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Adapting Asynchronous Computer Based Instruction To Individual Student Learning Styles

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2010 Annual Conference & Exposition


Louisville, Kentucky

Publication Date

June 20, 2010

Start Date

June 20, 2010

End Date

June 23, 2010



Conference Session

NSF Grantees Poster Session

Page Count


Page Numbers

15.124.1 - 15.124.10



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Paper Authors


Ronald Williams University of Virginia

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Ronald Williams is a faculty member in electrical and computer engineering at the University of Virginia. His research interests are in digital systems, embedded computing, and engineering education.

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Joanne Bechta Dugan University of Virginia

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Joanne Bechta Dugan is Professor of Electrical and Computer Engineering at the University of Virginia.

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

Adapting Asynchronous Computer-Based Instruction to Individual Student Learning Styles Abstract

This paper describes the approach and offers preliminary results for our guided on-demand adaptive learning (GOAL) project. GOAL provides asynchronous web-based instruction that detects preferred learning styles for each student and adapts the instruction to match the detected preference. It also provides a platform for research about learning and for evaluating instruction.


Undergraduate engineering education must change to accommodate the accelerating dependence of society upon engineering and to harness the evolving strengths of our students. To be technologically literate, a student today needs greater breadth and depth of technical knowledge than previous generations of students. However, today’s student cannot allocate more time to gain this greater knowledge. Further, the cadre of technical practitioners supporting our society must expand, become more diverse, and have greater access to technical knowledge.

Fortunately, many of the same advances that are compelling changes in undergraduate engineering education are also enabling these changes. Our understanding of the process of human learning has advanced significantly in recent years, and this improved understanding of teaching and learning tempts us to believe that we might be able to convey knowledge and understanding to students more efficiently. Any such efficiency improvements will help to address the challenge of increasing the depth and breadth of knowledge gained in a fixed interval of time. This project will expand our knowledge of the human process of learning by gathering and evaluating data to quantify certain aspects of the learning process. In addition, this work will address directly the increasing need to improve student access to technical knowledge.

This work is combining advances in technology with advances in understanding of human learning to teach engineering concepts more efficiently. Detailed data is being collected as the concepts are taught to attain new insight into the learning process. The central objective of this work is to show that this approach can improve the efficiency and availability of engineering instruction. This approach will automate and improve the delivery of facts and concepts, broaden access to this material, and create opportunities for the inclusion of additional material.

This project exploits results from research into the way people learn combined with technology providing instruction using established techniques for effective teaching. This work recognizes that different students learn in different ways, at different times and places, and at different rates. This project provides instructional guidance available on-demand at times and places convenient to each student. Our instruction is adaptive so that the student can proceed at his or her own pace using instructional techniques best suited to their own individual learning styles while their progress can be tracked and their instruction can be adjusted in response to their actions. We view this system as analogous to a patient and insightful tutor who is always available and who never tires of explaining and illustrating each concept.

Williams, R., & Bechta Dugan, J. (2010, June), Adapting Asynchronous Computer Based Instruction To Individual Student Learning Styles Paper presented at 2010 Annual Conference & Exposition, Louisville, Kentucky. 10.18260/1-2--16139

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