New rule use drives the relation between working memory capacity and Raven's Advanced Progressive Matrices.

Abstract

The correlation between individual differences in working memory capacity and performance on the Raven's Advanced Progressive Matrices (RAPM) is well documented yet poorly understood. The present work proposes a new explanation: that the need to use a new combination of rules on RAPM problems drives the relation between performance and working memory capacity scores. Evidence for this account is supported by an item-based analysis of performance during standard administration of the RAPM and an experiment that manipulates the need to use new rule combinations across 2 subsets of RAPM items. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

How knowing the rules affects solving the Raven Advanced Progressive Matrices Test

“…Arguably, the sheer amount of elements and rules that need to be handled while solving an item would exceed the storage capacity of working memory. Still, working memory capacity has not been assessed directly in these studies and, to the contrary, several studies that have assessed working memory capacity have failed to find a relation with item difficulty (Salthouse & Pink, 2008;Unsworth & Engle, 2005;Wiley, Jarosz, Cushen, & Colflesh, 2011). For example, Unsworth and Engle (2005) showed that item difficulty is not at all related to working memory capacity.…”

When high working memory capacity is and is not beneficial for predicting nonlinear processes

“…The involvement of WMC is particularly high when more cues need to be considered or more complex rules need to be abstracted (Karlsson, Juslin, & Olsson 2008;Mata et al, 2012). WMC is also associated with accuracy in a prototypical rule-induction task-Raven's Progressive Matrices-particularly for items requiring complex rules (D. R. Little, Lewandowsky, & Craig, 2014;Wiley, Jarosz, Cushen, & Colflesh, 2011). Despite these compelling connections, there is only one study directly assessing how WMC affects the prediction of continuous processes: McDaniel et al (2014) suspected that higher WMC allows participants to actively maintain a range of cue-criterion values and to concurrently compare them over trials to abstract a functional rule.…”

Improving fluid intelligence with training on working memory: a meta-analysis

“…It is also highly predictive of professional and educational success (Gottfredson, 1997) and has, therefore, been a prime target of intervention. One of the core processes driving Gf, as well as other higher cognitive abilities, is WM (Wiley, Jarosz, Cushen, & Colflesh, 2011). Estimates report a shared variance of at least 50% (Kane, Hambrick, & Conway, 2005;Oberauer, Schulze, Wilhelm, & Suss, 2005), and neuroimaging evidence has demonstrated functional overlap in the lateral prefrontal and parietal cortices, implicating shared neural resources that underlie both constructs (Burgess, Gray, Conway, & Braver, 2011).…”