preview: virtual patients in second life learning in immersive worlds

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October October 2008 2008 PREVIEW: Virtual Patients in Second Life Learning in Immersive worlds Emily Conradi, Sheetal Kavia, Luke Woodham, Terry Poulton St George’s University of London

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PREVIEW: Virtual Patients in Second Life Learning in Immersive worlds. Emily Conradi, Sheetal Kavia, Luke Woodham, Terry Poulton St George’s University of London. Overview. Introduction to PREVIEW About virtual patients Demonstration Technology Where next?. - PowerPoint PPT Presentation

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Page 1: PREVIEW: Virtual Patients in Second Life  Learning in Immersive worlds

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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Overview

• Introduction to PREVIEW • About virtual patients• Demonstration• Technology• Where next?

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Problem-based Learning in Virtual Interactive Educational Worlds

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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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Why Second Life?

• Cost• Ownership • Supports external resources• Educational community• Voice and chat• Evolving

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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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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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Paramedic Scenarios

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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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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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Testing days

• Technology• Training• Scenarios• Engagement• Collaboration• Learning

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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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Where next?

• Create more scenarios• Expand functionality• Extend work to other subjects/Institutions

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Thank you

Sheetal Kavia

[email protected]

Luke Woodham

[email protected]

http://www.elu.sgul.ac.uk/preview