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Mastering the Core Competencies of Electrical Engineering through Knowledge Integration

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Conference

2016 ASEE Annual Conference & Exposition

Location

New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

June 29, 2016

ISBN

978-0-692-68565-5

ISSN

2153-5965

Conference Session

Electrical and Computer Division Poster Session

Tagged Division

Electrical and Computer

Tagged Topic

Diversity

Page Count

12

DOI

10.18260/p.25683

Permanent URL

https://strategy.asee.org/25683

Download Count

1684

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Paper Authors

biography

Tom Chen Colorado State University

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Tom Chen received his Ph.D. from the University of Edinburgh. After spending 4 years with Philips Semiconductors in Europe, he joined the Department of Electrical & Computer Engineering at Colorado State University. Prof. Chen published more than 180 journal and conference papers in the areas of analog and digital VLSI design and CAD for VLSI design. Prof. Chen served as General Chair of 2015 IEEE Midwest Symposium on Circuits and Systems, and as the Guest Editor of the IEEE Trans. on Computer-Aided Design of Integrated Circuits
and Systems special issue on Design Quality and Design Closure: Present Issues and Future Trend", 2005. He also served as the Guest Editor of the Microelectronics Journal on Quality Electronic Design, 2005. His research interests include VLSI circuit and system design, CAD methodology for VLSI design, and bioelectronics.

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Anthony A. Maciejewski Colorado State University

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Anthony A. Maciejewski received the BSEE, MS, and PhD degrees from the Ohio State University
in 1982, 1984, and 1987, respectively.From 1988 to 2001, he was a professor of electrical
and computer engineering at Purdue University, West Lafayette. He is currently a professor
and the department head of Electrical and Computer Engineering at Colorado State University.
He is a fellow of the IEEE. A complete vita is available at: http://www.engr.colostate.edu/ ~aam.

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Branislav M. Notaros Colorado State University

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Branislav M. Notaros is Professor in the Department of Electrical and Computer Engineering at Colorado State University, where he also is Director of Electromagnetics Laboratory. He received a Ph.D. in electrical engineering from the University of Belgrade, Yugoslavia, in 1995. His research publications in computational and applied electromagnetics include more than 150 journal and conference papers. He is the author of textbooks Electromagnetics (2010) and MATLAB-Based Electromagnetics (2013), both with Pearson Prentice Hall. Prof. Notaros served as General Chair of FEM2012, Colorado, USA, and as Guest Editor of the Special Issue on Finite Elements for Microwave Engineering, in Electromagnetics, 2014. He was the recipient of the 1999 Institution of Electrical Engineers (IEE) Marconi Premium, 2005 Institute of Electrical and Electronics Engineers (IEEE) MTT-S Microwave Prize, 2005 UMass Dartmouth Scholar of the Year Award, 2012 Colorado State University System Board of Governors Excellence in Undergraduate Teaching Award, 2012 IEEE Region 5 Outstanding Engineering Educator Award, 2014 Carnegie Foundation for the Advancement of Teaching Colorado Professor of the Year Award, 2015 American Society for Engineering Education ECE Distinguished Educator Award, 2015 IEEE Undergraduate Teaching Award, and many other research and teaching awards.

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Ali Pezeshki Colorado State University

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Ali Pezeshki received the BSc and MSc degrees in electrical engineering from University of Tehran, Tehran, Iran, in 1999 and 2001, respectively. He earned his PhD degree in electrical engineering at Colorado State University in 2004. In 2005, he was a postdoctoral research associate with the Electrical and Computer Engineering Department at Colorado State University. From January 2006 to August 2008, he was a postdoctoral research associate with The Program in Applied and Computational Mathematics at Princeton University. In August 2008, he joined the faculty of Colorado State University, where he is now an Associate Professor in the Department of Electrical and Computer Engineering, and the Department of Mathematics. His research interests are in statistical signal processing, coding theory, applied harmonic analysis, and bioimaging.

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Melissa D. Reese Colorado State University

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Melissa D. Reese received a BS in International Business/Finance and an MBA in Management/Organizational Development from Rochester Institute of Technology in 1998 and 2006, respectively. She is currently the department manager of Electrical and Computer Engineering at Colorado State University.

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Abstract

This work in progress describes pedagogical innovations in an electrical and computer engineering department designed to help students gain core competencies in electrical engineering more effectively. Electrical engineering (EE) core competencies consist of three pillars: signals and systems, electronic circuits, and electromagnetics. Technical courses teaching the core competencies are typically in the middle years of a four-year undergraduate program. With the requirement of knowing a wide range of fundamental math concepts such as complex variables and their representations/manipulations, integrations and differentiations, factorization and other algebraic manipulations, gaining core competencies represents significant technical challenges to students enrolled in an EE undergraduate program in two different ways: • The amount of contents covered increases significantly over time. Many students find it difficult to grasp the concepts because they are extremely abstract and mathematically intense. • Students do not see the connections between core competency courses and how they fit into the big picture, as well as why the mastery of individual topics matters greatly for solving real-world engineering problems. Thus, they lose confidence and motivation.

By recognizing that key concepts in different core competency areas are often applied to solve real-world engineering problems, the new proposed approach tackles one of the fundamental deficiencies in learning by changing the traditional silo-style teaching and learning. The proposed approach breaks the courses in the core competency areas into a set of learning studio modules (LSMs). Each LSM is self-contained and addresses a key anchoring concept and a set of related concepts in a given core competency area. For example, differential signaling and its circuit realization is an anchoring concept in Electronic Circuits. The related concepts include common mode noise, matching, input offset, etc. A traditional semester-long course for a given core competency area consists of a set of LSMs in a specified order. Thus, a path exists for students to learn all anchoring concepts in a given core competency area. However, by properly aligning LSMs from different core competency areas, LSMs provide an opportunity to stitch together a set of key anchoring concepts across different core competency areas to form new learning modules to illustrate how a set of anchoring concepts can be applied together to solve real-world engineering problem. The purpose of the new modules is to make the overall learning more coherent and to provide context of utilization of these anchoring concepts to increase student appreciation and motivation. Therefore, they play the role of knowledge integration (KI).

KI modules reinforce the fact that concepts in different core competency areas are highly connected and dependent on each other to make a complex system function as intended. They allow students to gain deeper understanding of the roles the anchoring concepts play through applications. KI modules also provide a platform for better unpacking of math, physics, and engineering concepts to create knowledge coherency among the core competency areas. This paper provides details for the proposed LSMs and their related KI modules. The relationship between the proposed LSMs and KIs and their rationales will also be discussed.

Chen, T., & Maciejewski, A. A., & Notaros, B. M., & Pezeshki, A., & Reese, M. D. (2016, June), Mastering the Core Competencies of Electrical Engineering through Knowledge Integration Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.25683

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