Training Effectiveness Framework for Augmented and Virtual Reality: Developing a Knowledge Base
Abstract
Numerous meta-analyses show that augmented reality (AR) and virtual reality (VR) technologies can be effective for training and performance enhancement. However, the broad assertion of AR/VR effectiveness is overly simplistic and clouds important factors influencing the generalizability of findings. Studies of AR/VR effectiveness come from disparate disciplines and perspectives that may complicate the applicability of findings from effectiveness studies. The studies include disciplines such as computer science and engineering focused on technology, education and training focused on instructional methods, and other disciplines focused on their specializations. A framework, developed for this project, cuts across differences by employing a common language with four dimensions and an outcome category, captured through five questions: 1) What is the technology? 2) What are the tasks/skills being trained? 3) Who are the users? 4) How is the technology used or integrated or trained in a situation/course? 5) What was the study outcome? That framework provides the foundation for an online knowledge base with characteristics that users can query to help probe the evidence for AR/VR technologies and their effectiveness. This report is about the frameworks development, its application to a searchable knowledge base, and the kinds of results that enable users to organize and summarize AR/VR effectiveness study findings for their own needs. An initial knowledge base of 64 studies that employs the framework can grow to provide an ever-improving resource for users to understand how AR/VR can be effective.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2022
- Accession Number
- AD1206915
Entities
People
- Emily A. Fedele
- Franklin L. Moses
- James Belanich
Organizations
- Institute for Defense Analyses