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9th Annual Meeting
July 14-19,
2005
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Abstract Category: Innovation & Technology |
Poster ID: IT1 |
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REIFICATION OF ABSTRACT CONCEPTS TO IMPROVE COMPREHENSION USING INTERACTIVE VIRTUAL ENVIRONMENTS AND A KNOWLEDGE-BASED DESIGN Dale C. Alverson, M.D.1*, Stanley M. Saiki Jr, MD5,6, Thomas P. Caudell, PhD2, Timothy Goldsmith, PhD3, Susan Stevens, MS3, Linda Saland, PhD1, Kathleen Colleran, MD1, John Brandt, MD1, Lee Danielson, PhD1, Lisa Cerilli, MD1, Alexis Harris, MD1, Martin C. Gregory, MD7, Randall Stewart, MD1, Jeffery Norenberg, PharmD1, George Shuster, DNSc1, Panaiotis, PhD4, James Holten, III2, Victor M. Vergara, MS2, Andrei Sherstyuk, PhD5, Kathleen Kihmm5, Jack Lui5, Alex Wang5 1Health Sciences Center, 2School of Engineering, and 3Department of Psychology, 4School of Music, University of New Mexico, Albuquerque, NM 87131 U.S.A., 5John A. Burns School of Medicine University of Hawaii, Honolulu, HI 96822, 6Pacific Telehealth and Technology Hui, Tripler Army Medical Center, Honolulu, HI 96859, School of Medicine, University of Utah, Salt lake City, UT 84132 U.S.A. There are many abstract concepts in medical education that are
difficult to teach and comprehend. In order to address this challenge, we
have been applying the approach of reification of abstract concepts using
interactive virtual environments and a knowledge-based design. Reification
is the process of making abstract concepts and events, beyond the realm of
direct human experience, concrete and accessible to teachers and learners.
Entering virtual worlds and simulations not otherwise easily
accessible provides an opportunity to create, study, and evaluate the
emergence of knowledge and comprehension from the direct interaction of
learners with otherwise complex abstract ideas and principles by bringing
them to life. Using a knowledge-based design process and appropriate
subject matter experts, knowledge structure methods are applied in order
to prioritize, characterize important relationships, and create a concept
map that can be integrated into the reified models that are subsequently
developed. Applying these principles, our interdisciplinary team has been
developing a reified model of the nephron into which important physiologic
functions can be integrated and rendered into a three dimensional virtual
environment called Flatland, a virtual environments development software
tool, within which a learners can interact using off-the-shelf hardware.
The nephron model can be driven dynamically by a rules-based artificial
intelligence engine, applying the rules and concepts developed in
conjunction with the subject matter experts. In the future, the nephron
model can be used to interactively demonstrate a number of physiologic
principles or a variety of pathological processes that may be difficult to
teach and understand. In addition, this approach to reification can be
applied to a host of other physiologic and pathological concepts in other
systems. These methods will require further evaluation to determine their
impact and role in learning.
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