Do complex span and content-embedded working memory tasks predict unique variance in inductive reasoning?

Abstract

Complex span and content-embedded tasks are two kinds of tasks that are designed to measure maintenance and processing in the working memory system. However, a key functional difference between these task types is that complex span tasks require the maintenance of information that is not relevant to the processing task, whereas content-embedded tasks require the maintenance of task-relevant information. The purpose of the present research was to test the hypothesis that more unique variance in inductive reasoning would be explained by content-embedded tasks than by complex span tasks, given that inductive reasoning requires reasoners to maintain and manipulate task-relevant information in order to arrive to a solution. A total of 384 participants completed three complex span tasks, three content-embedded tasks, and three inductive reasoning tasks. The primary structural equation model explained 51% of the variance in inductive reasoning; 45% of the variance in inductive reasoning was uniquely predicted by the content-embedded latent factor, 6% of the variance was predicted by shared variance between the content-embedded and complex span latent factors, and less than 1% was uniquely predicted by the complex span latent factor. These outcomes provide a novel extension to the small but growing literature showing an advantage of using content-embedded rather than complex span tasks for predicting higher-level cognition.