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Measurement and Automation: Experiential Learning Opportunity

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2014 ASEE Annual Conference & Exposition


Indianapolis, Indiana

Publication Date

June 15, 2014

Start Date

June 15, 2014

End Date

June 18, 2014



Conference Session

Active Learning in ECE

Tagged Division

Electrical and Computer

Page Count


Page Numbers

24.891.1 - 24.891.15



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Paper Authors


John W. Dyer School of Electrical and Computer Engineering, University of Oklahoma

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John Dyer received a B.S. in Physiology from Oklahoma State University, and the B.S., M.S. and Ph.D. in Electrical Engineering from the University of Oklahoma. His main research interests are in instrumentation, data acquisition, and signal processing of the acquired data. Dr. Dyer applies these interests largely in the area of aviation and navigation, though he has applied his work in areas such as Cardiac Electrophysiology research and gas-fracture wellhead stress analysis.

Professor Dyer has worked on projects with the FAA and the OU Department of Aviation to implement the Ground Based Augmentation System, a Differential-GPS based aircraft landing system. He has also worked on projects involving passive multilateration for aircraft tracking, Distance Measuring Equipment (DME, a standard FAA navigation technology), and Space Based Augmentation System (SBAS) error analysis. Dr. Dyer is a Commercial-rated pilot and occasionally lends his piloting skill set to test flights for assessing navigation technology performance.

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David Sandmann MSEE University of Oklahoma

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Obtained Bachelors’ and Masters’ in Electrical Engineering from the University of Oklahoma in 1994 and 1998 respectively. Currently Doctorate candidate with current graduation set for December 2013.

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Chad Eric Davis P.E. University of Oklahoma

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Chad E. Davis received the B.S. degree in mechanical engineering, M.S. degree in electrical engineering, and Ph.D. degree in engineering from the University of Oklahoma (OU), Norman, in 1994, 2000, and 2007, respectively. Since 2008, he has been a member of the Electrical and Computer Engineering (ECE) faculty, University of Oklahoma. Prior to joining the OU-ECE faculty, he worked in industry at Uponor (Tulsa, OK), McElroy Manufacturing (Tulsa, OK), Lucent (Oklahoma City, OK), Celestica (Oklahoma City, OK), and Boeing (Midwest City, OK). His work experience ranges from electromechanical system design to automation of manufacturing and test processes. His research at OU involves GPS ground-based augmentation systems utilizing feedback control. Dr. Davis holds a dual discipline (electrical and mechanical) professional engineering license in the state of Oklahoma. He currently serves as the faculty advisor for Robotics Club, the Loyal Knights of Old Trusty, and Sooner Competitive Robotics at OU and he serves as the recruitment and outreach coordinator for OU-ECE. He received the Provost's Outstanding Academic Advising Award in 2010 and the Brandon H. Griffin Teaching Award in 2012.

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Measurement and Automation: Experiential Learning OpportunityA growing body of evidence shows that experiential learning promotes better retention, directedself-learning, and lifelong learning. To address this, we have developed a Measurement andAutomation laboratory class that studies key features of Electrical and Computer Engineeringwith hands-on projects designed to enhance the learning opportunity. Many engineering classesare lecture-oriented courses in which theory is presented didactically, and homework problemsare assigned that are intended to reinforce both the math and the fundamental engineeringconcepts under discussion. This methodology frequently leads to student study methods orientedtoward memorizing problems to the extent that they can pass the next exam. Studies haveshown, though, that this style of learning does not promote long-term retention of concepts andunderstanding in many students. Furthermore, different learning styles may keep some studentsfrom grasping the underlying engineering concepts solely based on a theoretical lecture.To address these problems, we developed a laboratory course for seniors and graduate studentsthat provides project-based learning opportunities covering the fundamental concepts inelectrical and computer engineering. Projects provide tangible understanding of dynamic rangeand sampling rates, aliasing that students can control and observe in real-time, physicalrealization of second-order differential equations through a damped oscillatory system andaccelerometers, controlled output based on analysis of input data, image processing to countchange, and many other projects. Computerized data analysis is a key feature in all engineeringfields, and understanding the proper acquisition of that data relative to the signal characteristicsis critical to success. During the semester, students are exposed to noisy data, filtering effects,and correlating classroom theory to physical reality.While there are many such courses being developed in engineering schools, this course is uniquebecause it provides the students with a single data source from real sensors operating on liveequipment. Sensor types include pressure sensors, strain gauges, accelerometers, humidity andtemperature sensors, wind speed and direction sensors, and digital images. The data aredelivered to the students by a novel laboratory layout in which each sensor feeds a centralizeddistribution point. The data are then delivered to each workstation through a proto-boardinterface designed and built in-house. The proto-board interface provides for audio input andoutput, analog input and output, digital input and output, LEDs to simulate digital control, athermistor port, and a breadboard area for student-built external circuitry, e.g. an anti-aliasingfilter. Each workstation has an interface board connected to a National Instruments USB-6211Multifunction DAQ unit. The USB-6211 is connected to a desktop computer, with universitynetwork access, running the LabVIEW software from National Instruments. The single-sourcelayout ensures that each student works with the same data stream, which provides the students anopportunity to collaborate and compare results as they gain understanding. Furthermore, thesingle data source ensures an expected outcome by which the instructor can assess studentperformance. The hands-on nature of the course makes it popular with students, and industrypartners have provided positive feedback based on new-hires from our university.

Dyer, J. W., & Sandmann, D., & Davis, C. E. (2014, June), Measurement and Automation: Experiential Learning Opportunity Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--22824

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