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    This study introduces a new method for drawing evaluation structures, which are hierarchical representations of human cognition. The proposed layer-assignment technique improves user preference and understanding of these complex cognitive graphs.

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    Area of Science:

    • Cognitive Science
    • Computer Science
    • Graph Theory

    Background:

    • Evaluation structures represent hierarchical human cognition derived from interviews using the evaluation grid method.
    • These structures can be formally defined as directed acyclic graphs (DAGs).
    • Existing methods for drawing DAGs may not fully meet the specific requirements for visualizing evaluation structures.

    Purpose of the Study:

    • To propose a novel layer-assignment method for drawing evaluation structures.
    • To adapt the Sugiyama framework for the specific needs of visualizing cognitive hierarchies.
    • To enhance the user comprehension and preference of evaluation structure visualizations.

    Main Methods:

    • A layer-assignment method was developed, integrated within the Sugiyama framework.
    • The method specifically addresses the requirements for drawing directed acyclic graphs representing evaluation structures.
    • User evaluations were conducted to assess the effectiveness of the proposed visualization technique.

    Main Results:

    • The proposed layer-assignment method successfully generates layered graph drawings of evaluation structures.
    • User evaluations indicated a preference for the graph drawings produced by the new method.
    • The visualizations aided significantly in users' understanding of the evaluation structures.

    Conclusions:

    • The developed layer-assignment method is effective for visualizing evaluation structures.
    • This approach enhances user experience and facilitates a better understanding of cognitive hierarchies.
    • The integration with the Sugiyama framework provides a robust solution for drawing complex DAGs in cognitive science.