Examining the Incremental Validity of Working Memory for Predicting Learning and Task Performance: A Partial Mediation Model

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Virginia Tech

General intelligence (“g”) has long been used as an effective predictor of both learning and job performance. Further, other more specific cognitive abilities have not been able to consistently predict incremental variance in job knowledge and job performance beyond “g”. However, the processes associated with working memory (WM) are important for these outcomes and are not captured by our traditional tests of “g”. This study tested a partial mediation model in which working memory (WM) incrementally predicts task performance above “g” through task knowledge and through a direct effect. Participants were given measures of “g” and WM in a lab. They were then given a learning opportunity and a task that applies this newly learned knowledge in order to tests the effects of WM. Results indicate that WM explains additional variance in both task knowledge and task performance, and the partial mediation model was supported using one of the two WM tasks used.

Working Memory, Intelligence, Knowledge, Learning, Performance