Toward a Model of Knowledge-Based Graph Comprehension

Abstract. Research on graph comprehension has been concerned with relatively low-level information extraction. However, laboratory studies often produce conflicting findings because real-world graph interpretation requires going beyond the data presentation to make inferences and solve problems. Furthermore, in real-world settings, graphical information is presented in the context of relevant prior knowledge. According to our model, knowledge-based graph comprehension involves an interaction of top-down and bottom up processes. Several types of knowledge are brought to bear on graphs: domain knowledge, graphical skills, and explanatory skills. During the initial processing, people chunk the visual features in the graphs. Nevertheless, prior knowledge guides the processing of visual features. We outline the key assumptions of this model and show how this model explains the extant data and generates testable predictions.

Rationality, Perception and the All-Seeing Eye

Seeing—perception and vision—is implicitly the fundamental building block of the literature on rationality and cognition. Herbert Simon and Daniel Kahneman’s arguments against the omniscience of economic agents—and the concept of bounded rationality—depend critically on a particular view of the nature of perception and vision. We propose that this framework of rationality merely replaces economic omniscience with perceptual omniscience. We show how the cognitive and social sciences feature a pervasive but problematic meta-assumption that is characterized by an “all-seeing eye.” We raise concerns about this assumption and discuss different ways in which the all-seeing eye manifests itself in existing research on (bounded) rationality. We first consider the centrality of vision and perception in Simon’s pioneering work. We then point to Kahneman’s work—particularly his article “Maps of Bounded Rationality”—to illustrate the pervasiveness of an all-seeing view of perception, as manifested in the extensive use of visual examples and illusions. Similar assumptions about perception can be found across a large literature in the cognitive sciences. The central problem is the present emphasis on inverse optics—the objective nature of objects and environments: e.g., size, contrast, color. This framework ignores the nature of the organism and perceiver. We argue instead that reality is constructed and expressed, and we discuss the species-specificity of perception, as well as perception as a user interface. We draw on vision science as well as the arts to develop an alternative understanding of rationality in the cognitive and social sciences. We conclude with a discussion of the implications of our arguments for the rationality and decision making literature in cognitive psychology and behavioral economics, along with suggesting some ways forward