 6Geothermal Heating/Cooling in Massachusetts General HospitalZoe Zyvith, Rutgers UniversityMr. Mark Thomas Trevena, Rutgers University Student in the Department of Industrial and Systems Engineering at Rutgers University-New Brunswick. Has conducted research in the past on safety risk modeling of unmanned air systems through NASA/NJ Space Grant Consortium fellowship program.Andrew YongMr. Ryan LamantiaMiss Lana E Sharp, Rutgers UniversityDr. Sasan Haghani, University of the District of Columbia Sasan Haghani, Ph.D., is an
physics lab report writing and undergraduate research paper writing.I. IntroductionThe City University of New York instituted a writing intensive component in its curriculummore than ten years ago. Queensborough Community College (QCC), being a junior college inthe CUNY System, requires two writing intensive courses for graduation. Our PhysicsDepartment has designated Calculus Physics and Technology Physics classes as writingintensive classes where lab report writing is a substantial element 1. A quick review of the 2014high school SAT score shows that Engineering majors have higher critical reading scores whencompared to English majors, while English majors have higher writing scores when compared toengineering majors 2, 3. The result would
embedded systems, runtime optimization, non-intrusive system observation methods, data-adaptable systems, and embedded system security. He has recently coauthored multiple textbooks, published by zyBooks, that utilize a web-native, interactive, and animated approach, which has been shown to increase student learning and achievements.Dr. Susan Lysecky, zyBooks Susan received her PhD in Computer Science from the University of California, Riverside in 2006. She served as a faculty member at the University of Arizona from 2006-2014. She has a background in design automation and optimization for embedded systems, as well as experience in the development of accessi- ble engineering curricula and learning technologies. She is
Paper ID #15023Engaging Students in Authentic Research in Introductory Chemistry and Bi-ology LaboratoriesDr. Julianne Vernon, University of Michigan Julianne Vernon is a Research Program Officer at the University of Michigan, the College of Literature, Science, and Arts where she is coordinating the implementation of faculty led research projects into introductory chemistry and biology lab courses. She received her bachelors of engineering in chemical engineering from the City College of New York and her doctorate degree at University of Florida in Environmental Engineering. She has experience developing international
Paper ID #27796Diversifying Pathways in Cybersecurity through the Design of Holistic Com-petitionsDr. John Y Oliver, California Polytechnic State University, San Luis Obispo Dr. Oliver is an assistant professor of Electrical Engineering and Computer Engineering and the director of Computer Engineering at Cal Poly, San Luis Obispo. His field of expertise is in computer architecture and system performance analysis with a growing interest in cybersecurity. His teaching activities focus on embedded systems and digital circuit design.Cassidy Elwell, Cal Poly, San Luis Obispo c American Society for
AC 2008-570: BIOFUELS IN THE CLASSROOM: USING THE BIODIESELPROCESS TO DEMONSTRATE CHEMICAL AND PHYSICAL PRINCIPLESRoger Beardsley, Central Washington University Roger Beardsley is an assistant professor of Mechanical Engineering Technology at Central Washington University, Ellensburg WA. His interests include many of the renewable energy technologies, with biodiesel processing as his current primary research topic. Page 13.252.1© American Society for Engineering Education, 2008 Biofuels in the Classroom: Using the Biodiesel Process to Demonstrate Chemical and Physical PrinciplesAbstractGlobal
AC 2007-356: CUSTOM PROCESSOR USING AN FPGA FOR UNDERGRADUATECOMPUTER ARCHITECTURE COURSESJonathan Hill, University of Hartford Dr. Jonathan Hill is an assistant professor in the College of Engineering, Technology, and Architecture (CETA) at the University of Hartford, Connecticut (USA). Ph.D. and M.S. from Worcester Polytechnic Institute (WPI) and B.S. from Northeastern University. Previously an applications engineer with the Networks and Communications division of Digital Corporation. His interests involve embedded microprocessor based systems. Page 12.438.1© American Society for Engineering
Paper ID #5999Deepening Conceptual Understanding in an Introductory Material ScienceCourse Through Active learning StrategiesProf. Todd C. Hufnagel, Johns Hopkins UniversityMr. Michael J. Reese Jr., Johns Hopkins University Michael Reese is the Associate Director at the Johns Hopkins Center for Educational Resources. Reese previously worked as an Educational Technologist at Caliber Learning and Booz-Allen and Hamilton. He also consulted with the University of Maryland School of Nursing on the launch of their distance education program. He earned an M.Ed. in educational technology from the University of Virginia and a B.S. in
support.Introduction“There’s Plenty of Room at the Bottom.” Richard Feynman (1960)Artificial intelligence (AI) methods are revolutionizing undergraduate science, technology,engineering, and mathematics (STEM) education through early forecasting of end-of-semesteracademic performance [1, 2, 3, 4, 5, 6]. These methods typically leverage numeric features ofstudents’ academic trajectories to train AI models. The advent of Transformer-based [7] largelanguage models (LLMs) [8, 9, 10, 11] has significantly expanded the potential for cross-domainapplications due to their extensive knowledge bases [12, 13] and complex task-solvingcapabilities through basic reasoning [9, 14, 15] and planning [16]. Fine-tuning these LLMs viatransfer
York. With a primary research focus on Game Theory and Social Networks, Dr. Dean also harbors a keen interest in Machine Learning classification. Passionate about mentoring undergraduate students, she has guided many in the realms of Game Theory and Machine Learning. Additionally, Dr. Dean has contributed her expertise as a judge at regional events such as the New York State Science and Engineering Fair (NYSSEF) and the WAC Lighting Invitational Science Fair.Dr. Moaath Alrajab, Farmingdale State College, SUNY, New York Moaath Alrajab serves as an Assistant Professor in the Computer Systems Department at Farmingdale State College, SUNY, New York. He earned his Ph.D. in Computer Science from the University of