The influence of temporal distributions on causal induction from tabular data

Two experiments investigated the joint influence of statistical and temporal information on causal inference from tabular data. Participants were presented with unambiguous data sets containing information about relative effect frequencies in cause-present and cause-absent situations. In addition to contingency information, the stimuli also revealed information about the temporal distribution of effects. The participants took this information into account when making causal judgments, so that the mere advancing or postponing of the effect in time was attached with causal significance, even when the cause did not increase the overall probability of the effect. These results cannot be reconciled with standard contingency accounts of causal induction.     

Causal judgement as evaluation of evidence: The use of confirmatory and disconfirrnatory information

There are four kinds of contingency information: occurrences and nonoccurrences of an effect in the presence and absence of a cause. In two experiments participants made judgements about sets of stimulus materials in which one of these four kinds had zero frequency. The experiments tested two kinds of predictions derived from the evidential evaluation model of causal judgement, which postulates that causal judgement depends on the proportion of instances evaluated as confirmatory for the cause being judged. The model predicts significant effects of manipulating the frequency of one kind of contingency information in the absence of changes in the objective contingency. The model also predicts that extra weight will be given to one kind of confirmatory information when the other kind has zero frequency, and to one kind of disconfirmatory information when the other kind has zero frequency. Results supported both sets of predictions, and also disconfirmed predictions of the power probabilistic contrast theory of causal judgement. This research therefore favours an account of causal judgement in which contingency information is transformed into evidence, and judgement is based on the net confirmatory or disconfirmatory value of the evidence.     

Effects of a Dependent Group-Oriented Contingency on Middle School Physical Education Students’ Fair Play Behaviors

This study investigated the effects of a dependent group-oriented contingency on the supportive and non-supportive fair play behaviors of 6th grade students engaged in volleyball games as part of their physical education instruction. Six students, one male and one female per class, from three classes, identified as demonstrating low incidences of supportive behaviors during volleyball games, were participants in this study. A multiple baseline across classes design was used to examine the data. During baseline few incidences of non-supportive behaviors occurred among all six students. However, the participants seldom displayed supportive behaviors during games (i.e., encouraged each other). Following the introduction of the dependent group contingency, supportive behaviors for all participants increased. Follow-up data, collected in an alternative setting, indicated variable maintenance. The results are discussed in the context of group contingencies and social behaviors in sports.     

The role of mechanism and covariation information in causal belief updating

The present study is aimed at identifying how prior causal beliefs and covariation information contribute to belief updating when evidence, either compatible or contradictory with those beliefs, is provided. Participants were presented with a cover story with which it was intended to activate or generate a causal belief. Variables related to the prior belief (the type of information, the strength of the cause-effect causal link, and how confident the participant was that the link existed) were assessed. Subsequently, participants were presented with covariational information and were asked to update their beliefs in light of the new evidence. Information reliability, prior belief's causal influence magnitude, and the cause-effect level of contingency portrayed by the new information--but not the type of the prior belief--are shown to directly determine belief updating.     

Selecting effective intervention strategies for escape-maintained academic-performance problems: Consider giving 'em a break!

This study compared consequence-and antecedent-based strategies to determine which treatments or combination of treatments produced the strongest improvements in math computation fluency with four elementary-aged students whose math computation was under the control of an escape contingency. Functional analyses were conducted to identify elementary-school students whose academic responding was under a negative-reinforcement contingency. A multielement design was then used to examine the impact of four treatments (DNRA, DRA, task choice, and task choice plus DRA) on each student's rate of correct digits per min. All four treatments increased rate of responding. Differentiated results were obtained for all participants, indicating a reliable effect. Yet, participants responded differently to the treatments, illustrating the need to investigate and adapt interventions for escape-motivated behavior on a case-by-case basis. Results are also discussed in terms of the effectiveness of choice relative to reinforcement procedures, whether there were additional benefits to combining treatments, and which type of reinforcement procedures (DRA or DNRA) appears to be more effective for students whose behavior is under the control of an escape contingency.     

The influence of the number of relevant causes on the processing of covariation information in causal reasoning

Research on causal reasoning has focused on the influence of covariation between candidate causes and effects on causal judgments. We suggest that the type of covariation information to which people attend is affected by the task being performed. For this, we manipulated the test questions for the evaluation of contingency information and observed its influence on both contingency learning and subsequent causal selections. When people select one cause related to an effect, they focus on conditional contingencies assuming the absence of alternative causes. When people select two causes related to an effect, they focus on conditional contingencies assuming the presence of alternative causes. We demonstrated this use of contingency information in four experiments.     

Cue interaction and judgments of causality: Contributions of causal and associative processes

In four experiments, the predictions made by causal model theory and the Rescorla-Wagner model were tested by using a cue interaction paradigm that measures the relative response to a given event based on the influence or salience of an alternative event. Experiments 1 and 2 uncorrelated two variables that have typically been confounded in the literature (causal order and the number of cues and outcomes) and demonstrated that overall contingency judgments are influenced by the causal structure of the events. Experiment 3 showed that trial-by-trial prediction responses, a second measure of causal assessment, were not influenced by the causal structure of the described events. Experiment 4 revealed that participants became less sensitive to the influence of the causal structure in both their ratings and their predictions as trials progressed. Thus, two experiments provided evidence for high-level (causal reasoning) processes, and two experiments provided evidence for low-level (associative) processes. We argue that both factors influence causal assessment, depending on what is being asked about the events and participants' experience with those events.     

