Data Acquisition Systems for the CGA Plasma LabAbstract: This paper reports on the results of an educational collaboration between Physics andElectrical Engineering faculty at US Coast Guard Academy (CGA), to advise a senior capstoneproject. The Physics faculty is constructing a research grade plasma laboratory as a nexus forProject Based Learning (PBL), the development of magneto-hydrodynamic (MHD) physicstheory applications to support organization missions, and investigations into plasma physicsexperiments that are vital to today’s scientific challenges. The collaborative project was designedto setup an electronic system for the lab’s command, control, and data collection from threeplasma experiments being developed in house.Two Electrical
controllers, and successfullypass the class. The observations made on this paper are based on our multiple years ofexperience in teaching the topics as well as several informal discussions with professors in otheruniversities. It appears that some students miss the basic understanding that a controller (whetheranalog or digital) represents a transfer function (in the S-Domain or the Z-Domain) or adifferential/difference equation so that, together with the dynamics of the plant and the rest of thesystem, it allows for desired closed loop behavior.This problem can be partially alleviated during laboratory experiments when students notice thata controller’s transfer function in the S-Domain can be practically implemented using hardware,which includes op
-wave technology and is currently performing research on millimeter-wave compo- nents and systems at Medical College of Wisconsin, Milwaukee, WI. He is a member of the IEEE and teaches courses in circuits, signals, electromagnetic fields, and RF/microwaves.Dr. Stephen M. Williams P.E., Milwaukee School of Engineering Dr. Stephen Williams, P.E. is a Professor and Chair of the Electrical Engineering and Computer Science (EECS) Department at Milwaukee School of Engineering. He has over 25 years of engineering experience across the corporate, government, and university sectors specializing in: engineering design, electrome- chanical systems, sensor technologies, power electronics and digital signal processing. His
Paper ID #18235Project-Based Learning Curriculum for the Junior Year Based on Building aLaser Tag SystemProf. Brad L. Hutchings, Brigham Young University Brad L. Hutchings received the PhD degree in Computer Science from the University of Utah in 1992. He is currently an associate professor in the Department of Electrical and Computer Engineering at Brigham Young University. In 1993, Dr. Hutchings established the Laboratory for Reconfigurable Logic at BYU and currently serves as its head. His research interests are custom computing, embedded systems, FPGA architectures, CAD, and VLSI. He has published numerous papers on
the students in the lab to assist themwith their research projects. As none of the undergraduate students had taken the FPGA Designclass yet, it was necessary first to teach them how to design with FPGAs. The group meetingswere initially dedicated to going over the lecture notes and the laboratory assignments from theFPGA class. The students were required to do some learning independently and then work on theFPGA tutorials in the lab. What was helpful was having the two graduate students working in thelab who were willing to help tutor and assist the students through this learning phase. Theauthor’s observation was that the students were able to grasp the basics of VHDL coding afterthree weeks of training. At this point, they were assigned
, Germany. He performed his post-doctoral research on biosensors at ASU during the years 2003-2005. Before joining ASU as a faculty member, Goryll spent several years at the Research Centre J¨ulich, the largest national research lab in Germany, focusing on SiGe chemical vapor deposition and biosensor development. Dr. Goryll’s current research interests are in the field of silicon processing for nanopore devices, the integration of biogenic nanostruc- tures with silicon MEMS and the development of low-noise wide-bandwidth electronics for the recording of ionic currents in the pA range. Dr. Goryll is a recipient of the NSF CAREER award in 2012 as well as numerous teaching awards, including the 2012 Fulton Schools of
Paper ID #13632Impact of a First and Second Year Culminating Experience on Student Learn-ing in an Electrical Engineering CurriculumDr. Cory J. Prust, Milwaukee School of Engineering Dr. Cory J. Prust is an Associate Professor in the Electrical Engineering and Computer Science Depart- ment at Milwaukee School of Engineering (MSOE). He earned his BSEE degree from MSOE in 2001 and his Ph.D. from Purdue University in 2006. Prior to joining MSOE in 2009, he was a Technical Staff mem- ber at MIT Lincoln Laboratory. He teaches courses in the signal processing, communication systems, and embedded systems areas.Dr. Richard W
small-scalelaboratory experiences within a lecture-based course. A number of different assessment methodsare on-going with this course.1. Introduction Circuits courses for non-majors typically have some of the highest enrollments of anyengineering course since they are required by so many majors. Viewed as “service courses” byboth students and instructors, these courses are often taken grudgingly by students because theyare required out-of-major courses and are often taught by adjunct instructors or GraduateTeaching Assistants. Thus, they are pedagogically a challenge to teach due to low student andinstructor motivation levels. The motivation for blending this course was to provide consistency across sections, allowfor in-class
