Towards Understanding Enjoyment and Flow in Information Visualization
This work addresses the need for standardized enjoyment evaluation in visualization, which is incremental as it builds on prior models without introducing new methods.
The paper tackles the problem of evaluating enjoyment in information visualization, which impacts performance and memorability, by relating the flow model to existing visualization evaluation frameworks and suggesting a comprehensive measurement approach.
Traditionally, evaluation studies in information visualization have measured effectiveness by assessing performance time and accuracy. More recently, there has been a concerted effort to understand aspects beyond time and errors. In this paper we study enjoyment, which, while arguably not the primary goal of visualization, has been shown to impact performance and memorability. Different models of enjoyment have been proposed in psychology, education and gaming; yet there is no standard approach to evaluate and measure enjoyment in visualization. In this paper we relate the flow model of Csikszentmihalyi to Munzner's nested model of visualization evaluation and previous work in the area. We suggest that, even though previous papers tackled individual elements of flow, in order to understand what specifically makes a visualization enjoyable, it might be necessary to measure all specific elements.