Optimal Training Systems

Abstract

This report investigates the training implications provided by models built for two domains: learning biology in an online course and learning basic flight maneuvers in an unmanned aerial vehicle simulator. The biology model uses rules to decide on study behavior. The flight maneuver model uses instances of expert behavior to decide on correct flight control actions. Both models are implemented in the ACT-R cognitive architecture. Essentially, the path to optimal training in both these cases involves finding the key domain feature to which learning progress is very sensitive. Based on our results, we would posit that explicitly training on these key features would promote more efficient learning.

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Document Details

Document Type
Technical Report
Publication Date
Apr 30, 2008
Accession Number
ADA481902

Entities

People

  • Marsha Lovett
  • Michael Matessa

Organizations

  • Alion Science and Technology

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Cognition
  • Computer Science
  • Distance Learning
  • Education
  • Flight
  • Flight Instruments
  • Flight Maneuvers
  • Psychology
  • Simulations
  • Simulators
  • Statistics
  • Students
  • Training
  • Unmanned Aerial Vehicles
  • Vehicles

Readers

  • Artificial Intelligence
  • Military Training and Readiness Simulation

Technology Areas

  • Autonomy