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Improving Tools And Techniques Of Teaching Graduate Engineering Courses Based On Students’ Learning Styles And Multiple Intelligences

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2009 Annual Conference & Exposition


Austin, Texas

Publication Date

June 14, 2009

Start Date

June 14, 2009

End Date

June 17, 2009



Conference Session

Innovations in ECE Education III

Tagged Division

Electrical and Computer

Page Count


Page Numbers

14.713.1 - 14.713.16



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Paper Authors


Buket Barkana University of Bridgeport

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Buket D. Barkana received the B.S. degree from Anatolia University, in 1994, and the M.S.E. and Ph.D. degrees from Eskisehir Osmangazi University, Turkey, in 1997 and 2005, respectively. She is now Assistant Professor of Electrical Engineering at the University of Bridgeport, CT. Dr. Barkana’s current research projects include: voice/audio signal processing, speech disorders, and innovations in engineering education.

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Navarun Gupta University of Bridgeport

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Dr. Navarun Gupta is an Assistant Professor of Electrical Engineering at the University of Bridgeport. He received his Ph.D. from Florida International University in Miami. He has two master's degrees - one in Physics from Georgia State University and another in Electrical Engineering from Mercer University. Dr. Gupta's research interests lie in the application of signal processing in audio and bio signals.

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Lawrence Hmurcik University of Bridgeport

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Lawrence V. Hmurcik is Professor and Chairman of Electrical Engineering at the University of Bridgeport, Bridgeport, CT. He earned his Ph.D. in semiconductor devices at Clarkson University in 1980.He worked in Diamond Shamrock's research division for 3 years before joining the University of Bridgeport in 1983. Dr. Hmurcik has 45 publications and 5 grants. He is also a professional consultant with 240 case entries, including 14 appearances in Court and Legal Depositions. Dr. Hmurcik's interests have changed over the years: starting in Solar Cell technology in 1977, Dr. Hmurcik is currently pursuing work in Medical Electronics and Electric Safety.

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Improving Tools and Techniques of Teaching Graduate Engineering Courses Based on Students’ Learning Styles and Multiple Intelligences


Our study proposes to improve the tools and techniques of teaching graduate engineering courses using students’ Learning Styles and Multiple Intelligences (MI). Thirty volunteers answered commercially available Learning Style and MI tests in our Electrical Engineering department. Learning styles are grouped as visual, auditory, and kinesthetic (VAK) and can determined by the VAK learning style test. Learning styles are reflected in different academic strengths, weaknesses, and skills. Studies show that the differences between learning styles will affect both a person’s choice of profession and their success in this profession, both in education and in the world of business. People who work at something that fits their learning style have a better chance of becoming successful in it. In this study, tools and techniques are presented for the teaching of graduate courses in engineering education.


Institutions of higher education are always looking for ways to improve their educational initiatives. In colleges and universities, teaching is a very important way to achieve institutional goals of increased effectiveness and the improvement of student learning. The inability to consciously control and manage the learning process in higher education in general and various classes in particular lies in a lack of understanding of the learning process itself, and this can serve as a substantial impediment to student learning and faculty teaching1. Instructors need to do more in utilizing accepted learning theories, principles, and teaching technology that will improve learning and assist students in developing themselves to their full potential. Researchers continually discuss ways to reform a university’s teaching. While some of them focus on the learning styles of the students2,3,4,5, others focus on the requirements for re-examination of fundamental assumptions about how universities function and consideration of empirical research about how students learn6.

We offer effective teaching tools for different learning styles of engineering graduate students. If we teach exclusively in the students' preferred mode, the students may not develop the mental dexterity they need to reach their potential for achievement in school and as professionals. On the other hand, if we teach exclusively in a manner that favors the students' less preferred learning style modes, the students' discomfort level may be great enough to interfere with their learning. In 1990, Tobias pointed out two tiers of entering college students. The first tier goes on to earn science degrees and the second tier has the initial intention and the ability to do so but instead switches to nonscientific fields. The number of students in the second tier might in fact be a result of the teaching techniques that are used in engineering education7.

Which teaching techniques should we use in the engineering classroom to engage more students? This is the question we need to answer. We focus on the students’ learning styles and multiple intelligences to answer this question.

Barkana, B., & Gupta, N., & Hmurcik, L. (2009, June), Improving Tools And Techniques Of Teaching Graduate Engineering Courses Based On Students’ Learning Styles And Multiple Intelligences Paper presented at 2009 Annual Conference & Exposition, Austin, Texas. 10.18260/1-2--4928

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