BackgroundA dearth of laboratory tests to study actual human approach-avoidance behavior has complicated translational research on anxiety. The elevated plus-maze (EPM) is the gold standard to assess approach-avoidance behavior in rodents.MethodsHere, we translated the EPM to humans using mixed reality through a combination of virtual and real-world elements. In two validation studies, we observed participants’ anxiety on a behavioral, physiological, and subjective level.ResultsParticipants reported higher anxiety on open arms, avoided open arms, and showed an activation of endogenous stress systems. Participants’ with high anxiety exhibited higher avoidance. Moreover, open arm avoidance was moderately predicted by participants’ acrophobia and sensation seeking, with opposing influences. In a randomized, double blind, placebo controlled experiment, GABAergic stimulation decreased avoidance of open arms while alpha-2-adrenergic antagonism increased avoidance.ConclusionThese findings demonstrate cross-species validity of open arm avoidance as a translational measure of anxiety. We thus introduce the first ecologically valid assay to track actual human approach-avoidance behavior under laboratory conditions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12915-017-0463-6) contains supplementary material, which is available to authorized users.

Planning is an important but difficult self-regulation strategy. The successful implementation of a plan requires that the plan is retrievable in everyday life when it is needed. Children in particular are unlikely to use effective strategies to internalize plans in a way that makes them easy to remember. Therefore, we designed PROMPT, a planning app to help children create and internalize plans effectively. The app included different internalization activities that were hypothesized to promote deeper or shallower processing of plans. School-aged children (N = 106, 9-14 years) used PROMPT for 27 days in their daily lives. Contrary to our hypotheses, the type of internalization activity was not associated with memory success overall. Deeper processing activities were only effective for children who spent more time performing these activities, suggesting that there were differences in how effectively children could make use of the internalization activities. These individual differences were predicted by children’s grade level and their analogical reasoning abilities, and mediated by time on task. Findings suggest that a child-appropriate planning app needs to be personalized to be effective; internalization activities have to be tailored to children’s learning prerequisites.

Digital distractions can interfere with goal attainment and lead to undesirable habits that are hard to get red rid of. Various digital self‐control interventions promise support to alleviate the negative impact of digital distractions. These interventions use different approaches, such as the blocking of apps and websites, goal setting, or visualizations of device usage statistics. While many apps and browser extensions make use of these features, little is known about their effectiveness. This systematic review synthesizes the current research to provide insights into the effectiveness of the different kinds of interventions. From a search of the ‘ACM’, ‘Springer Link’, ‘Web of Science’, ’IEEE Xplore’ and ‘Pubmed’ databases, we identified 28 digital self‐control interventions. We categorized these interventions according to their features and their outcomes. The interventions showed varying degrees of effectiveness, and especially interventions that relied purely on increasing the participants' awareness were barely effective. For those interventions that sanctioned the use of distractions, the current literature indicates that the sanctions have to be sufficiently difficult to overcome, as they will otherwise be quickly dismissed. The overall confidence in the results is low, with small sample sizes, short study duration, and unclear study contexts. From these insights, we highlight research gaps and close with suggestions for future research.

BackgroundDuring the past decade, the increasingly heterogeneous field of learning analytics has been critiqued for an over‐emphasis on data‐driven approaches at the expense of paying attention to learning designs.Method and objectiveIn response to this critique, we investigated the role of learning design in learning analytics through a systematic literature review. 161 learning analytics (LA) articles were examined to identify indicators that were based on learning design events and their associated metrics. Through this research, we address two objectives. First, to achieve a better alignment between learning design and learning analytics by proposing a reference framework, where we present possible connections between learning analytics and learning design. Second, to present how LA indicators and metrics have been researched and applied in the past.Results and conclusionIn our review, we found that a number of learning analytics papers did indeed consider learning design activities for harvesting user data. We also found a consistent increase in the number and quality of indicators and their evolution over the years.