The effects of assessment type on verbal ratings of conditional stimulus valence and contingency judgments: Implications for the extinction of evaluative learning.

Recent research on causal learning found (a) that causal judgments reflect either the current predictive value of a conditional stimulus (CS) or an integration across the experimental contingencies used in the entire experiment and (b) that postexperimental judgments, rather than the CS's current predictive value, are likely to reflect this integration. In the current study, the authors examined whether verbal valence ratings were subject to similar integration. Assessments of stimulus valence and contingencies responded similarly to variations of reporting requirements, contingency reversal, and extinction, reflecting either current or integrated values. However, affective learning required more trials to reflect a contingency change than did contingency judgments. The integration of valence assessments across training and the fact that affective learning is slow to reflect contingency changes can provide an alternative interpretation for researchers' previous failures to find an effect of extinction training on verbal reports of CS valence. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Asymmetries in predictive and diagnostic reasoning.

In this article, we address the apparent discrepancy between causal Bayes net theories of cognition, which posit that judgments of uncertainty are generated from causal beliefs in a way that respects the norms of probability, and evidence that probability judgments based on causal beliefs are systematically in error. One purported source of bias is the ease of reasoning forward from cause to effect (predictive reasoning) versus backward from effect to cause (diagnostic reasoning). Using causal Bayes nets, we developed a normative formulation of how predictive and diagnostic probability judgments should vary with the strength of alternative causes, causal power, and prior probability. This model was tested through two experiments that elicited predictive and diagnostic judgments as well as judgments of the causal parameters for a variety of scenarios that were designed to differ in strength of alternatives. Model predictions fit the diagnostic judgments closely, but predictive judgments displayed systematic neglect of alternative causes, yielding a relatively poor fit. Three additional experiments provided more evidence of the neglect of alternative causes in predictive reasoning and ruled out pragmatic explanations. We conclude that people use causal structure to generate probability judgments in a sophisticated but not entirely veridical way. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Making causal judgments from the proportion of confirming instances: The pCI rule.

It is proposed that causal judgments about contingency information are derived from the proportion of confirmatory instances (pCI) that are evaluated as confirmatory for the causal candidate. In 6 experiments, pCI values were manipulated independently of objective contingencies assessed by the ΔP rule. Significant effects of the pCI manipulations were found in all cases, but causal judgments did not vary significantly with objective contingencies when pCI was held constant. The experiments used a variety of stimulus presentation procedures and different dependent measures. The power PC theory, a weighted version of the ΔP rule, the Rescorla-Wagner associative learning model (R. A. Rescorla & A. R. Wagner, 1972), and the ΔD rule, which is the frequency-based version of the pCI rule, were unable to account for the significant effects of the pCI manipulations. These results are consistent with a general explanatory approach to causal judgment involving the evaluation of evidence and updating of beliefs with regard to causal hypotheses. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Expectations and interpretations during causal learning.

In existing models of causal induction, 4 types of covariation information (i.e., presence/absence of an event followed by presence/absence of another event) always exert identical influences on causal strength judgments (e.g., joint presence of events always suggests a generative causal relationship). In contrast, we suggest that, due to expectations developed during causal learning, learners give varied interpretations to covariation information as it is encountered and that these interpretations influence the resulting causal beliefs. In Experiments 1A–1C, participants' interpretations of observations during a causal learning task were dynamic, expectation based, and, furthermore, strongly tied to subsequent causal judgments. Experiment 2 demonstrated that adding trials of joint absence or joint presence of events, whose roles have been traditionally interpreted as increasing causal strengths, could result in decreased overall causal judgments and that adding trials where one event occurs in the absence of another, whose roles have been traditionally interpreted as decreasing causal strengths, could result in increased overall causal judgments. We discuss implications for traditional models of causal learning and how a more top-down approach (e.g., Bayesian) would be more compatible with the current findings. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Retrospective revaluation of causal judgments under positive and negative contingencies.

Retrospective revaluation of causal judgments was investigated in a 2-stage procedure. In the 1st stage, compounds of 2 cues were associated with the outcome, whereas in the 2nd stage, a cue from each compound was trained by itself. Associating this cue with the outcome in the 2nd stage had no detectable effect on the causal rating of the other cue from the compound, whereas presenting it without the outcome enhanced the causal rating of the other cue. The retrospective revaluation of the causal rating of these productive cues and also of preventative cues depended on consistent pairing of the cues during compound training, suggesting a role for within-compound associations. These results favor associative accounts of retrospective revaluation that use separate excitatory and inhibitory learning processes rather than a general error-correcting learning algorithm. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Schedules of reinforcement as determinants of human causality judgments and response rates.

