Adaptive user interfaces change according to the needs of each user and context by conforming their appearance, interactions, and level of automation to the operator’s cognitive state. Mental workload has been one of the most popular aspects of cognition to adapt, due to the potential to reduce stress and improve performance. Recent improvements in computing and physiological measurement have expanded possibilities for cognitive state measurement beyond workload, and now include trust and situational awareness as potential candidates for interface adaptation. However, capturing and adapting three dimensions exponentially increases complexity, and makes it difficult to adapt specific dimensions without disrupting others.
This paper presents an integrated approach for conceptualizing the combined operator cognitive state, a set of priorities for adaptation, and a taxonomy for factors that can be adapted. The operators cognitive state is conceptualized as a three-dimensional array, or tensor, with an ideal state of balanced workload, calibrated trust, and high situational awareness. This tensor permits demonstration of which operator states must be adapted first, and how each adaptation affects other states. A taxonomy of candidate adaptation factors is presented within this context, enabling future designers to explore and implement this methodology within their own future work.
Keywords
ADAPTIVE,AUTOMATION,COGNITIVE,HUMAN FACTORS
Additional Keywords
Workload, Trust, Situational Awareness