Assessment of Army Aviators' Ability to Perform Individual and Collective Tasks in the Aviation Networked Simulator (AIRNET)

Abstract

This research evaluates the training effectiveness of the Aviation Networked Simulator (hereafter referred to as AIRNET). The research was designed to (a) assess experienced crewmembers' ability to perform selected individual and collective tasks in AIRNET and (b) identify the specific design attributes that makes it difficult for crewmembers to perform tasks to standards in AIRNET. Because the research examined only in-simulator performance, inferences about the device's training effectiveness can be drawn only from data indicating that experienced crewmembers cannot perform a task effectively in AIRNET. Specifically, it is assumed that tasks cannot be trained effectively in a device if they cannot be performed adequately in that device. Transfer-of-training studies are required to assess the AIRNET's effectiveness for training tasks that can be performed adequately in the device. The report presents detailed data on the relative effectiveness of crewmembers performing the individual and collective tasks investigated. The report also presents detailed data on crewmember ratings of the adequacy of AIRNET for both performing and training specific tasks and conclusions and recommendations about the need to modify the design of AIRNET components.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1992
Accession Number
ADA250293

Entities

People

  • Beth W. Smith
  • Kenneth D. Cross

Tags

Communities of Interest

  • Air Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Acquisition
  • Air Defense
  • Aircrafts
  • Ammunition
  • Artillery Fire
  • Attack Aircraft
  • Attack Helicopters
  • Communication Channels
  • Communication Systems
  • Employment
  • Formation Flight
  • Ground Vehicles
  • Low Altitude
  • Plastic Explosives
  • Psychology
  • Radio Equipment
  • Social Sciences

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Aviation Science / Aeronautics.
  • Computational Modeling and Simulation

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks