A TECHNIQUE TO ASSESS THE COGNITIVE COMPLEXITY OF MAN-MACHINE INTERFACE

IMC PROPOSES TO DEVELOP AN INNOVATIVE APPROACH TO THE PROBLEM OF DETERMINING THE COGNITIVE COMPLEXITY OF MAN-MACHINE INTERFACES, INCLUDING THE FOLLOWING: 1. COMPUTATIONAL TECHNIQUES FOR DERIVING CONCEPTUAL MODELS FROM THE SYSTEM FUNCTIONAL SPECIFICATIONS, AND PREDICTING MODEL EVOLUTION IN THE COURSE OF OPERATOR TRANING. 2. METHODS FOR MEASURING MODEL INFORMATION-BASED COMPLEXITY. 3. METHODS FOR DETERMINING SYSTEM FEATURES RESPONSIBLE FOR COMPLEXITY. THE RESEARCH IS PREDICATED ON THE HYPOTHESES THAT (A) COGNITIVE COMPLEXITY OF THE MAN-MACHINE INTERFACE DEPENDS ON THE STRUCTURE OF OPERATOR MENTAL MODELS CAPTURING REGULARITY OF PATTERNS IN THE CONTROLLED SYSTEM BEHAVIOR, (B) THAT MODELS CAN BE REPRESENTED AS DIRECTED WEIGHTED GRAPHS, (C) THAT EVOLUTION OF MODELS INVOLVES FORMATION OF GESTALTS, OR COHESIVE STRUCTURAL COMPONENTS WITHIN THE GRAPHS, AND (D) THAT COGNITVE COMPLEXITY DEPENDS ON THE TOPOLOGY OF THE EVOLVING STRUCTURES. PHASE I INCLUDES FEASIBILITY ASSESSMENT OF THE PROPOSED METHODS, IMPLEMENTATION DESCRIPTION, AND A DETAILED DEFINITION OF COGNITIVE COMPLEXITY WITH EMPHASIS ON MULTIFUNCTION DISPLAYS.