Pathfinder Networks for Measuring Operator Mental Model Structure with a Simple Autopilot System

Author:

Politowicz Michael S.12,Sato Tetsuya2,Chancey Eric T.1,Yamani Yusuke2

Affiliation:

1. National Aeronautics and Space Administration (NASA), Langley Research Center, Hampton, VA

2. Old Dominion University, Norfolk, VA

Abstract

Pathfinder networks are a method to represent mental models from empirically generated pairwise relatedness ratings. This study examined the effects of training exposure on mental model structures based on relatedness ratings collected using the Target Rating method. Forty-eight participants read instruction slides with or without explicit information on the functionality of an autopilot system (Advanced Mental Model or Basic Mental Model groups, respectively). Participants provided relatedness ratings and completed a comprehension test. The Advanced Mental Model group had more common links with the expected model, higher within-group network similarity scores, and higher mental model assessment questionnaire scores than the Basic Mental Model group. Both groups had coherence scores above the minimum threshold for internal consistency. Pathfinder network analysis was sensitive to changes produced by a simple exposure training intervention. In practice, a simple training program may effectively influence operator mental models in novel technological environments such as Advanced Air Mobility.

Publisher

SAGE Publications

Subject

General Medicine,General Chemistry

Reference22 articles.

1. Allen R. B. (1997). Mental models and user models. In Handbook of Human-Computer Interaction (pp. 49–63). Elsevier. https://doi.org/10.1016/B978-044481862-1.50069-8

2. Chancey E. T., Politowicz M. S. (2020). Designing and training for appropriate trust in increasingly autonomous Advanced Air Mobility operations: A mental model approach; Version 1 (NASA/TM–20205003378). NASA technical memorandum. https://ntrs.nasa.gov/citations/20205003378

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