Evaluating the Base Complexity of Planning Required in User Interface

다국어 초록 (Multilingual Abstract)

As modern system is getting complex, it has received a great interest to control the cognitive complexity that user feels. In this study, we evaluate the cognitive complexity of user interface by applying Yoon's Entropy Model, which models the users' knowledge into matrix form and provides the quantification method. The entropy model was applied to the knowledge about whether the operation is available to use or not. We proposes a quantitative measure - System Entropy - based on the quantified result of the entropy model, and experimentally examines the ability of the measure to predict the difficulty of learning to use interfaces.
Three different interfaces in system size (the number of operations and states) or system entropy were built: low system entropy and small system size, high system entropy and small system size, and high system entropy and large system size. It was hypothesized and confirmed that the performance of low-entropy interface was superior to high-entropy interface. That is, the effect of system entropy dominated the effect of system size. The proposed measure may provide a practically useful tool to interface designers by making it possible to quickly assess the complexity of alternative interfaces.