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.     

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.     

空间推理的脑机制：一项ERP研究

记录14名正常成人完成四种空间推理及一种基线任务（记忆任务）时的事件相关电位,对空间推理的脑电活动情况进行考察。研究结果表明,在200ms-900ms窗口,推理任务比基线任务诱发更大的正成分。对不同推理任务的比较表明,具体与抽象材料的单模型推理诱发相似的波形;单模型与有效的双模型任务诱发的ERP成分明显不同,在300ms-600ms窗口,后者比前者诱发更大的正波;在200-600ms时间窗口,存在有效结论与无有效结论的双模型问题也诱发明显不同的ERP波形。研究的结果表明,推理与记忆涉及不同的加工要求,推理需要整合前提的信息,而记忆只需要储存前提信息。在解决双模型推理问题时,从200ms开始,被试就对刺激材料进行初步的加工与判断,随后对双模型问题采用有注解的单模型加工策略。另外,不同材料的空间推理任务之间的波形较为一致,表明视觉表象并未明显影响空间推理过程。     

图形型归纳推理的神经机制:一项fMRI研究

利用fMRI脑成像技术探讨图形型归纳推理的神经机制。设计了一种由图形形状和条纹方向描述的简单几何图形组成的归纳推理任务,这种图形型任务与以往研究中常用的语句型归纳推理任务是同质的。根据两个图形共享特征数量的不同设计了两种实验任务:共享两个特征(2T)和共享一个特征(1T),以休息基线(Rest)作为控制任务。2T和1T任务均为归纳推理任务,但2T任务包含知觉特征整合成分,而1T任务不包括。结果发现:与控制任务相比,归纳推理任务在前额区(BA6、9、11、46、47)、尾状核、壳核和丘脑等脑区有显著激活,反映了"前额皮层-纹状体-丘脑"通路在图形型归纳推理中的重要作用;图形型归纳推理中的知觉信息整合与右侧额下回(BA47)、双侧尾状核头部、壳核等脑区有关。