Adding Types,But Not Tokens,Affects Property Induction

The extent to which we generalize a novel property from a sample of familiar instances to novel instances depends on the sample composition. Previous property induction experiments have only used samples consisting of novel types (unique entities). Because real-world evidence samples often contain redundant tokens (repetitions of the same entity), we studied the effects on property induction of adding types and tokens to an observed sample. In Experiments 1–3, we presented participants with a sample of birds or flowers known to have a novel property and probed whether this property generalized to novel items varying in similarity to the initial sample. Increasing the number of novel types (e.g., new birds with the target property) in a sample produced tightening, promoting property generalization to highly similar stimuli but decreasing generalization to less similar stimuli. On the other hand, increasing the number of tokens (e.g., repeated presentations of the same bird with the target property) had little effect on generalization. Experiment 4 showed that repeated tokens are encoded and can benefit recognition, but appear to be given little weight when inferring property generalization. We modified an existing Bayesian model of induction (Navarro, Dry, & Lee, 2012) to account for both the information added by new types and the discounting of information conveyed by tokens.     

Do details bug you? Effects of perceptual richness in learning about biological change

People often have difficulty in understanding processes of biological change, and they typically reject drastic life cycle changes such as metamorphosis, except for animals with which they are familiar. Even after a lesson about metamorphosis, people often do not generalize to animals not seen during the lesson. This might be partially due to the perceptual richness of the diagrams typically used during lessons on metamorphosis, which serves to emphasize the individual animal rather than a class of animals. In two studies, we examined whether the perceptual richness of a diagram influences adults' learning and transfer of knowledge about metamorphosis. One study was conducted in a laboratory setting, and the other was online. In both studies, adults who saw the bland diagram during the lesson accurately transferred more than adults who saw the rich diagram during the lesson.     

Are there gender differences in cognitive reflection? Invariance and differences related to mathematics

ABSTRACT

Cognitive reflection is recognized as an important skill, which is necessary for making advantageous decisions. Even though gender differences in the Cognitive Reflection test (CRT) appear to be robust across multiple studies, little research has examined the source of the gender gap in performance. In Study 1, we tested the invariance of the scale across genders. In Study 2, we investigated the role of math anxiety, mathematical reasoning, and gender in CRT performance. The results attested the measurement equivalence of the Cognitive Reflection Test – Long (CRT- L), when administered to male and female students. Additionally, the results of the mediation analysis showed an indirect effect of gender on CRT-L performance through mathematical reasoning and math anxiety. The direct effect of gender was no longer statistically significant after accounting for the other variables. The current findings suggest that cognitive reflection is affected by numerical skills and related feelings.     

The Influence of Rater Effects in Training Sets on the Psychometric Quality of Automated Scoring for Writing Assessments

Automated essay scoring engines (AESEs) are becoming increasingly popular as an efficient method for performance assessments in writing, including many language assessments that are used worldwide. Before they can be used operationally, AESEs must be “trained” using machine-learning techniques that incorporate human ratings. However, the quality of the human ratings used to train the AESEs is rarely examined. As a result, the impact of various rater effects (e.g., severity and centrality) on the quality of AESE-assigned scores is not known. In this study, we use data from a large-scale rater-mediated writing assessment to examine the impact of rater effects on the quality of AESE-assigned scores. Overall, the results suggest that if rater effects are present in the ratings used to train an AESE, the AESE scores may replicate these effects. Implications are discussed in terms of research and practice related to automated scoring.     

Response acquisition by zebrafish (Danio rerio) with delayed reinforcement

Zebrafish (Danio rerio) is a common vertebrate animal model in biomedical research and is a promising species for studying how genes interact with environmental factors in determining behavior. The present study investigated how reinforcement parameters affect zebrafish behavior by assessing response acquisition with delayed reinforcement, which has been studied with other species (e.g., rats, pigeons, humans, etc.) but not with zebrafish. Twenty‐four experimentally naïve subjects were exposed to a tandem fixed‐ratio 1 differential‐reinforcement‐of‐other‐behavior x‐s schedule of reinforcement, where x varied across subjects. There were six different delay‐to‐reinforcement durations and sets of four fish were assigned to each delay duration. All of the fish assigned to a 0‐, 0.5‐, or 1‐s delay acquired responding. Two fish acquired responding with a 3‐s delay and one fish appeared to have acquired it with a 6‐s delay although the latter result was less clear. None acquired responding with a 12‐s delay. These results suggest that zebrafish behavior is sensitive to delays to reinforcement and the time frame over which reinforcement is effective may be limited approximately to 6 s. This time frame is shorter than that found with other species. Practical and theoretical implications of the present finding are discussed.     

