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Learning Strategy and Verbal-Visual Preferences for Chemical Engineering Students

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Chemical Engineering Pedagogy

Tagged Division

Chemical Engineering

Tagged Topic

Diversity

Page Count

17

Permanent URL

https://strategy.asee.org/37430

Download Count

12

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Paper Authors

biography

Charles E. Baukal Jr. P.E. John Zink Co. LLC

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Charles E. Baukal, Jr. has a Ph.D. in Mechanical Engineering, an Ed.D., and Professional Engineering License. He is the Director of the John Zink Institute which offers continuing professional development for engineers and technicians. He has nearly 35 years of industrial experience and 30 years of teaching experience as an adjunct. He is the author/editor of 14 books on industrial combustion and 2 on engineering education. He is an inventor on 11 U.S. patents.

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Abstract

The learner characteristics of preferred learning strategy and verbal-visual preferences of 180 chemical engineering students at a Midwestern university were studied in relation to the demographics of gender, class in school, ethnicity, native country, and native language. Learning strategy and verbal-visual preferences were measured by the ATLAS and the Verbal-Visual Learning Style Rating tests, respectively. Neither characteristic had been previously measured for chemical engineering students. The overall learning strategy preference profile for the chemical engineering students was 35.1% Navigators, 39.7% Problem Solvers, and 25.3% Engagers. This profile is statistically significantly different from the established values for the general population where there are more Problem Solvers and fewer Engagers among the students compared to the general population. This suggests chemical engineering instructors should include problem solving as an important element of their instructional methods. The overall verbal-visual preference profile was 6.3% more verbal, 56.8% no strong preference, and 36.9% more visual. This profile is statistically significantly different than the general population and suggests chemical engineering instructors should design instructional materials with a significant proportion of visual content. This paper will report on the relationships found between learner characteristics and demographics. It will also include recommendations for instructional practice and for future chemical engineering education research.

Baukal, C. E. (2021, July), Learning Strategy and Verbal-Visual Preferences for Chemical Engineering Students Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://strategy.asee.org/37430

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