Adaptive User Experience Based on Detecting User Perplexity

As humans, our abilities and performance while carrying out different tasks differ due to several factors, such as health conditions, mental processing capabilities, emotional feelings, task difficulty and the desire to achieve it. Additionally, understanding human feelings and states that may entail information about achieving certain tasks can be an intricate job. Subsequently, this paper aims to outline the main aspects of self-ware systems and adaptive Human-Computer Interaction styles. There is an opportunity to enable machines to be more perceptive devices that can recognise innate
human factors, which could be used to assist and improve the human's performance and effectiveness. This paper shows use-case scenarios of intelligent and affect-aware systems as well as presenting a conceptual model for User Perplexity as an important aspect an adaptive system should be able to capture to instantiate appropriate adaptation to the user experience. We argue that there is a subtle difference between adaptive user interfaces and adaptive user experiences.