Numerous recent studies seem to provide evidence for the general intellectual benefits of working memory training. In reviews of the training literature, Shipstead, Redick, and Engle (2010, 2012) argued that the field should treat recent results with a critical eye. Many published working memory training studies suffer from design limitations (no-contact control groups, single measures of cognitive constructs), mixed results (transfer of training gains to some tasks but not others, inconsistent transfer to the same tasks across studies), and lack of theoretical grounding (identifying the mechanisms responsible for observed transfer). The current study compared young adults who received 20 sessions of practice on an adaptive dual n-back program (working memory training group) or an adaptive visual search program (active placebo-control group) with a no-contact control group that received no practice. In addition, all subjects completed pretest, midtest, and posttest sessions comprising multiple measures of fluid intelligence, multitasking, working memory capacity, crystallized intelligence, and perceptual speed. Despite improvements on both the dual n-back and visual search tasks with practice, and despite a high level of statistical power, there was no positive transfer to any of the cognitive ability tests. We discuss these results in the context of previous working memory training research and address issues for future working memory training studies.

Working memory is a critical element of complex cognition, particularly under conditions of distraction and interference. Measures of working memory capacity correlate positively with many measures of real-world cognition, including fluid intelligence. There have been numerous attempts to use training procedures to increase working memory capacity and thereby performance on the real-world tasks that rely on working memory capacity. In the study reported here, we demonstrated that training on complex working memory span tasks leads to improvement on similar tasks with different materials but that such training does not generalize to measures of fluid intelligence.

Cogmed working memory training is sold as a tool for improving cognitive abilities, such as attention and reasoning. At present, this program is marketed to schools as a means of improving underperforming students’ scholastic performance, and is also available at clinical practices as a treatment for ADHD. We review research conducted with Cogmed software and highlight several concerns regarding methodology and replicability of findings. We conclude that the claims made by Cogmed are largely unsubstantiated, and recommend that future research place greater emphasis on developing theoretically motivated accounts of working memory training.

Measures of working memory capacity (WMC), such as complex span tasks (e.g., operation span), have become some of the most frequently used tasks in cognitive psychology. However, due to the length of time it takes to complete these tasks many researchers trying to draw conclusions about WMC forgo properly administering multiple tasks. But can the complex span tasks be shortened to take less administration time? We address this question by splitting the tasks into three blocks of trials, and analyzing each block's contribution to measuring WMC and predicting fluid intelligence (Gf). We found that all three blocks of trials contributed similarly to the tasks' ability to measure WMC and Gf, and the tasks can therefore be substantially shortened without changing what they measure. In addition, we found that cutting the number of trials by 67 % in a battery of these tasks still accounted for 90 % of the variance in their measurement of Gf. We discuss our findings in light of administering the complex span tasks in a method that can maximize their accuracy in measuring WMC, while minimizing the time taken to administer.

Previous research has identified several cognitive abilities that are important for multitasking, but few studies have attempted to measure a general multitasking ability using a diverse set of multitasks. In the final dataset, 534 young adult subjects completed measures of working memory (WM), attention control, fluid intelligence, and multitasking. Correlations, hierarchical regression analyses, confirmatory factor analyses, structural equation models, and relative weight analyses revealed several key findings. First, although the complex tasks used to assess multitasking differed greatly in their task characteristics and demands, a coherent construct specific to multitasking ability was identified. Second, the cognitive ability predictors accounted for substantial variance in the general multitasking construct, with WM and fluid intelligence accounting for the most multitasking variance compared to attention control. Third, the magnitude of the relationships among the cognitive abilities and multitasking varied as a function of the complexity and structure of the various multitasks assessed. Finally, structural equation models based on a multifaceted model of WM indicated that attention control and capacity fully mediated the WM and multitasking relationship. (PsycINFO Database Record