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A Longitudinal Study of Student Performance in an Elective Applied Digital Signal Processing Course

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2013 ASEE Annual Conference & Exposition


Atlanta, Georgia

Publication Date

June 23, 2013

Start Date

June 23, 2013

End Date

June 26, 2013



Conference Session

Electrical and Computer Engineering (ECE) Poster Session

Tagged Division

Electrical and Computer

Page Count


Page Numbers

23.64.1 - 23.64.12



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Paper Authors


Roger A. Green North Dakota State University

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Roger Green received the B.S. degree in electrical and computer engineering and the M.S. and Ph.D. degrees in electrical engineering from the University of Wyoming in 1992, 1994, and 1998, respectively. During his Ph.D. studies, he also obtained a graduate minor in statistics.

He is currently an Associate Professor with the Electrical and Computer Engineering department at North Dakota State University, where he teaches courses in signals and systems, digital signal processing, random processes, communications, controls, embedded systems, and others. His main research interests include digital and statistical signal processing, time series analysis, spectral and time-frequency analysis, array processing, real-time systems, and data adaptive techniques.

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A Longitudinal Study of Student Performance in an Elective Applied Digital Signal Processing CourseIn this paper, we describe multiple components of a longitudinal study of student performance inan elective applied digital signal processing course. First, we overview course organization andlearning objectives. Next, we present data and analysis on student performance. We assessstudent preparedness over the period from 2002 to 2012 using, as a course pretest, the discrete-time signals and systems concept inventory (DT SSCI) developed by Wage and Buck. Pretestperformance establishes a baseline for various student performance data, including hardware-based project grades over the same eleven-year period. Final exam performance data ispresented from 2006, the year the course adopted a standardized final exam that is similar instructure to the DT SSCI but custom designed for this particular course. Particular attention ispaid to the time period beginning in 2008, when students began field-testing a digital signalprocessing text coauthored by the course instructor. Since this is an elective course, we includeselect department-wide Fundamentals of Engineering (FE) exam data to provide an improvedcontext for course data and analysis. Data is interpreted through a combination of statisticalanalysis, student feedback, and instructor observations. Successes and difficulties in assessmentmethodology and process are discussed, including recommendations for improvement.

Green, R. A. (2013, June), A Longitudinal Study of Student Performance in an Elective Applied Digital Signal Processing Course Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. 10.18260/1-2--19078

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