Examining the Mental Model Convergence Process and Its Consequences

Abstract

This project demonstrates the impact of mental model convergence on team performance. Results suggest that teams achieve better performance when they converge on goals, then on the approach to complete their task, and finally on how they will allocate work. These types of findings can inform training materials. Computational models developed were used to determine optimal communication patterns and run simulated experiments. Findings suggest that teams perform close to optimal when they achieve mental model convergence first and then shift to taskwork. These types of results inform the design of future human experimentation. Results were transitioned to other ONR-funded PIs and to submarine domain.

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Document Details

Document Type
Technical Report
Publication Date
Aug 16, 2013
Accession Number
ADA589019

Entities

People

  • Sara Mccomb

Organizations

  • Purdue University

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Cognition
  • Cognitive Systems Engineering
  • Computer Programs
  • Computers
  • Convergence
  • Engineering
  • Industrial Engineering
  • Manpower
  • Measurement
  • Operations Research
  • Psychological Phenomena And Processes
  • Psychology
  • Simulations
  • Students
  • Systems Engineering
  • Teamwork
  • Training

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