title: A componential model of human interaction with graphs: VI. Cognitive engineering of pie graphs.
abstract: This paper proposes and tests the following three-component model of reading a pie graph to estimate segment size: (a) selecting a mentally represented anchor segment (25%, 50%, or 75%), (b) mentally aligning representations of the anchor and target segments, and (c) mentally adjusting the size of the anchor to match the target. Experiment 1 showed that the size difference between the target and closest anchor and the angular displacement of the target from vertical predicted response times (RTs) and absolute error. Experiment 2 demonstrated that an aligned pie graph, designed to reduce the "align" portion of the process, produced faster RTs and lower error than did a regular pie graph. Experiment 3 showed that a pie graph labeled at the anchor values produced the same response times and absolute error as a regular pie graph but that a pie labeled off the anchor points produced a very different pattern of results. The discussion relates the results to the componential model and describes applications in increasing pie graph usability and developing design guidelines. Actual or potential applications of this research include guidelines for graph design and more usable pie graphs.
authors.affiliation: New Mexico State University, Las Cruces 88003, USA. gillan@crl.nmse.edu
authors.forename: D J
authors.initials: DJ
authors.lastname: Gillan
authors.forename: A B
authors.initials: AB
authors.lastname: Callahan
mesh_terms: D003071:Cognition; D003627:Data Interpretation, Statistical; D006804:Ergonomics / Q000523:psychology; D006801:Humans; D008606:Mental Processes; D011601:Psychophysics; D014481:United States