Experiments examined the effect of relationships between a response and an outcome on human judgments of causal effectiveness. In Experiment 1, the time between outcomes obtained on a variable ratio (VR) schedule became the intervals for a yoked variable interval (VI) schedule. Response rates were higher on the VR than on the VI schedule. In Experiment 2, the number of responses required per outcome on a VR schedule were matched to that on a master VI 20-s schedule. Both ratings of causal effectiveness and response rates were higher in the VR schedule. In Experiment 3, tandem VI fixed-ratio (FR) schedules produced higher rates and judgments than equivalent conjunctive VI FR schedule. In Experiment 4, a VI schedule with a reinforcement requirement for a short interresponse time (IRT) produced higher rates and judgments than a simple VI schedule. These results corroborate the view that schedules are a determinant of both response rates and causal judgments. Few current theories of causal judgment predict this pattern of results. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

From Covariation to Causation: A Test of the Assumption of Causal Power.

How humans infer causation from covariation has been the subject of a vigorous debate, most recently between the computational causal power account (P. W. Cheng, 1997) and associative learning theorists (e.g., K. Lober & D. R. Shanks, 2000). Whereas most researchers in the subject area agree that causal power as computed by the power PC theory offers a normative account of the inductive process. Lober and Shanks, among others, have questioned the empirical validity of the theory. This article offers a full report and additional analyses of the original study featured in Lober and Shanks's critique (M. J. Buehner & P. W. Cheng, 1997) and reports tests of Lober and Shanks's and other explanations of the pattern of causal judgments. Deviations from normativity, including the outcome-density bias, were found to be misperceptions of the input or other artifacts of the experimental procedures rather than inherent to the process of causal induction. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Temporal predictability facilitates causal learning.

[Correction Notice: An erratum for this article was reported in Vol 140(3) of Journal of Experimental Psychology: General (see record 2011-16270-001). Figure 2 (p. 759) contained an error. The corrected figure appears in the correction.] Temporal predictability refers to the regularity or consistency of the time interval separating events. When encountering repeated instances of causes and effects, we also experience multiple cause–effect temporal intervals. Where this interval is constant it becomes possible to predict when the effect will follow from the cause. In contrast, interval variability entails unpredictability. Three experiments investigated the extent to which temporal predictability contributes to the inductive processes of human causal learning. The authors demonstrated that (a) causal relations with fixed temporal intervals are consistently judged as stronger than those with variable temporal intervals, (b) that causal judgments decline as a function of temporal uncertainty, and (c) that this effect remains undiminished with increased learning time. The results therefore clearly indicate that temporal predictability facilitates causal discovery. The authors considered the implications of their findings for various theoretical perspectives, including associative learning theory, the attribution shift hypothesis, and causal structure models. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Do different metamemory judgments tap the same underlying aspects of memory?

We compared the predictions from several kinds of metamemory judgments (on the same set of items), both in terms of their predictive accuracy and in terms of the commonality of predictions. Undergraduates made judgments about the ease with which they could learn each item in a list (ease-of-learning judgments); then they learned every item, either to a minimal criterion of learning or with overlearning, and made judgments about how well they knew each item (judgments of knowing); finally, they returned 4 weeks later for a retention session and made feeling-of-knowing judgments on every time they could not recall, after which a recognition test assessed predictive accuracy. Ease-of-learning judgments had the least predictive accuracy. Surprisingly, however, the recognition of nonrecalled items was predicted equally well by judgments of knowing (made 4 weeks earlier) as by feeling-of-knowing judgments (made immediately prior to recognition). Moreover, those two kinds of judgments were only weakly correlated with each other, which implies that they do not tap memory in the same way. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Correction to Greville and Buehner (2010).

Reports an error in "Temporal predictability facilitates causal learning" by W. James Greville and Marc J. Buehner (Journal of Experimental Psychology: General, 2010[Nov], Vol 139[4], 756-771). Figure 2 (p. 759) contained an error. The corrected figure appears in the correction. (The following abstract of the original article appeared in record 2010-22538-005.) Temporal predictability refers to the regularity or consistency of the time interval separating events. When encountering repeated instances of causes and effects, we also experience multiple cause–effect temporal intervals. Where this interval is constant it becomes possible to predict when the effect will follow from the cause. In contrast, interval variability entails unpredictability. Three experiments investigated the extent to which temporal predictability contributes to the inductive processes of human causal learning. The authors demonstrated that (a) causal relations with fixed temporal intervals are consistently judged as stronger than those with variable temporal intervals, (b) that causal judgments decline as a function of temporal uncertainty, and (c) that this effect remains undiminished with increased learning time. The results therefore clearly indicate that temporal predictability facilitates causal discovery. The authors considered the implications of their findings for various theoretical perspectives, including associative learning theory, the attribution shift hypothesis, and causal structure models. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Does aging influence people's metacomprehension? Effects of processing ease on judgments of text learning.

