and information from a variety of sources (e.g., static task context, dynamic external events occurring during the scenario, pilot's individual history, personality, training and proficiency, and simulated physiological data), predicted the effects of this state within the constrained context of the demonstration task, and suggested and implemented specific GUI adaptation strategies based on the pilot's individual information presentation preferences (e.g., modified an icon or display to capture attention and enhance visibility). An empirical study would be required to assess the effectiveness of the adaptations in an operational context.
As a result of the ABAIS prototype demonstration, a number of specific requirements were identified for developing an operational affective adaptive interface. These include: 1) limiting the number, type, and resolution of affective states; 2) using multiple, complementary affect assessment methods; 3) providing highly individualized user data (e.g., past performance history and physiological data; 4) constraining the context in terms of situation assessment and behavioral possibilities; 5) fine-tuning the rule-bases and inferencing to "personalize" the system to the individual user-task context; and 6) implementing only 'benign' adaptations, that is, GUI / DSS modifications that at best enhance and at worst maintain current level of performance (e.g., adaptations should never limit access to existing information).
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