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PREVIEW: Virtual Patients in Second Life Learning in Immersive worlds

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?.

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PREVIEW: Virtual Patients in Second Life Learning in Immersive worlds

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

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

  3. Problem-based Learning in Virtual Interactive Educational Worlds

  4. Background Problem-based learning courses Students in work placement At a distance; Time poor; Loss of collaborative element. Investigate new ways to deliver PBL

  5. Why Second Life? Cost Ownership Supports external resources Educational community Voice and chat Evolving

  6. 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.

  7. 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.

  8. Paramedic Scenarios

  9. MVP • Process of authoring, adapting and exchanging virtual patients is • Difficult • Time-consuming • Costly • These factors have limited their uptake • A standard would reduce the problem by enabling interoperability between systems • Medbiquitous Virtual Patient (MVP) standard for exchange and reuse of virtual patients

  10. MVP Elements • Virtual Patient Data • XML data • Personal and clinical data relevant to the patient • Data Availability Model • XML Data • References the Virtual Patient data and media resources • Media resources • Media collection of supported file types • Activity Model • XML Data • Encodes how the learner engages with the virtual patient

  11. Testing days • Technology • Training • Scenarios • Engagement • Collaboration • Learning

  12. Future work • More testing days • Embedding within course • Comprehensive evaluation • Guides • Best practice • Releasing scenarios and tools • Register, demos • Opensource

  13. Where next? • Create more scenarios • Expand functionality • Extend work to other subjects/Institutions

  14. Thank you Sheetal Kavia skavia@sgul.ac.uk Luke Woodham lwoodham@sgul.ac.uk http://www.elu.sgul.ac.uk/preview

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