A Project-based Computer Engineering CurriculumAbstractThis paper documents an innovative, project-based approach to teaching computer engineering.A project-based undergraduate computer engineering curriculum, with an embedded systemsfocus, has been offered since 2004 at a small, private college in the Northwestern US. The maingoals of the curriculum are twofold. The first is to engage students in engineering problemsstarting in the first semester of the Program, thus providing them with a sense of pride andownership in their work. The second is to prepare students for engineering careers by involvingthem in complex, team projects, which are typically only conducted outside of requiredundergraduate coursework, at the graduate level, or in
apply voltage and current division. Weemphasize the importance of comparing and contrasting when teaching concepts, particularly forthe cases of voltage and current sources, short and open circuits (as special cases of voltage andcurrent sources, respectively), voltage and current dividers, series and parallel connections, andvoltage and current measurements. We highlight the importance of contrasting the variousfunctions of terminals in a circuit. We propose various models that can promote understandingof basic electrical concepts, such as a microscopic Drude model of conduction, a “balls in tube”analogy to explain the constancy of current through circuit elements, and a “control loop” modelto explain the operation of voltage and current
their homework computer assignments and the final course project.When hands-on experimentation is implemented in image processing courses, it isusually via computer laboratory assignments done after the class meets. However, in theauthor’s opinion this “waiting period” between the time the knowledge is acquired andthe time it is applied through hands-on activities in unnecessary and may negativelyaffect student learning. Students are more likely to understand and retain the theory if it isillustrated with immediate hands-on experiments. In the course described here, studentswere given the chance to practice the theory at the same time as they were learning it.The remainder of the paper is organized as follows. The context of the DIP course is
Department of Electrical Engineering at Wright State University. Since 2018, he has served as an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Cincinnati. American c Society for Engineering Education, 2021 Pinball Mechatronics: Leveraging Pinball Machines to Teach Embedded SystemsIntroductionIn general, robotic and mechatronic applications present many engaging opportunities forhands-on, experiential learning, and there has been numerous courses developed that leveragethese opportunities 1,2,3,4,5,6,7,8 . Due to their exciting nature, many of these courses are targeted forfirst or
signals, and synthesis of digital diffractive elements. He has been a visiting summer faculty Page 11.1336.1 member at IBM Watson Research Center in Yorktown Heights, NY, Sandia Labs in Livermore, CA, and Hewlett-Packard Labs in Palo Alto, CA. In addition, he has consulted extensively for industry and government laboratories. Professor Allebach is a Fellow of the IEEE, a Fellow of the Society for Imaging Science and Technology (IS&T), and a member of the Optical Society of America. In 1987, he received the© American Society for Engineering Education, 2006 Senior Award from the IEEE
Research and CurriculumDevelopment (CRCD), whose goal is to remedy this shortcoming. In the past two years, we havereported on our experiences of introducing Machine Learning modules in sophomore and juniorundergraduate classes, as well as our experiences of teaching two senior level Machine Learningclasses, entitled Machine Learning I and Machine Learning II. In Machine Learning I weintroduce our research to the students in the class. In Machine Learning II we assign researchprojects to the students and we help them produce their own contributions in the MachineLearning field. One important component of our project is the assessment and evaluation of ourefforts. Last spring (spring of 2005) we have invited a CRCD Advisory Board consisting
. His research focuses on the teaching and learning of physics. He is particularly interested in issues pertaining to transfer of learning and problem solving in physics and engineering. Most recently his research has focused on using the principles of visual cognition to design multimedia hints and cues to facilitate problem solving. This research has potential applications for the design on online learning environments.Prof. Michael R. Melloch, Purdue University, West Lafayette Michael R. Melloch received the B.S.E.E., M.S.E.E., and Ph.D degrees from Purdue University in 1975, 1976, and 1981 respectively. From June 1976 to August 1978 he was a design engineer at Intel Cor- poration (Santa Clara, CA) where he worked
