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Utilizing New Instructional Technologies To Optimize The Learning Process

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2001 Annual Conference


Albuquerque, New Mexico

Publication Date

June 24, 2001

Start Date

June 24, 2001

End Date

June 27, 2001



Page Count


Page Numbers

6.1131.1 - 6.1131.8



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Paper Authors

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James Wade

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Virginia Elkins

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Roy Eckart

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Catherine Rafter

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Eugene Rutz

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

Session 3430

Utilizing New Instructional Technologies to Optimize the Learning Process Roy Eckart, Virginia Elkins, Terri Heidotting, Catherine Rafter, Eugene Rutz and James Wade University of Cincinnati


The goal of this project, funded by a grant from the General Electric Fund, is to determine whether using new instructional technologies to optimize the learning process for students with different learning styles and personality types. This paper presents the progress made toward this goal in the first year of a three-year project.

The student learning styles and personality types were measured and compared to student performance in four sections of a single class (Mechanics I) taught using three different instructional technologies: two interactive video classes, (a local and a remote site), a web-based class and a streaming video class. A standard lecture class was used as the control class.

All classes received in-person instruction which varied depending on the specific instructional technology used in that class. The traditional class and the interactive video classes were standard lectures. Students in the web-based class and the streaming video class were required to preview the Mechanics I course material prior to the class. The instructor’s role changed from the traditional lecturer to that of mentor; he reviewed difficult concepts, answered questions, worked problems and gave practical examples.

Two widely accepted instruments were chosen to provide information on how students learn: The Myers-Briggs Type Indicator (MBTI) and the Learning Style Inventory (LSI). A statistical analysis was used to assess student learning based on MBTI types and LSI in the control class and each of the three technology classes. We examined how various personality types and learning styles perform within a specific class, how various personality types and learning styles perform across all four instructional formats; and how student interest in the class or instructional technology affects his/her grades.

There were 200 students enrolled in the five classes, a relatively small sample for statistical analysis. Data acquired during the next two years will significantly increase confidence in the results. Significant differences were found between the web-based and streaming video classes as well as the web-based and traditional classes. Analysis revealed that different thinking types

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Wade, J., & Elkins, V., & Eckart, R., & Rafter, C., & Rutz, E. (2001, June), Utilizing New Instructional Technologies To Optimize The Learning Process Paper presented at 2001 Annual Conference, Albuquerque, New Mexico. 10.18260/1-2--9991

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