Virtual Civilian Aeromedical Evacuation Sustainment Training Project (V-CAEST)

Abstract

The Virtual Civilian Aeromedical Evacuation Sustainment Training (V-CAEST) project has a central goal to improve communication between civilian medical practitioners (i.e., first responders, EMTs, etc.) and the military during disaster situations. V-CAEST focuses on disaster situations that span multiple jurisdictions and require aeromedical evacuation. The University of Memphis, in conjunction with Arizona State University, gathered the content of an existing live-action training program (CAEST) and leveraged existing effective educational technologies (i.e., Auto Tutor Lite, a web-based intelligent tutoring system equipped with natural language processing) to develop a new virtual learning environment. Specifically, the University of Memphis worked with CliniSpace to develop a virtual world enabled with Auto Tutor Lite, to model the live-action training program CAEST. The V-CAEST project sought to develop a virtual learning environment that is more cost-effective and wide-reaching than the live-action training alternative, but as effective in producing learning gains. The final evaluation of the program compared the pre-test and post-test learning gains of both the live-action training program and the virtual learning environment. The results indicate that the V-CAEST virtual learning environment is as effective at producing significant learning gains as the live action training program.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2015
Accession Number
AD1002332

Entities

People

  • Keith Shubeck
  • Marian Levy
  • Robert Koch
  • Scotty D Craig
  • Usef Faghihi
  • Xiangen Hu

Organizations

  • University of Memphis

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Aeromedical Evacuation
  • Artificial Intelligence
  • Cognitive Science
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computers
  • Electronic Mail
  • Health Services
  • Language
  • Machine Learning
  • Medical Personnel
  • Natural Language Processing
  • Operating Systems
  • Psychology
  • Students
  • Test And Evaluation

Fields of Study

  • Computer science

Readers

  • Coastal and Marine Engineering/Sediment Transport/Hydraulic Engineering
  • Military Training and Readiness Simulation
  • STEM Education

Technology Areas

  • AI & ML