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Home» SOLUTIONS » Education and Training » METTLE: Medical Emergency Team Tutored Learning Environment

METTLE: Medical Emergency Team Tutored Learning Environment

Customer Office of the Secretary of Defense / U.S. Army Telemedicine and Advanced Technology Research Center (TATRC)
Users Clinicians
Need It is difficult for clinicians to become proficient diagnosing and treating unusual medical problems that are rarely encountered. Journal articles and medical cases can introduce facts and concepts. However, because they are non-interactive, they do not provide practice opportunities, assess student performance, or provide instructional feedback students need for application-level learning. Seminars with instructor-led discussions provide interactive learning experiences, but they require students to set aside blocks of free time to attend, and they are available only at certain times and locations.
Solution To make interactive, scenario-based, medical training available anytime and anywhere, Stottler Henke developed METTLE, an authorable and extensible framework that makes it easy to create and deliver richly interactive scenarios over the web. During the scenario, a student can interact with simulated characters using language, forms, interactive images and diagrams, audio, and other media. Intelligent tutoring capabilities monitor and assess the student’s actions and communications to identify contextually appropriate coaching and instruction feedback to present to the student.
Status An operational prototype has been developed. In one scenario, a patient arrives at an emergency room with presenting flu symptoms but, it turns out, suffers from anthrax exposure. By reviewing patient charts, examining the patient, and ordering lab tests, the student must diagnose, treat, and manage the patient. A study assessing the software’s effectiveness will be carried out in early 2008.
Related Applications METTLE was developed for medical training scenarios, and it provides interaction modes and pre-built content for simulating diagnostic/treatment encounters. The framework is general and can be applied to any training application that requires (1) practice making decisions, informed by interacting with simulated characters, (2) distributed web-based delivery, and (3) automated tutoring to support any time/anywhere web training.
Additional information
  • Video demo: WMV (36 MB)
  • Screens: main screen    chart    exam
  • Overview
  • Slides from MMVR 2008 (Medicine Meets Virtual Reality)
  • I/ITSEC 2009 paper: Domeshek, E. (2009) Scenario-Based Conversational Intelligent Tutoring Systems for Decision-Making Skills     

 

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