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The Multiple-Attribute Task Battery (MATB) is composed of four simultaneously running components to which a human operator responds. A prior report has quantified information content as a machine input baud rate using the Hick-Hyman and Fitt's Laws for three of the four components and defines a strategy function. This report covers methods to quantify information content of the fourth component, creating a single metric which describes overall task complexity and evaluates human performance and strategy. Six MATB task-scenarios (combinations of two, three, or all four MATB components) each at two input baud rates are evaluated. Subjects were also provided with a chart that shows information weighting of each MATB component. Results show a change in strategy paradigm between medium input baud rate and high input baud rate for the six task-scenarios collectively. This likely occurs because subjects only refer to the component weighting chart for strategy formulation when performing more challenging task-scenarios. Advancements made with this thesis give a better understanding of how humans process information during multitasking, provide a simpler and more effective metric for analyzing MATB human performance, and create a foundation for further model development. |