Two mechanisms of human contingency learning

How do humans learn contingencies between events? Both pathway-strengthening and inference-based process models have been proposed to explain contingency learning. We propose that each of these processes is used in different conditions. Participants viewed displays that contained single or paired objects and learned which displays were usually followed by the appearance of a dot. Some participants predicted whether the dot would appear before seeing the outcome, whereas other participants were required to respond quickly if the dot appeared shortly after the display. In the prediction task, instructions guiding participants to infer which objects caused the dot to appear were necessary in order for contingencies associated with one object to influence participants' predictions about the object with which it had been paired. In the response task, contingencies associated with one object affected responses to its pair mate irrespective of whether or not participants were given causal instructions. Our results challenge single-mechanism accounts of contingency learning and suggest that the mechanisms underlying performance in the two tasks are distinct.     

The impact of domain-specific beliefs on decisions and causal judgments

Extensive evidence suggests that people often rely on their causal beliefs in their decisions and causal judgments. To date, however, there is a dearth of research comparing the impact of causal beliefs in different domains. We conducted two experiments to map the influence of domain-specific causal beliefs on the evaluation of empirical evidence when making decisions and subsequent causal judgments. Participants made 120 decisions in a two-alternative forced-choice task, framed in either a medical or a financial domain. Before each decision, participants could actively search for information about the outcome (“occurrence of a disease” or “decrease in a company's share price”) on the basis of four cues. To analyze the strength of causal beliefs, we set two cues to have a generative relation to the outcome and two to have a preventive relation to the outcome. To examine the influence of empirical evidence, we manipulated the predictive power (i.e., cue validities) of the cues. Both experiments included a validity switch, where the four selectable cues switched from high to low validity or vice versa. Participants had to make a causal judgment about each cue before and after the validity switch. In the medical domain, participants stuck to the causal information in causal judgments, even when evidence was contradictory, while decisions showed an effect of both empirical and causal information. In contrast, in the financial domain, participants mainly adapted their decisions and judgments to the cue validities. We conclude that the strength of causal beliefs (1) is shaped by the domain, and (2) has a differential influence on the degree to which empirical evidence is taken into account in causal judgments and decision making.     

Programming a randomized dependent group contingency and common stimuli to promote durable behavior change

Low levels of academic engagement may impede students’ acquisition of skills. Intervening on student behavior using group contingencies may be a feasible way to increase academic engagement during group instruction. The current study examined the effect of a randomized dependent group contingency on levels of academic engagement for second‐grade participants receiving small‐group reading and writing instruction. The results showed that a randomized dependent group contingency increased the academic engagement of primary participants and several of the other participants during small‐group instruction. The findings also showed that high levels of academic engagement were maintained when common stimuli were present and the dependent group contingency was withdrawn.     

实质取样对因果强度估计的影响

使用单个目标原因和单个效果的图形集中呈现范式协变关系探讨实质取样增量（12.5%< 50%< 87.5% <100%）对大学生被试因果强度估计的影响。实验结果显示：1）实质取样增加在Power-PC=.50和1协变关系上都导致高估计,在Power-PC=0的协变关系上导致低估计;2）相同实质取样增量对被试在Power-PC=.50（1）协变关系上强度估计的影响符合一次（二次）函数假设。结果说明高实质取样促使被试做出符合理性预期的强度估计,混合假设可以解释被试的强度估计偏离Power-PC值的现象。     

The effect of representations of binary variables on judgment of influence

Studies concerned with judgments of contingency between binary variables have often ignored what the variables stand for. The two values of a binary variable can be represented as a prevailing state (nonevent) or as an active state (event). Judgments under the four conditions resulting from the combination of a binary input variable that can be represented as event-nonevent or event-event with an outcome variable that can be represented in the same way were obtained. It is shown in Experiment 1, that judgments of data sets which exhibit the same degree of covariation depend upon how the input and output variables are represented. In Experiment 2 the case where both the input and output variables are represented as event-nonevent is examined. Judgments were higher when the pairing of the input event was with the output event and the input nonevent with the output nonevent that when the pairing was of event with nonevent, suggesting a causal compatibility of event-event pairings and a causal incompatibility of event-nonevent pairings. Experiment 3 demonstrates that judgments of the strength of the relation between binary input and output variables is not based on the appropriate statistical measure, the difference between two conditional probabilities. The overall pattern of judgments in the three experiments is mainly explicable on the basis of two principles: (1) judgments tend to be based on the difference between confirming and disconfirming cases and (2) causal compatibility in the representation of the input and output variables plays a critical role.     