Fundamental failure to think logically about scientific questions: An illustration of tunnel vision with the application of Wason's Card Selection Test to criminal evidence

Logic and science are in some respects fundamentally different disciplines, in that for example, application of rules of logic can yield conclusions that are at odds with physical reality. Not surprisingly, people have ample difficulty with logical thinking. Nonetheless, in some instances, logical thinking can fuel empirical decision making. In the current research, it was established that applying rules of logic to a particular area of empirical decision making, that is, criminal fact finding, is indeed quite difficult (Study 1). Furthermore, the ability to think logically was found to be associated with superior evaluation of criminal evidence (Study 2). Implications of these findings are discussed.     

A threatening exchange: Gender and life history strategy predict perceptions and reasoning about sexual harassment

Sexual harassment is a serious societal issue, with extensive economic and psychological consequences, yet it is also an ill-defined construct fundamentally defined in terms of subjective perception. The current work was designed to examine the ways in which individual differences between people are systematically related to different perceptions of sexual harassment scenarios, as well as reasoning about those harassment situations. Participants (N = 460) read several possible harassment scenarios and rated how uncomfortable they would find them. They then also evaluated a quid pro quo sexual harassment situation in terms of their interpretation of it as a threat or a social exchange and completed a deductive reasoning task about the same situation. Females and individuals with slow life history strategies were more uncomfortable with potential harassment situations and were more likely to interpret the quid pro quo scenario as a threat. Further, interpreting the scenario as a threat was associated with poorer performance on the deductive logic task, compared to those who interpreted the scenario as a social exchange.     

Identifying expectations about the strength of causal relationships

When we try to identify causal relationships, how strong do we expect that relationship to be? Bayesian models of causal induction rely on assumptions regarding people’s a priori beliefs about causal systems, with recent research focusing on people’s expectations about the strength of causes. These expectations are expressed in terms of prior probability distributions. While proposals about the form of such prior distributions have been made previously, many different distributions are possible, making it difficult to test such proposals exhaustively. In Experiment 1 we used iterated learning—a method in which participants make inferences about data generated based on their own responses in previous trials—to estimate participants’ prior beliefs about the strengths of causes. This method produced estimated prior distributions that were quite different from those previously proposed in the literature. Experiment 2 collected a large set of human judgments on the strength of causal relationships to be used as a benchmark for evaluating different models, using stimuli that cover a wider and more systematic set of contingencies than previous research. Using these judgments, we evaluated the predictions of various Bayesian models. The Bayesian model with priors estimated via iterated learning compared favorably against the others. Experiment 3 estimated participants’ prior beliefs concerning different causal systems, revealing key similarities in their expectations across diverse scenarios.     

Publication standards in infancy research: Three ways to make Violation-of-Expectation studies more reliable

The Violation-of-Expectation paradigm is a widespread paradigm in infancy research that relies on looking time as an index of surprise. This methodological review aims to increase the reliability of future VoE studies by proposing to standardize reporting practices in this literature. I review 15 VoE studies on false-belief reasoning, which used a variety of experimental parameters. An analysis of the distribution of p-values across experiments suggests an absence of p-hacking. However, there are potential concerns with the accuracy of their measures of infants’ attention, as well as with the lack of a consensus on the parameters that should be used to set up VoE studies. I propose that (i) future VoE studies ought to report not only looking times (as a measure of attention) but also looking-away times (as an equally important measure of distraction); (ii) VoE studies must offer theoretical justification for the parameters they use, and (iii) when parameters are selected through piloting, pilot data must be reported in order to understand how parameters were selected. Future VoE studies ought to maximize the accuracy of their measures of infants’ attention since the reliability of their results and the validity of their conclusions both depend on the accuracy of their measures.