plan defines when, thefrequency, and the number of SOs to be evaluated. This evaluation is of the corresponding SOs’own cycle of assessment before the next accreditation.The GR assessment model has the following characteristics: • Since only mastery-level courses are being assessed, even without dedicated toolsets, the process can be achieved manually with commonly available tools like Words, Excel, etc. in a timely manner. • Independent raters remove the involvement of faculty teaching the courses during the evaluation process.The process is particularly time effective if the assessed results at the end meet the expectations,since laterally you could justify meeting an outcome by investigating evidence from one courseat
Hydrogen-proton membrane transport proteins and her pedagogical research is in the area interactive teaching and learning strategies for any size classroom.Pat Lancey, University of Central Florida© American Society for Engineering Education, 2009Pat Lancey, University of Central Florida PATRICE M. LANCEY earned her B.A. from Brooklyn College, Brooklyn, New York, in 1974, and an M.A. and Ph.D. in Clinical Psychology from Wayne State University, Detroit, Michigan, in 1979 and 1996 respectively. She joined the University of Central Florida in 2001 where she serves as Director, of Operational Excellence and Assessment Support. Dr. Lancey coordinates the university wide Institutional
. The student body primarily studiesengineering, applied sciences, and architecture and construction fields. Class sizes are typicallysmall, averaging around 20-25 students per class, with no teaching assistants. Students arerequired to take two co-ops, one each during their junior and senior years, with an optional co-opduring the sophomore year. Co-ops can be paid and off-campus with industry and academicpartners, or the students can do on-campus research and work with faculty/staff (paid orunpaid).The rest of the paper is as follows: Section 2 describes the project from a technical perspective;Section 3 describes the planned student and technical outcomes; Section 4 details the results ofthe project, with Section 5 providing lessons learned
, in 1997, in electrical engineering. He is currently an Assistant Professor at the University of Texas at San Antonio. From 1999 to 2003 he was with Nokia Corporation. Prior to joining Nokia in 1999 he was a member of teaching and research staff of TUT and a research scientist with the Institute of Informatics and Automatization, Yerevan, Armenia. His current research interests include digital signal processing algorithms for communication receivers, dedicated hardware architectures, positioning methods, and wireless applications. Page 13.428.1© American Society for Engineering Education, 2008
processing techniques for electronic navigation systems, and autonomous vehicle design.Cmdr. Kelly Charles Seals P.E., U.S. Coast Guard Academy Commander Kelly Charles Seals is Program Chair for Electrical Engineering at the U.S. Coast Guard Academy. He has a Ph.D. in Electrical and Computer Engineering from Worcester Polytechnic Institute, a M.S. in Electrical Engineering from Northeastern University, and a B.S. in Electrical Engineering from the U.S. Coast Guard Academy from which he graduated in 1998. He also received a Certificate in College Teaching from the Colleges of Worcester Consortium.Dr. Paul Benjamin Crilly, U.S. Coast Guard Academy Paul Crilly is an Associate Professor of Electrical Engineering at the United
been involved in initiatives at the interface of engineering and the liberal arts. She has led two national symposia on engineering and liberal education at Union College and she was General Chair for the 2008 Frontiers in Education conference. Her teaching interests are in the computer engineering area including digital design, embedded systems, and VLSI. She has co-taught international project courses in Turkey and in Spain. Her research has been focused on timing issues in digital systems. She has directed local and national outreach programs, including Robot Camp and the P. O. Pistilli Scholarship.Dr. Stephen M. Williams P.E., Milwaukee School of Engineering Stephen Williams is professor of electrical
Page 25.1084.1 c American Society for Engineering Education, 2012 Project-based Service Oriented Projects as a way to learn and apply Analog ElectronicsAbstractElectrical and computer engineering students at our university are required during their junioryear to take a three credit lecture course and a two credit laboratory in analog electronics. Overthe past seven years, several attempts have been made to enhance student learning throughparticipation in PBL projects. In Project-based learning “PBL”, since the project is developed bythe instructor and the learning path is predictable, student creativity, ingenuity and innovationmay be diminished. In order to provide opportunities for student creativity
to provide a first-level evaluation method that may determine whichsystems can fit general needs right out of the box. Platforms that are easy to implement are those that areadaptable to the wide range of laboratories, studios, or workspaces and have strong online and offlinetechnical support. Lastly, course/application relevance (CAR) is defined as how appropriate the systemis with respect to the goals of the course/application. This includes taking into account the HI and SIratings, ease-of-implementation (EI), and how well they are aligned with the nature of the problem-solving application. It is important for the designer/instructor to identify clearly the expectation of the course/application.If the goal is to make people think