Causal judgment from contingency information: Relation between subjective reports and individual tendencies in judgment

In two experiments, participants made causal judgments from contingency information for problems with different objective contingencies. After the judgment task, the participants reported how their judgments had changed following each type of contingency information. Some reported idiosyncratic tendencies--in other words, tendencies contrary to those expected under associative-learning and normative rule induction models of contingency judgment. These idiosyncratic reports tended to be better predictors of the judgments of those who made them than did the models. The results are consistent with the view that causal judgment from contingency information is made, at least in part, by deliberative use of acquired and sometimes idiosyncratic notions of evidential value, the outcomes of which tend, in aggregate, to be highly correlated with the outcomes of normative procedures.     

Category learning in the color-word contingency learning paradigm

In the typical color-word contingency learning paradigm, participants respond to the print color of words where each word is presented most often in one color. Learning is indicated by faster and more accurate responses when a word is presented in its usual color, relative to another color. To eliminate the possibility that this effect is driven exclusively by the familiarity of item-specific word-color pairings, we examine whether contingency learning effects can be observed also when colors are related to categories of words rather than to individual words. To this end, the reported experiments used three categories of words (animals, verbs, and professions) that were each predictive of one color. Importantly, each individual word was presented only once, thus eliminating individual color-word contingencies. Nevertheless, for the first time, a category-based contingency effect was observed, with faster and more accurate responses when a category item was presented in the color in which most of the other items of that category were presented. This finding helps to constrain episodic learning models and sets the stage for new research on category-based contingency learning.     

Causal imprinting in causal structure learning

Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures "causal imprinting." Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C.     

Inattentional blindness for negative relationships in human causal learning

The present study focuses on the effect of selective attention on causal learning. Three effects of the level of attention to predictive symptoms in positive and negative contingency learning tasks are reported. First, participants accurately detected a positive relationship between an incidental cue and a contingent outcome, although judgements were slightly lower than those for the attended cue. Second, participants were unable to detect negative relationships between incidental cues and outcomes, which suggests a major role of selective attention in this type of learning. Third, participants retrieved the frequency of each trial type more accurately in the attended conditions than in the incidental conditions. These findings show how attention guides and constrains human causal learning and reveal an inattentional blindness effect for negative contingency learning.     

Inattentional blindness for negative relationships in human causal learning

The present study focuses on the effect of selective attention on causal learning. Three effects of the level of attention to predictive symptoms in positive and negative contingency learning tasks are reported. First, participants accurately detected a positive relationship between an incidental cue and a contingent outcome, although judgements were slightly lower than those for the attended cue. Second, participants were unable to detect negative relationships between incidental cues and outcomes, which suggests a major role of selective attention in this type of learning. Third, participants retrieved the frequency of each trial type more accurately in the attended conditions than in the incidental conditions. These findings show how attention guides and constrains human causal learning and reveal an inattentional blindness effect for negative contingency learning.     

暴力游戏对青少年攻击性认知影响的文化差异：基于元分析视角

对国内外现有的暴力游戏影响青少年攻击性认知的实验研究进行元分析。总共纳入24篇研究, 产生28个独立样本, 涉及被试2449人。结果表明, 暴力游戏助长青少年攻击性认知的总效应接近中等程度; 暴力游戏对青少年攻击性认知的效应受文化类型和被试群体类型的调节, 但不受测验方法的影响, 西方文化的效应值显著大于东方文化的效应值; 其对小学生、大学生、中学生攻击性认知的影响效力依次递减, 各测验方法之间的效应值差异并不显著。     

Causal status as a determinant of feature centrality

One of the major problems in categorization research is the lack of systematic ways of constraining feature weights. We propose one method of operationalizing feature centrality, a causal status hypothesis which states that a cause feature is judged to be more central than its effect feature in categorization. In Experiment 1, participants learned a novel category with three characteristic features that were causally related into a single causal chain and judged the likelihood that new objects belong to the category. Likelihood ratings for items missing the most fundamental cause were lower than those for items missing the intermediate cause, which in turn were lower than those for items missing the terminal effect. The causal status effect was also obtained in goodness-of-exemplar judgments (Experiment 2) and in free-sorting tasks (Experiment 3), but it was weaker in similarity judgments than in categorization judgments (Experiment 4). Experiment 5 shows that the size of the causal status effect is moderated by plausibility of causal relations, and Experiment 6 shows that effect features can be useful in retrieving information about unknown causes. We discuss the scope of the causal status effect and its implications for categorization research.     

A comparison of group contingencies on academic compliance

We used a reversal design with an embedded multielement design to compare the effects of an independent group contingency and a randomized dependent group contingency on compliance with assigned literacy worksheets in a first‐grade general education classroom. Nine participants were selected based on low levels of compliance in baseline or by teacher identification. Results indicated that both group contingencies increased compliance relative to baseline for the majority of participants. The independent condition produced higher levels of compliance for four students and the randomized dependent condition produced higher levels of compliance for one student. For four students, the two group contingencies were equally effective. A preference assessment indicated that the majority of target students preferred the randomized dependent condition and the majority of nontarget students preferred the independent condition. A number of potential explanations for our preference findings, including the possible role of obtained reinforcement, are discussed.