In 2 experiments, the authors investigated whether age-related differences exist in metacomprehension by evaluating predictions based on the ease-of-processing (EOP) hypothesis. According to this hypothesis, judgments of how well a text has been learned are based on how easily each text was processed; easier processing results in higher judgments. Participants read either sentence pairs or longer texts and judged their learning of each immediately afterward. Although an age-related difference in the use of processing ease in judgments was observed with sentence pairs, for longer texts older and younger adults' judgments were similarly related to processing ease. In both experiments, age equivalence was also evident in the accuracy of the judgments at predicting performance on the criterion test. The overall pattern of results suggests that judging text learning remains largely intact with aging. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Outcome Specificity of Learned Predictiveness Effects: Parallels Between Human Causal Learning and Animal Conditioning.

Two experiments examined the outcome specificity of a learned predictiveness effect in human causal learning. Experiment 1 indicated that prior experience of a cue-outcome relation modulates learning about that cue with respect to a different outcome from the same affective class but not with respect to an outcome from a different affective class. Experiment 2 ruled out an interpretation of this effect in terms of context specificity. These results indicate that learned predictiveness effects in human causal learning index an associability that is specific to a particular class of outcomes. Moreover, they mirror demonstrations of the reinforcer specificity of analogous effects in animal conditioning, supporting the suggestion that, under some circumstances, human causal learning and animal conditioning reflect the operation of common associative mechanisms. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Metacognition of emotional face recognition.

While humans are adept at recognizing emotional states conveyed by facial expressions, the current literature suggests that they lack accurate metacognitions about their performance in this domain. This finding comes from global trait-based questionnaires that assess the extent to which an individual perceives him or herself as empathic, as compared to other people. Those who rate themselves as empathically accurate are no better than others at recognizing emotions. Metacognition of emotion recognition can also be assessed using relative measures that evaluate how well a person thinks s/he has understood the emotion in a particular facial display as compared to other displays. While this is the most common method of metacognitive assessment of people's judgments of learning or their feelings of knowing, this kind of metacognition—“relative meta-accuracy”—has not been studied within the domain of emotion. As well as asking for global metacognitive judgments, we asked people to provide relative, trial-by-trial prospective and retrospective judgments concerning whether they would be right or wrong in recognizing the expressions conveyed in particular facial displays. Our question was: Do people know when they will be correct in knowing what expression is conveyed, and do they know when they do not know? Although we, like others, found that global meta-accuracy was unpredictive of performance, relative meta-accuracy, given by the correlation between participants' trial-by-trial metacognitive judgments and performance on each item, were highly accurate both on the Mind in the Eyes task (Experiment 1) and on the Ekman Emotional Expression Multimorph task (in Experiment 2). (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Aging and the Detection of Contingency in Causal Learning.

Young and older participants' ability to detect negative, random, and positive response-outcome contingencies was evaluated using both contingency estimation and response rate adaptation tasks. Age differences in contingency estimation were consistently greater for negative than positive contingencies, and these differences, though still present, were smaller when response rate adaptation was used as the measure of contingency learning. Detecting causal contingency apparently becomes more difficult with age, especially when an oven numerical estimate of contingency must be provided and when the relationship between a causal event and an outcome is negative. A model that incorporates features of both associative and rule-based approaches to contingency learning (e.g., P. C. Price & J. F. Yates, 1995; D. R. Shanks, 1995) provides the best explanation for this pattern of findings. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Causal beliefs and conditioned responses: Retrospective revaluation induced by experience and by instruction.

The author tested causal beliefs and conditioned responses in a task involving retrospective revaluation of the causal status of a target cue with respect to electric shock. Successful revaluation was observed on both self-report shock expectancy and skin conductance, whether the training trials were directly experienced, described, or partly experienced and partly described. The results contradict models that link anticipatory conditioned responses to a separate or earlier process from that underlying explicit causal knowledge. They suggest instead that a single learning process gives rise to propositional knowledge that (a) drives anticipatory responding, (b) forms the basis for self-reported causal beliefs, and (c) can be combined with other knowledge, provided either by experience or symbolically, to generate inferences such as retrospective revaluation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Causal learning mechanisms in very young children: Two-, three-, and four-year-olds infer causal relations from patterns of variation and covariation.

