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Relationship Between Learning Style Preferences And Instructional Technology Usage

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2008 Annual Conference & Exposition


Pittsburgh, Pennsylvania

Publication Date

June 22, 2008

Start Date

June 22, 2008

End Date

June 25, 2008



Conference Session

Instructional Methods and Tools in BME

Tagged Division


Page Count


Page Numbers

13.1031.1 - 13.1031.12



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Paper Authors


Mia Markey University of Texas at Austin

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MIA K. MARKEY is an Assistant Professor in The University of Texas Department of Biomedical Engineering, an inter-institutional department spanning UT Austin, UT M. D. Anderson Cancer Center, and UT Health Science Houston. The mission of her Biomedical Informatics Lab is to design cost-effective, computational decision aids for diagnosis, treatment, and management of disease. The BMIL develops decision support systems for clinical decision making and scientific discovery using artificial intelligence and signal processing technologies. Her interests in improving engineering education are the identification of effective strategies for coordinating instructional technologies to reinforce learning and programs for the recruitment and retention of students from groups traditionally under-represented in engineering.

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Kathy Schmidt University of Texas at Austin

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KATHY J. SCHMIDT is the Director of the Faculty Innovation Center for the Cockrell School of
Engineering at The University of Texas at Austin. In this position, she promotes the School's commitment to finding ways to enrich teaching and learning. She works in all aspects of education including design and development, faculty training, learner support, and evaluation.

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

Session #

Relationship between Learning Style Preferences and Instructional Technology Usage

Mia K. Markey, The University of Texas Department of Biomedical Engineering Kathy J. Schmidt, Faculty Innovation Center, Cockrell School of Engineering, The University of Texas at Austin

Abstract We have been studying engineering students’ learning in both undergraduate and graduate courses on probability and statistics as part of the biomedical engineering curriculum. These courses employ a scaffold of multiple instructional technologies including the course management system, BlackBoard®, hyperlinked PowerPoint® notes, Classroom Performance System (CPS) technology, and “real-world” MATLAB®-intensive problems. The goal of this study is to determine if students with different learning styles (e.g., active vs. reflective learners) have different usage patterns of and derive different benefits from the instructional technologies. We also compare the learning styles of this sample of biomedical engineering students to the existing literature and explore if there are relationships between factors such as learning style, grades and graduate vs. undergraduate status. We present an analysis of Learning Styles Inventory data, survey data on instructional technology perceptions, usage statistics collected from the course management system, and outcome data. In addition, we provide suggestions on how to align instructional strategies (such as interactions between students and interaction with professor) with learning preferences.

I. Introduction

Background The expanding range of learning technologies has created many choices for instructional delivery. Furthermore for the last decade or so, pedagogy and not technology has captured our attention. “What’s different this time, however, is that the focus of change efforts is less on building new institutional structures, redefining the curriculum, or expanding access, and more on the heart of higher education – the teaching/learning process1. ” Our usage of instructional technologies include Blackboard®, a Web-based course management system used at The University of Texas at Austin that is available for any course, Classroom Performance System (CPS) technology that consists of student-operated remote controls and a receiver that records responses to multiple-choice questions posed by the instructor, PowerPoint®, a presentation software package that comes with Microsoft Office and MATLAB®, a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numerical computation.

In this paper, we build upon our previous studies on how instructional technologies influence students in developing basic content understanding, but also in the development of critical thinking and reasoning skills (as categorized by an educational taxonomy) 2,3. We found that instructional technologies can provide scaffolds to support different levels of learning. This finding prompted us to question more. Do students learning styles influence their usage of technology and the benefits they derive from it? We know that a one-size-fits-all curriculum has

Proceedings of the 2008 American Society for Engineering Education Annual Conference & Exposition Copyright © 2008 American Society for Engineering Education

Markey, M., & Schmidt, K. (2008, June), Relationship Between Learning Style Preferences And Instructional Technology Usage Paper presented at 2008 Annual Conference & Exposition, Pittsburgh, Pennsylvania. 10.18260/1-2--3173

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