Priming Locus of Control to affect performance

Recent research suggests that the personality trait Locus of Control (LOC) can be a reliable predictor of performance when learning a new visualization tool. While these results are compelling and have direct implications to visualization design, the relationship between a user's LOC measure and their performance is not well understood. We hypothesize that there is a dependent relationship between LOC and performance; specifically, a person's orientation on the LOC scale directly influences their performance when learning new visualizations. To test this hypothesis, we conduct an experiment with 300 subjects using Amazon's Mechanical Turk. We adapt techniques from personality psychology to manipulate a user's LOC so that users are either primed to be more internally or externally oriented on the LOC scale. Replicating previous studies investigating the effect of LOC on performance, we measure users' speed and accuracy as they use visualizations with varying visual metaphors. Our findings demonstrate that changing a user's LOC impacts their performance. We find that a change in users' LOC results in performance changes.