Three studies investigated whether young children make accurate causal inferences on the basis of patterns of variation and covariation. Children were presented with a new causal relation by means of a machine called the "blicket detector." Some objects, but not others, made the machine light up and play music. In the first 2 experiments, children were told that "blickets make the machine go" and were then asked to identify which objects were "blickets." Two-, 3-, and 4-year-old children were shown various patterns of variation and covariation between two different objects and the activation of the machine. All 3 age groups took this information into account in their causal judgments about which objects were blickets. In a 3rd experiment, 3- and 4-year-old children used the information when they were asked to make the machine stop. These results are related to Bayes-net causal graphical models of causal learning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Encoding fluency is a cue used for judgments about learning.

The authors used paired-associate learning to investigate the hypothesis that the speed of generating an interactive image (encoding fluency) influenced 2 metacognitive judgments: judgments of learning (JOLs) and quality of encoding ratings (QUEs). Results from Experiments 1 and 2 indicated that latency of a keypress indicating successful image formation was negatively related to both JOLs and QUEs even though latency was unrelated to recall. Experiment 3 demonstrated that when concrete and abstract items were mixed in a single list, latency was related to concreteness, judgments, and recall. However, item concreteness and fluency influenced judgments independently of one another. These outcomes suggest an important role of encoding fluency in the formation of metacognitive judgments about learning and future recall. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Rating causal relations: Role of probability in judgments of response-outcome contingency.

Investigated the possible role of the conditional probabilities of an outcome given a response P(O/R) and of an outcome given the absence of a response P(O/NoR) in mediating college students' judgments of response–outcome contingency. A total of 150 Ss in 3 experiments were asked to describe the effect that telegraph key tapping had on the brief illumination of a lamp. Ss' ratings along a prevent–cause scale closely approximated the scheduled contingencies between response (R?=?key tapping) and outcome (O?=?lamp illumination), as measured by the delta coefficient δP?=?P(O/R)?–?P(O/NoR) (Exps 1 and 3). Ss also sensitively rated the conditional probabilities of an outcome when they tapped the key and when they refrained from doing so (Exps 2 and 3). Nevertheless, the evidence failed to support the hypothesis that causal ratings were mediated by subjective judgments of P(O/R) and P(O/NoR) because the errors made in judging the conditional probabilities were not consistent with the errors made judging δP. The authors suggest that an associative explanation derived from a model devised by R. A. Rescorla and A. R. Wagner (1972) might account for these and other results. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Blocking and Unblocking in Human Causal Learning.

Three experiments sought to develop the suggestion that, under some circumstances, common associative learning mechanisms might underlie animal conditioning and human causal learning, by demonstrating, in humans, an effect analogous to the unblocking by reinforcer omission observed in animal conditioning. Experiment 1 found no such effect. Experiment 2, designed to prevent inhibitory influences that might have masked excitatory unblocking in Experiment 1, demonstrated unblocking, indicating common human-animal associative learning mechanisms in which the associability of a stimulus varies as a function of its predictive history. Experiment 3, using a similar design but with a procedure promoting application of rational inference processes, failed to detect the same unblocking effect, indicating that associative and cognitive mechanisms may influence human causal learning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Selective attention in human associative learning and recognition memory.

Four experiments examined the role of selective attention in a new causal judgment task that allowed measurement of both causal strength and cue recognition. In Experiments 1 and 2, blocking was observed; pretraining with 1 cue (A) resulted in reduced learning about a 2nd cue (B) when those 2 cues were trained in compound (AB+). Participants also demonstrated decreased recognition performance for the causally redundant Cue B, suggesting that less attention had been paid to it in training. This is consistent with the idea that attention is preferentially allocated toward the more predictive Cue A, and away from the less predictive Cue B (e.g., N. J. Mackintosh, 1975). Contrary to this hypothesis, in Experiments 3 and 4, participants demonstrated poorer recognition for the most predictive cues, relative to control cues. A new model, which is based on N. J. Mackintosh's (1975) model, is proposed to account for the observed relationship between the extent to which each cue is attended to, learned about, and later recognized. (PsycINFO Database Record (c) 2010 APA, all rights reserved)