Examining Working Memory as an Incremental Predictor of Task Performance: A Partially Mediated Model

General intelligence, or “g”, has been shown to predict both training performance and job performance across job domains. Much research has been conducted to determine whether more specific abilities may be able to add... [ view full abstract ]

General intelligence, or “g”, has been shown to predict both training performance and job performance across job domains. Much research has been conducted to determine whether more specific abilities may be able to add incremental validity to the prediction of performance in the workplace. This specific aptitude theory has been mostly refuted in the literature, as most specific abilities have not accounted for additional variance in performance, with the exception of spatial abilities and perceptual speed, and only for specific job domains. However, there has been relatively less research conducted using working memory (WM) as an incremental predictor. Building upon Bosco, Allen, & Singh’s (2015) research which found WM to be an incremental predictor of task performance, we propose WM to be a part of a partially mediated model, such that WM indirectly predicts task performance through learning of task knowledge, and directly affects task performance independent of task knowledge. The two functions of the WM system, capacity and processing, drive these two paths, such that WM capacity enhances an individual’s ability to learn and WM processing enhances an individual’s ability to perform a task efficiently. Further, we propose that WM scores will predict learning and performance above “g” based on past research and the fact that many fluid reasoning tasks do not include measures that capture WM processes. Therefore, we will be examining the predictive utility of both a measure of Gf and a two WM tasks in the prediction of learning and task performance for a sample of ~100 undergraduate students. Participants will be given a video tutorial demonstrating the proper formatting of an APA style reference page. They will be given pre- and post-test APA knowledge assessments to examine knowledge gains from the tutorial. Lastly, they will be tasked with formatting their own APA reference pages, which will be scored for accuracy in order to examine task performance. Our goal is to provide evidence that WM processes are important independent of “g”, as well as propose a more complete partially mediated model of WM, learning, and task performance. Data collection is expected to be completed by the end of April. Support of our hypotheses would provide support for specific aptitude theory, and would open further research directions toward the examination of WM as a personnel selection tool, such as evaluating the adverse impact created by the use of WM measures.