There is growing interest in the contributions of neuroscience to educational practice; however, to date, neuroscience seems to have had little impact on education. Nonetheless, neuroscience has potential value for education on several fronts, as illustrated by the articles in this Special Topic. These articles provide excellent examples for how neuroscientific approaches can complement behavioral work, and they demonstrate how understanding the neural level can help researchers develop richer models of learning and development. These articles further show that, ideally, research efforts in neuroscience and education should be reciprocal. Specifically, education should encourage psychology and neuroscience to develop learning theories that are relevant in the real world and further improve our understanding of how specific instructional practices affect learning and achievement; in turn, psychology and neuroscience can provide insights into underlying neural and cognitive mechanisms of learning, with the overall goal to maximize human potential and learning for all.

Textbooks commonly present scientific results with graphs. However, high school students struggle with interpreting them,in part because they do not focus on the most relevant comparisons among data values. Using a pre-/posttest design, weasked whether using visuospatial cues to teach this skill to high school students could improve graph comprehension. Halfof the students were randomly assigned to complete a visuospatial learning module, and the other half completed a non-visual control learning module. Data comparison performance increased significantly between pretest and posttest for thevisuospatial group, but decreased for the control group. Teaching students how to perceptually judge relevant comparisonscan thus improve graph comprehension.

A growing body of literature demonstrating the malleability of critical higher-order cognitive functions by means of targeted interventions has incited widespread scientific interest, most notably in the form of cognitive training programs. The results are mixed and a point of contention: It has been argued that gains observed in cognitive training are mainly due to placebo effects. To address this, we examined the effect of participant expectations on one type of cognitive training that has been central to the controversy, namely n-back training, by inducing beliefs about expected outcomes. Participants receiving n-back training showed improvements in non-trained n-back performance regardless of expectations, and furthermore, expectations for positive outcomes did not result in any significant gains in an active control group. Thus, there was no detectable expectancy effect in either direction as a function of the cognitive intervention used, suggesting that training-related improvements are unlikely due solely to a placebo effect.

Objective: The efficacy of n-back training for children with attention deficit hyperactivity disorder (ADHD) was tested in a randomized controlled trial. Method: 41 children aged 7 to 14 years with ADHD were trained on an n-back task, and their performance was compared with that of an active control group (n = 39) who were trained on a general knowledge and vocabulary task. Results: The experimental group demonstrated transfer of training to a nontrained n-back task as well as to a measure of inhibitory control. These effects were correlated with the magnitude of training gains. Conclusion: Our results suggest that n-back training may be useful in addressing some of the cognitive and behavioral issues associated with ADHD.

We revisit a transfer-of-training study and analyze its data using a cognitive modeling approach. Fitting a diffusion model to participant behavior over sessions al- lows conclusions as to the underlying causes of behav- ioral changes—be they changes in cognitive strategies, adaptation to the paradigm, increasing familiarity with the stimuli, or speed of information processing. Our dif- fusion model analysis revealed that participants simul- taneously adapt speed-accuracy trade-off, increase their non-decisional response speed, and increase their speed of information processing. All three of these adaptations transferred to a similar, non-trained outcome task.

OBJECTIVE: The majority of the population will experience some cognitive decline with age. Therefore, the development of effective interventions to mitigate age-related decline is critical for older adults cognitive functioning and their quality of life. METHODS: In our randomized controlled multisite trial, we target participants working memory (WM) skills, and in addition, we focus on the interventions optimal scheduling in order to test whether and how the distribution of training sessions might affect task learning, and ultimately, transfer. Healthy older adults completed an intervention targeting either WM or general knowledge twice per day, once per day, or once every-other-day. Before and after the intervention and 3 months after training completion, participants were tested in a variety of cognitive domains, including those representing functioning in everyday life. RESULTS: In contrast to our hypotheses, spacing seems to affect learning only minimally. We did observe some transfer effects, especially within the targeted cognitive domain (WM and inhibition/interference), which remained stable at the 3-month follow-up. DISCUSSION: Our findings have practical implications by showing that the variation in training schedule, at least within the range used here, does not seem to be a crucial element for training benefits.