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Transcript of October2008 PREVIEW: Virtual Patients in Second Life Learning in Immersive worlds Emily Conradi,...
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OctoberOctober20082008
PREVIEW:Virtual Patients in Second Life
Learning in Immersive worlds
Emily Conradi, Sheetal Kavia,
Luke Woodham, Terry PoultonSt George’s University of London
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OctoberOctober20082008
Overview
• Introduction to PREVIEW • About virtual patients• Demonstration• Technology• Where next?
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OctoberOctober20082008
Problem-based Learning in Virtual Interactive Educational Worlds
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OctoberOctober20082008
Background
• Problem-based learning courses• Students in work placemento At a distance;o Time poor;o Loss of collaborative element.
• Investigate new ways to deliver PBL
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OctoberOctober20082008
Why Second Life?
• Cost• Ownership • Supports external resources• Educational community• Voice and chat• Evolving
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OctoberOctober20082008
Aims
• Deliver PBL in Second Life;• Develop eight interactive PBL scenarios;• Users guide development and evaluation;• Develop guidelines and best-practice on delivering
PBL in virtual worlds;• Share outputs, technology.
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OctoberOctober20082008
Virtual Patients
“an interactive computer simulation of real-life clinical scenarios for the purpose of
medical training, education, or assessment”
Ellaway, R., Candler, C., Greene, P. and Smothers, V., 2006.
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OctoberOctober20082008
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OctoberOctober20082008
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OctoberOctober20082008
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OctoberOctober20082008
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OctoberOctober20082008
Paramedic Scenarios
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OctoberOctober20082008
MVP
• Process of authoring, adapting and exchanging virtual patients iso Difficulto Time-consumingo Costly
• These factors have limited their uptake• A standard would reduce the problem by enabling
interoperability between systemso Medbiquitous Virtual Patient (MVP) standard for exchange and
reuse of virtual patients
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OctoberOctober20082008
MVP Elements
Virtual Patient Data•XML data
•Personal and clinical data relevant to the patient
Media resources•Media collection of supported file types
Data Availability Model•XML Data
•References the Virtual Patient data and media resources
Activity Model•XML Data
•Encodes how the learner engages with the virtual patient
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OctoberOctober20082008
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OctoberOctober20082008
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OctoberOctober20082008
Testing days
• Technology• Training• Scenarios• Engagement• Collaboration• Learning
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OctoberOctober20082008
Future work
• More testing days• Embedding within course• Comprehensive evaluation
o Guideso Best practice
• Releasing scenarios and toolso Register, demoso Opensource
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OctoberOctober20082008
Where next?
• Create more scenarios• Expand functionality• Extend work to other subjects/Institutions
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OctoberOctober20082008
Thank you
Sheetal Kavia
Luke Woodham
http://www.elu.sgul.ac.uk/preview