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Learning Strategy and Verbal-Visual Preferences for Mechanical Engineering Students

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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

Learning and Assessment in ME

Tagged Division

Mechanical Engineering

Page Count


Page Numbers

24.855.1 - 24.855.15



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Paper Authors


Charles E. Baukal Jr. P.E. John Zink Hamworthy Combustion

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Chuck Baukal, Ph.D., P.E., is the director of the John Zink Institute, the training organization for John Zink Hamworthy Combustion, where he has been since 1998. He has over 30 years of industrial experience and over 20 years of adjunct teaching experience. He is currently an adjunct instructor at Oral Roberts University, the University of Tulsa, the University of Oklahoma, and the University of Utah. He is the author/editor of 13 books on industrial combustion and more than 150 publications on combustion and engineering education, and is an inventor on 11 U.S. patents.

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Lynna J. Ausburn Oklahoma State University

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Dr. Ausburn is a professor of occupational education in the College of Education at Oklahoma State University. She teaches courses in quantitative research, theory in research, visual design, and adult education. Her research interests include virtual reality environments for learning, virtual HRD, and adult learning strategies and styles. She has worked in 19 countries in the field of workforce and productivity development.

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Learning Strategy and Verbal-Visual Preferences for Mechanical Engineering StudentsThe learner characteristics of preferred learning strategy and verbal-visual preferences of 54mechanical engineering students at two Midwestern universities were studied in relation to thedemographics of gender, class in school, ethnicity, native country, and native language. Learningstrategy and verbal-visual preferences were measured by the ATLAS and the Verbal-VisualLearning Style Rating tests, respectively. Neither characteristic had been previously measuredfor mechanical engineering students. The overall learning strategy preference profile for themechanical engineering students was 32.7% Navigators, 32.7% Problem Solvers, and 34.7%Engagers. This profile was not statistically significantly different from the established values forthe general population. Because mechanical engineering students appear to be approximatelyequally divided among the three learning strategy preferences, a variety of instructionaltechniques addressing all three styles is recommended for use by instructors to match students’preferences. The overall verbal-visual preference profile was 5.6% more verbal, 46.3% no strongpreference, and 48.1% more visual. This profile is statistically significantly different than thegeneral population and suggests mechanical engineering instructors should design instructionalmaterials with a significant proportion of visual content. This paper will report on therelationships found between learner characteristics and demographics. It will also includerecommendations for instructional practice and for future research.

Baukal, C. E., & Ausburn, L. J. (2014, June), Learning Strategy and Verbal-Visual Preferences for Mechanical Engineering Students Paper presented at 2014 ASEE Annual Conference & Exposition, Indianapolis, Indiana. 10.18260/1-2--20746

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