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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.

In the current literature, there are a number of cognitive training studies that use N-back tasks as their training vehicle; however, the interventions are often bland, and many studies suffer from considerable attrition rates. An increasingly common approach to increase participant engagement has been the implementation of motivational features in training tasks; yet, the effects of such "gamification" on learning have been inconsistent. To shed more light on those issues, here, we report the results of a training study conducted at two Universities in Southern California. A total of 115 participants completed 4 weeks (20 sessions) of N-back training in the laboratory. We varied the amount of "gamification" and the motivational features that might make the training more engaging and, potentially, more effective. Thus, 47 participants trained on a basic color/identity N-back version with no motivational features, whereas 68 participants trained on a gamified version that translated the basic mechanics of the N-back task into an engaging 3D space-themed "collection" game (Deveau et al. Frontiers in Systems Neuroscience, 8, 243, 2015). Both versions used similar adaptive algorithms to increase the difficulty level as participants became more proficient. Participants' self-reports indicated that the group who trained on the gamified version enjoyed the intervention more than the group who trained on the non-gamified version. Furthermore, the participants who trained on the gamified version exerted more effort and also improved more during training. However, despite the differential training effects, there were no significant group differences in any of the outcome measures at post-test, suggesting that the inclusion of motivational features neither substantially benefited nor hurt broader learning. Overall, our findings provide guidelines for task implementation to optimally target participants' interest and engagement to promote learning, which may lead to broader adoption and adherence of cognitive training.

Visual aids have been found to provide an unusually efficientmeans of risk communication for diverse and vulnerableindividuals facing high-stakes choices (e.g., health, finance,natural hazards). Research indicates the benefits of visual aidsfollow from scaffolding of cognitive and metacognitiveprocesses that enable independent evaluation andunderstanding of risk—i.e., risk literacy (see Skilled DecisionTheory; Cokely et al.,. 2012; in press). Here, we present a briefreview and progress report on the development of an onlineadaptive graph literacy tutor developed as part of theRiskLiteracy.org decision education platform. We begin witha brief review of theoretical foundations of the current tutorbased on graph comprehension theory. Next, we discuss keysteps in developing and validating our pseudo-intelligentadaptive tutor with emphasis on cognitive and psychometricitem analyses and transfer assessments (i.e., decision-makingbiases). Finally, we present recent changes in technicalimplementation of the RiskLiteracy.org platform (i.e., Pythonbased with a NoSQL database) that are designed to facilitateinteractive, yet brief (5 minute to 3 hour) and easier-to-developtraining and risk communication tutors. Discussion focuses onemerging opportunities including cognitive oriented usabilityanalyses that should help promote an effective, enjoyable, andinclusive user experience.

Can we create engaging training programs that improve working memory (WM) skills? While there are numerous procedures that attempt to do so, there is a great deal of controversy regarding their efficacy. Nonetheless, recent meta-analytic evidence shows consistent improvements across studies on lab-based tasks generalizing beyond the specific training effects (Au et al., 2014; Karbach and Verhaeghen, 2014), however, there is little research into how WM training aids participants in their daily life. Here we propose that incorporating design principles from the fields of Perceptual Learning (PL) and Computer Science might augment the efficacy of WM training, and ultimately lead to greater learning and transfer. In particular, the field of PL has identified numerous mechanisms (including attention, reinforcement, multisensory facilitation and multi-stimulus training) that promote brain plasticity. Also, computer science has made great progress in the scientific approach to game design that can be used to create engaging environments for learning. We suggest that approaches integrating knowledge across these fields may lead to a more effective WM interventions and better reflect real world conditions.

Can we create engaging training programs that improve working memory (WM) skills? While there are numerous procedures that attempt to do so, there is a great deal of controversy regarding their efficacy. Nonetheless, recent meta-analytic evidence shows consistent improvements across studies on lab-based tasks generalizing beyond the specific training effects (Au et al., 2014; Karbach and Verhaeghen, 2014), however, there is little research into how WM training aids participants in their daily life. Here we propose that incorporating design principles from the fields of Perceptual Learning (PL) and Computer Science might augment the efficacy of WM training, and ultimately lead to greater learning and transfer. In particular, the field of PL has identified numerous mechanisms (including attention, reinforcement, multisensory facilitation and multi-stimulus training) that promote brain plasticity. Also, computer science has made great progress in the scientific approach to game design that can be used to create engaging environments for learning. We suggest that approaches integrating knowledge across these fields may lead to a more effective WM interventions and better reflect real world conditions.