Where science starts: spontaneous experiments in preschoolers' exploratory play

Probabilistic models of expected information gain require integrating prior knowledge about causal hypotheses with knowledge about possible actions that might generate data relevant to those hypotheses. Here we looked at whether preschoolers (mean: 54 months) recognize “action possibilities” (affordances) in the environment that allow them to isolate variables when there is information to be gained. By manipulating the physical properties of the stimuli, we were able to affect the degree to which candidate variables could be isolated; by manipulating the base rate of candidate causes, we were able to affect the potential for information gain. Children’s exploratory play was sensitive to both manipulations: given unambiguous evidence children played indiscriminately and rarely tried to isolate candidate causes; given ambiguous evidence, children both selected (Experiment 1) and designed (Experiment 2) informative interventions.     

Inferring hidden causal structure

We used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a pattern of associations and interventions on a novel causal system. Given minimal training and no feedback, participants in Experiment 1 used causal graph notation to spontaneously draw structures containing one observed cause, one unobserved common cause, and two unobserved independent causes, depending on the pattern of associations and interventions they saw. We replicated these findings with less-informative training (Experiments 2 and 3) and a new apparatus (Experiment 3) to show that the pattern of data leads to hidden causal inferences across a range of prior constraints on causal knowledge.     

A sufficient condition for pooling data

We consider the problems arising from using sequences of experiments to discover the causal structure among a set of variables, none of whom are known ahead of time to be an “outcome”. In particular, we present various approaches to resolve conflicts in the experimental results arising from sampling variability in the experiments. We provide a sufficient condition that allows for pooling of data from experiments with different joint distributions over the variables. Satisfaction of the condition allows for an independence test with greater sample size that may resolve some of the conflicts in the experimental results. The pooling condition has its own problems, but should—due to its generality—be informative to techniques for meta-analysis.     

类比归纳的相似性效应和概念效应比较

该文用两个实验比较了类比归纳中的相似性效应和概念效应。预备实验首先检验了实验所使用的人工概念符号的效度。结果显示,研究采用的人工符号能够按照实验要求准确控制被试对概念关系和相似性的估计。预备实验还显示,在只有相似性或概念信息的条件下,人们更加信任概念信息。在正式实验中,相似性信息和概念信息同时呈现,结果显示,在概念信息明确的时候,人会忽略相似性信息;但在相似性信息和明确的时候,人不会忽略概念信息,因此,文章得出结论：概念是类比归纳的基本构成要素。     

条件推理中的二元效应初探

通过预备实验选取前件(或后件)是二元(或多元)的5种条件命题的4种推理形式作为实验材料,以大学本科生为被试,考察了五种不同条件命题类型对4种推理结果的影响.结果表明命题类型、推理规则以及两者的交互作用都非常显著.这个结果进一步验证了条件推理的集合映射模型.     

Immediate and delayed effects of causal uncertainty inductions on uncertainty accessibility

Previous research has focused on enhanced processing as a response to causal uncertainty (CU), but relatively little empirical attention has been given to how CU is activated and the temporal unfolding of this activation. The current research investigates the counterintuitive idea that people inhibit causal uncertainty immediately after its activation. We find that this inhibition weakens over time. Study 1 demonstrates this inhibition effect with self-report uncertainty. Study 2 demonstrates this effect with an implicit accessibility measure. Temporary inhibition of uncertainty may be a general response when uncertainty is activated.     

Second-order conditioning of human causal learning

This article provides the first demonstration of a reliable second-order conditioning (SOC) effect in human causal learning tasks. It demonstrates the human ability to infer relationships between a cause and an effect that were never paired together during training. Experiments 1a and 1b showed a clear and reliable SOC effect, while Experiments 2a and 2b demonstrated that first-order extinction did not affect SOC. These results were similar to those found in animal and human conditioning and suggested that a similar associative mechanism could explain these effects. However, they can also be used to look into the underlying causal mental model people build and store while they are learning this task. From a cognitive view, overall results suggest that an independent rather than a chain causal mental model is stored after second-order learning in human causal tasks.     

文本阅读中回指推理发生的整合性因素

探讨回指距离、干扰词的精细描述、干扰词的典型性 对回指推理（先行词通达）的影响。包括2个实验,被试是华南师范大学一二年级本科生164名。采用移动窗口技术,要求被试阅读一定篇数（如,实验1a每个被试阅读15篇）的文章,对不同条件的探测词的反应时进行统计。实验1探讨干扰词精细描述类型（精细描述高和精细描述低）对回指推理的影响。结果表明,干扰的精细描述并非是影响回指推理的主要因素。实验2探讨干扰词和先行词的典型性类型的相对变化对回指推理的影响。结果表明高典型干扰在不同回指距离条件下都会对回指推理产生影响。本研究结果初步证明在影响回指推理的干扰典型性和干扰精细描述的二个因素中,起主要作用的是干扰的典型性     

5~6岁儿童传递推理能力的发展特点

通过有效的实验设计,在控制儿童记忆容量影响的前提下,考察了5~6岁儿童在长度传递推理和重量传递推理能力上的发展水平。结果表明:(1)5~6岁是儿童传递推理能力迅速发展的时期。在大概6岁左右,大多数儿童已经能够进行真正意义上的传递推理。(2)此年龄儿童在长度传递推理和重量传递推理能力上不具有显著差异。(3)条件排列的一致与不一致对于被试的推理成绩并不具有显著影响。     

The probability of causal conditionals

Conditionals in natural language are central to reasoning and decision making. A theoretical proposal called the Ramsey test implies the conditional probability hypothesis: that the subjective probability of a natural language conditional, P(if p then q), is the conditional subjective probability, P(q/p). We report three experiments on causal indicative conditionals and related counterfactuals that support this hypothesis. We measured the probabilities people assigned to truth table cases, P(pq), P(p notq), P( notpq) and P( notp notq). From these ratings, we computed three independent predictors, P(p), P(q/p) and P(q/ notp), that we then entered into a regression equation with judged P(if p then q) as the dependent variable. In line with the conditional probability hypothesis, P(q/p) was by far the strongest predictor in our experiments. This result is inconsistent with the claim that causal conditionals are the material conditionals of elementary logic. Instead, it supports the Ramsey test hypothesis, implying that common processes underlie the use of conditionals in reasoning and judgments of conditional probability in decision making.