Assessment of Driving Mental Models as a Predictor of Crashes and Moving Violations

Assessment of Driving Mental Models as a Predictor of Crashes and Moving Violations. (May 2011) Gonzalo Javier Muñoz Gálvez, B. S., Pontificia Universidad Católica de Chile Chair of Advisory Committee: Dr. Winfred Arthur, Jr. The purpose of the current study was to assess the efficacy of mental models as a predictor of driving outcomes. In contrast to more traditional measures of knowledge, mental models capture the configural property of knowledge, that is, an individual’s understanding of the interrelationships that exist among critical concepts within a particular knowledge domain. Given that research has consistently shown the usefulness of mental models for the prediction of performance in a number of settings, it was hypothesized that the development of accurate driving mental models would also play an important role in the prediction of driving outcomes, especially in comparison to traditional measures of driving knowledge—such as the multiple-choice type tests typically required to obtain a driver license. Mental models of 130 college students (52% females) between 17 and 21 yearsold (M = 18.68, SD = 0.80) were analyzed and compared to a subject matter expert (SME) referent structure using Pathfinder. A statistically significant correlation was found for mental model accuracy and moving violations (r = –.18, p <.05), but not for at-

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