Cognitive modelling shares many features with statistical modelling, making it seem trivial to borrow from the practices of robust Bayesian statistics to protect the practice of robust cognitive modelling. We take one aspect of statistical workflow--prior predictive checks--and explore how they might be applied to a cognitive modelling task. We…

Research has shown that novel words can be learned through the mechanism of statistical or cross-situational word learning (CSWL). So far, CSWL studies using adult populations have focused on the presentation of spoken words. However, words can also be learned through their written form. This study compared auditory and orthographic presentations…

Learning analytics, referring to the measurement, collection, analysis, and reporting of data about learners and their contexts in order to optimize learning and the environments in which it occurs, is proving to be a powerful approach for understanding and improving science learning. However, few studies focused on leveraging learning analytics…

Identifying patterns in the world requires noticing not only unusual occurrences, but also unusual absences. We examined how people learn from absences, manipulating the extent to which an absence is expected. People can make two types of inferences from the absence of an event: either the event is possible but has not yet occurred, or the event…

There is a wealth of evidence that people's reasoning is influenced by explanatory considerations. Little is known, however, about the exact form this influence takes, for instance about whether the influence is unsystematic or because of people's following some rule. Three experiments investigate the descriptive adequacy of a precise proposal to…

Statistical mediation allows researchers to investigate potential causal effects of experimental manipulations through intervening variables. It is a powerful tool for assessing the presence and strength of postulated causal mechanisms. Although mediation is used in certain areas of psychology, it is rarely applied in cognitive psychology and…

This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…

Randomized controlled trials (RCTs) admit unconfounded design-based inference--randomization largely justifies the assumptions underlying statistical effect estimates--but often have limited sample sizes. However, researchers may have access to big observational data on covariates and outcomes from RCT non-participants. For example, data from A/B…

Like scientists, children seek ways to explain causal systems in the world. But are children scientists in the strict Bayesian tradition of maximizing posterior probability? Or do they attend to other explanatory considerations, as laypeople and scientists--such as Einstein--do? Four experiments support the latter possibility. In particular, we…

We routinely observe others' choices and use them to guide our own. Whose choices influence us more, and why? Prior work has focused on the effect of perceived similarity between two individuals (self and others), such as the degree of overlap in past choices or explicitly recognizable group affiliations. In the real world, however, any dyadic…

Humans' face ability develops and matures with extensive experience in perceiving, recognizing, and interacting with faces that move most of the time. However, how facial movements affect 1 core aspect of face ability--holistic face processing--remains unclear. Here we investigated the influence of rigid facial motion on holistic and part-based…

Provided stimuli are highly distinct, the detection of changes between two briefly separated arrays appears to be achieved by an all-or-none process where either the relevant information is in working memory or observers guess. This observation suggests that it is possible to estimate the average number of items an observer was able to retain…

Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, we conducted quantitative comparisons between Bayesian inference and human inference at the level of individuals. In 3 experiments, with more than 13,000 participants, we…

Although ownership is acknowledged to exert a potent influence on various aspects of information processing, the origin of these effects remains largely unknown. Based on the demonstration that self-relevance facilitates perceptual judgments (i.e., the self-prioritization effect), here we explored the possibility that ownership enhances object…

A key assumption of dual process theory is that reasoning is an explicit, effortful, deliberative process. The present study offers evidence for an implicit, possibly intuitive component of reasoning. Participants were shown sentences embedded in logically valid or invalid arguments. Participants were not asked to reason but instead rated the…