students’measurement journeys allows us to better understand students’ thought processes while debuggingand helps us uncover students’ stumbling blocks, which will hopefully lead to better teachinginterventions. We have continued to modify the experiments and used this tool in subsequentterms, in efforts to improve the tool and gather more data about how students debug. We are happyto share source code with others who would like to help test out this system. We look forward tosharing additional insights into students’ debugging processes in the near future.Bibliography[1] A. Price, et al. “A Detailed Characterization of the Expert Problem-Solving Process in Scienceand Engineering; Guidance for Teaching and Assessment,” submitted to CBE Life SciencesEducation
Laboratory (see subject’s wrist)Student Questionnaire Responses The students who participated in the program were given a short questionnaire atthe beginning of the program to assess their level of education and experience and todetermine their reasons for participating in the program. Of the seven students whoattended high school in the US and did not have any engineering courses at Texas Tech,four had completed calculus in high school, two were on track to complete calculus intheir senior year, one completed pre-calculus, and three had some experience inprogramming C++. When asked what attracted them to engineering, students typically Page
http://www.engr.ncsu.edu/learningstyles/ilsweb.html 3 R.M. Felder and L.K. Silverman, “Learning and Teaching Styles in Engineering Education,” Engr. Education, 78(7), 674-681 (1988). 4 R.M. Felder and J.E. Spurlin, “Applications, Reliability, and Validity of the Index of Learning Styles,” Intl. Journal of Engineering Education, 21(1), 103-112 (2005). 5 R.M. Felder and R. Brent, “Understanding Student Differences,” J. Engr. Education, 94(1), 57-72 (2005). 6 R.M. Felder, “Matters of Style,” ASEE Prism, 6(4), 18-23 (December 1996). 7 R.M. Felder, G.N. Felder, and E.J. Dietz, “The Effects of Personality Type on Engineering Student Performance and Attitudes,” J. Engr. Education, 91(1), 3-17 (2002).8 D. G. Meyer, “Strategies for
AC 2009-1425: VIRTUALIZING FIRST FOR IMPROVED RECRUITMENT OFSTUDENTS IN COMPUTER SCIENCE AND ENGINEERINGJohn Bowles, University of South Carolina John Bowles is an Associate Professor in the Computer Science and Engineering Department at the University of South Carolina where he teaches and does research in reliable system design. Previously he was employed by NCR Corporation and Bell Laboratories. He has a BS in Engineering Science from the University of Virginia, an MS in Applied Mathematics from the University of Michigan, and a Ph.D. in Computer Science from Rutgers University.Caitlin Buchhaults, University of South Carolina Caitlin Buckhaults is an undergraduate student majoring in Computer
. Page 14.1186.5At the same time, the algorithms-first approach has several critical weaknesses. Important amongthem is lack of practical experience as these algorithms/pseudo codes cannot be executed andtested. Additionally this approach doesn’t provide the holistic view of the discipline. Finally, thealgorithms-first approach requires substantial grading effort [8].The “hardware-first” approach teaches the basics of computer engineering beginning at themachine level and builds up toward more abstract concepts. The basic philosophy behind thisstrategy is for students to learn about computing in a step-by-step fashion that requires as littledemystification as possible. The syllabus begins with switching circuits, uses those to makesimple logic
. Introductory course in programming. This is typically a first course in a high level language. We call this CS Fundamentals I. 2. Introductory course on programming and data structures. This course may introduce a second high level language and typically focuses on data structures and some algorithms. We call this CS Fundamentals II. 3. Object-oriented courses. About a third of the programs had a separate course in object- oriented programming. Many of those that did not have such a course had at least an introduction to OOP in the first two courses. 4. Algorithms. This course is sometimes taught as primarily a mathematics course and some programs teach it with very little programming. We nevertheless classified it
committee member for IEEE Globecom, ICC, ICCCN and VTC conferences, and a reviewer for several international journals and conferences.Dr. Agnieszka Miguel, Seattle University Agnieszka Miguel received her Ph.D. in Electrical Engineering in 2001 from the University of Wash- ington, and MSEE and BSEE from Florida Atlantic University in 1996 and 1994. Dr. Miguel’s profes- sional interests involve image processing, machine learning, and engineering education especially active learning, diversity, retention, and recruitment. Her teaching interests include MATLAB, circuits, linear systems, and digital image processing. She is a member of the IEEE, ASEE, SWE, and Tau Beta Pi. Cur- rently, Dr. Miguel is the Chair of the ASEE