Please use this identifier to cite or link to this item: http://dx.doi.org/10.18419/opus-9753
|Title:||A systematic exploration of uncertainty in interactive systems|
|Abstract:||Uncertainty is an inherent part of our everyday life. Humans have to deal with uncertainty every time they make a decision. The importance of uncertainty additionally increases in the digital world. Machine learning and predictive algorithms introduce statistical uncertainty to digital information. In addition, the rising number of sensors in our surroundings increases the amount of statistically uncertain data, as sensor data is prone to measurement errors. Hence, there is an emergent need for practitioners and researchers in Human-Computer Interaction to explore new concepts and develop interactive systems able to handle uncertainty. Such systems should not only support users in entering uncertainty in their input, but additionally present uncertainty in a comprehensible way. The main contribution of this thesis is the exploration of the role of uncertainty in interactive systems and how novel input and output methods can support researchers and designers to efficiently and clearly communicate uncertainty. By using empirical methods of Human-Computer Interaction and a systematic approach, we present novel input and output methods that support the comprehensive communication of uncertainty in interactive systems. We further integrate our results in a simulation tool for end-users. Based on related work, we create a systematic overview of sources of uncertainty in interactive systems to support the quantification of uncertainty and identify relevant research areas. The overview can help practitioners and researchers to identify uncertainty in interactive systems and either reduce or communicate it. We then introduce new concepts for the input of uncertain data. We enhance standard input controls, develop specific slider controls and tangible input controls, and collect physiological measurements. We also compare different representations for the output of uncertainty to make recommendations for their usage. Furthermore, we analyze how humans interpret uncertain data und make suggestions on how to avoid misinterpretation and statistically wrong judgements. We embed the insights gained from the results of this thesis in an end-user simulation tool to make it available for future research. The tool is intended to be a starting point for future research on uncertainty in interactive systems and foster communicating uncertainty and building trust in the system. Overall, our work shows that user interfaces can be enhanced to effectively support users with the input and output of statistically uncertain information.|
|Appears in Collections:||05 Fakultät Informatik, Elektrotechnik und Informationstechnik|
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