Virtual reality training improves students' knowledge structures of medical concepts.

Virtual environments can provide training that is difficult to achieve under normal circumstances. Medical students can work on high-risk cases in a realistic, time-critical environment, where students practice skills in a cognitively demanding and emotionally compelling situation. Research from cognitive science has shown that as students acquire domain expertise, their semantic organization of core domain concepts become more similar to those of an expert's. In the current study, we hypothesized that students' knowledge structures would become more expert-like as a result of their diagnosing and treating a patient experiencing a hematoma within a virtual environment. Forty-eight medical students diagnosed and treated a hematoma case within a fully immersed virtual environment. Student's semantic organization of 25 case-related concepts was assessed prior to and after training. Students' knowledge structures became more integrated and similar to an expert knowledge structure of the concepts as a result of the learning experience. The methods used here for eliciting, representing, and evaluating knowledge structures offer a sensitive and objective means for evaluating student learning in virtual environments and medical simulations.

Distributed interactive virtual environments for collaborative experiential learning and training independent of distance over Internet2.

Medical knowledge and skills essential for tomorrow's healthcare professionals continue to change faster than ever before creating new demands in medical education. Project TOUCH (Telehealth Outreach for Unified Community Health) has been developing methods to enhance learning by coupling innovations in medical education with advanced technology in high performance computing and next generation Internet2 embedded in virtual reality environments (VRE), artificial intelligence and experiential active learning. Simulations have been used in education and training to allow learners to make mistakes safely in lieu of real-life situations, learn from those mistakes and ultimately improve performance by subsequent avoidance of those mistakes. Distributed virtual interactive environments are used over distance to enable learning and participation in dynamic, problem-based, clinical, artificial intelligence rules-based, virtual simulations. The virtual reality patient is programmed to dynamically change over time and respond to the manipulations by the learner. Participants are fully immersed within the VRE platform using a head-mounted display and tracker system. Navigation, locomotion and handling of objects are accomplished using a joy-wand. Distribution is managed via the Internet2 Access Grid using point-to-point or multi-casting connectivity through which the participants can interact. Medical students in Hawaii and New Mexico (NM) participated collaboratively in problem solving and managing of a simulated patient with a closed head injury in VRE; dividing tasks, handing off objects, and functioning as a team. Students stated that opportunities to make mistakes and repeat actions in the VRE were extremely helpful in learning specific principles. VRE created higher performance expectations and some anxiety among VRE users. VRE orientation was adequate but students needed time to adapt and practice in order to improve efficiency. This was also demonstrated successfully between Western Australia and UNM. We successfully demonstrated the ability to fully immerse participants in a distributed virtual environment independent of distance for collaborative team interaction in medical simulation designed for education and training. The ability to make mistakes in a safe environment is well received by students and has a positive impact on their understanding, as well as memory of the principles involved in correcting those mistakes. Bringing people together as virtual teams for interactive experiential learning and collaborative training, independent of distance, provides a platform for distributed "just-in-time" training, performance assessment and credentialing. Further validation is necessary to determine the potential value of the distributed VRE in knowledge transfer, improved future performance and should entail training participants to competence in using these tools.