The Path Less Taken: When Working Memory Capacity Constrains Insight

The Path Less Taken: When Working Memory Capacity Constrains Insight Charles Van Stockum (charles.vanstockum@louisville.edu) Department of Psychological and Brain Sciences, University of Louisville Louisville, KY 40292 USA Marci S. DeCaro (marci.decaro@louisville.edu) Department of Psychological and Brain Sciences, University of Louisville Louisville, KY 40292 USA Abstract Working Memory Capacity Higher working memory capacity (WMC) supports performance on a wide variety of complex cognitive and academic activities (Barret, Tugade, & Engle, 2004). However, a growing body of research demonstrates that higher WMC can have disadvantages—leading individuals to employ complex performance strategies that are less optimal for a given task (cf. DeCaro & Beilock, 2010). We examine this possibility in the domain of insight problem solving. Participants (N=84) completed Matchstick Arithmetic problems thought to either rely on controlled search and retrieval processes (non-insight problems) or diverging from known mathematical constraints (insight problems). Consistent with a large body of research on WMC, higher WMC was associated with higher non-insight problem accuracy. However, higher WMC led to significantly worse insight problem-solving. Although higher WMC supports complex problem-solving strategies, relying on these may lead individuals to miss associatively-driven solutions that are important for insight. Keywords: Working memory capacity; attention; insight; problem solving. Introduction A great deal of work has demonstrated that higher working memory capacity (WMC) is advantageous to an array of complex cognitive and academic activities, such as reasoning, comprehension, and problem-solving (see Barrett, Tugade, & Engle, 2004, for a review). Indeed, WMC—the ability to hold and manipulate information in a temporary active state—has been said to be “so central to human cognition that it is hard to find activities where it is not involved” (Ericsson & Delaney, 1999, p. 259). However, a growing body of research demonstrates that higher WMC can have disadvantages—leading individuals to employ complex performance strategies that are less optimal for a given task (see DeCaro & Beilock, 2010, for a review). In the current work, we examine the possibility that higher WMC can hinder creative thinking in the form of insight problem-solving. Specifically, we examine the hypothesis that those who have the ability to implement complex problem-solving strategies may be more likely to miss associatively-driven solutions that are important for insight. WMC supports the ability to suppress distractors and guide attention toward relevant information in goal-directed tasks (McCabe, Roediger, McDaniel, Balota, & Hambrick, 2010). The predictive power of WMC as a construct stems from this domain-general capacity for attentional control, and individual differences in WMC emerge primarily when that capacity is challenged (Engle, 2002). So-called “executive attention” is accomplished via controlled processing, which is important in novel or interference-rich situations and when goals come in conflict with prepotent responses (Unsworth & Engle, 2007). A large body of research has been built around the well- established differences in performance outcomes of individuals who fall toward either extreme of the WMC scale. Kane and Engle (2000) found that individuals with lower WMC demonstrated a greater vulnerability to proactive interference, and were more likely to lose track of task goals than their higher WMC counterparts (Unsworth & Engle, 2007). Additionally, studies have found that individuals with lower WMC display higher rates of attentional capture (Conway, Cowan, & Bunting, 2001; Kane, Bleckley, Conway, & Engle, 2001), and have greater difficulty discriminating relevant and irrelevant information (Unsworth & Engle, 2007). It is no surprise that the ability of higher WMC individuals to control attention leads to greater ability to implement more difficult, multi-step problem-solving strategies (Engle, 2002). Indeed, the ability to execute complex strategies may lead individuals to select strategies in line with their ability—even if the task does not call for a controlled processing approach. Beilock and DeCaro (2007) explored this idea by examining the strategy selection of higher and lower WMC individuals completing Luchins’ (1946) water jug task. This task requires individuals to use three depicted water jugs with varying capacities (e.g., Jug A=23, Jug B=96, and Jug C=3) to fill a “goal” jug with a certain capacity (e.g., 67). For example, one might fill Jug B, then pour that amount into Jug A, and then pour the remaining amount into Jug C twice (i.e., B-A-2C). Participants were explicitly instructed to mentally derive the answers (i.e., without the use of paper), and use the simplest strategy possible. The first few problems were solve-able using a single complex formula (B-A-2C). The final few problems could also be solved using this formula (e.g., Jug