Effective elaboration and inferential reasoning

The present study investigated the effects of several variables on subjects’ abilities to draw inferences from two related premises. Contiguous presentation of the related sentences led to significantly higher inference scores than did noncontiguous presentation. The nature of the initial premise was also manipulated. For some subjects, the initial premise was relatively consistent with subjects’ semantic knowledge, whereas other subjects received initial premises that were somewhat arbitrary with respect to semantic knowledge. Inference scores were significantly higher for subjects who received the more consistent initial premises. This effect persists even when differential memory for the initial premises has been accounted for. The results suggest certain constraints on the nature of the knowledge one must possess in order to make appropriate inferences from material.     

Test-Anxiety,inferential reasoning and working memory load

Abstract

Subjects high and low in test-anxiety were presented with an inferential reasoning task requiring the verification of necessary and unnecessary inferences. The task was performed whilst holding either two or six digits in memory. On the verification task, the performance of high-test-anxious subjects was slower and less accurate than that of the low-test-anxious subjects. In addition, unnecessary inferences took longer to process than necessary inferences for the high-test-anxiety group only. The high-test-anxious subjects studied the memory loads for longer than the low-test-anxious group, but their recognition accuracy did not differ. Findings support Eysenck and Calvo's (Cognition and Emotion, 6, 409–434, 1992) processing efficiency theory. The high-test-anxious group's performance on the sentence verification task was impaired overall, and was particularly impaired when performing the unnecessary inference task. However, we also demonstrated that the high-test-anxious group's performance on a secondary memory task was unimpaired as a result of increased effort.     

Comparing elemental and configural associative theories in human causal learning: a case for attention

In two causal learning experiments with human participants, the authors compared various associative theories that assumed either elemental (unique cue, modified unique cue, replaced elements model, and Harris' model) or configural processing of stimuli (Pearce's theory and a modification of it). The authors used modified patterning problems initially suggested by Redhead and Pearce (1995). Predictions for all theories were generated by computer simulations. Both configural theories and the unique cue approach failed to account for the observations. The replaced elements model was able to account for part of the data, but only if the replacement parameters could vary across discrimination problems. The Harris model and the modified unique cue approach, assuming that the salience of stimuli decreases with an increasing number of stimuli in a compound, successfully accounted for all of our data. This success implies that attentional factors should be explicitly taken into account in associative learning theory.     

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.     

Generalization decrement in human contingency learning

An association between a cue and an outcome will generalize to a similar novel cue to some extent, but not completely. Learning theorists refer to the discrepancy between responding elicited by the original cue and the novel cue as a generalization decrement. Two experiments used a contingency learning task with human participants to compare the size of a generalization decrement between configurations of cues that were altered by adding or subtracting compositional elements. The results suggest that adding elements to a configuration can produce a generalization decrement, but removing elements produces a more robust generalization decrement. Furthermore, the generalization decrement caused by adding elements was not likely to be caused by competing orienting responses. The results are used to contrast Pearce's (1987, 1994) and Wagner's (2003) models of stimulus generalization.     

Generalization decrement in human contingency learning

An association between a cue and an outcome will generalize to a similar novel cue to some extent, but not completely. Learning theorists refer to the discrepancy between responding elicited by the original cue and the novel cue as a generalization decrement. Two experiments used a contingency learning task with human participants to compare the size of a generalization decrement between configurations of cues that were altered by adding or subtracting compositional elements. The results suggest that adding elements to a configuration can produce a generalization decrement, but removing elements produces a more robust generalization decrement. Furthermore, the generalization decrement caused by adding elements was not likely to be caused by competing orienting responses. The results are used to contrast Pearce's (1987, 1994) and Wagner's (2003) models of stimulus generalization.     

Negative transfer in human associative learning

Models of attentional allocation in associative learning are typically structured according to one of two guiding principles: the predictiveness principle, which posits that attention is paid to cues that have reliably predicted an outcome in the past, or the uncertainty principle, which states that attention is paid to cues about which little is known. Both principles are well supported by studies of animals. However, in studies of human learning, there is very little direct empirical support for the uncertainty principle. In the study reported here, we addressed this gap by investigating negative transfer, a phenomenon that may provide unique support for the uncertainty principle. In two human learning experiments using an allergist task, we replicated the primary findings of previous research on animal learning. We believe that these data provide the first direct evidence for the uncertainty principle in human associative learning.     

Overt attention and predictiveness in human contingency learning

Two experiments used eye-tracking procedures to investigate the relationship between attention and associative learning in human participants. These experiments found greater overt attention to cues experienced as predictive of the outcomes with which they were paired, than to cues experienced as nonpredictive. Moreover, this attentional bias persisted into a second training phase when all cues were equally predictive of the outcomes with which they were paired, and it was accompanied by a related bias in the rate of learning about these cues. These findings are consistent with the attentional model of associative learning proposed by Mackintosh (1975), but not with that proposed by Pearce and Hall (1980).     

Interfering with inferential, but not associative, processes underlying spontaneous trait inference

Three studies explore mental processes underlying spontaneous trait inferences about self-informants and the spontaneous trait transference characterizing third-party informants. Process differences are suggested in that instructions prompting a nontrait inference (truth or lie?) reduce self-informant trait-savings effects and lower self-informant trait judgments. For third-party informants, such instructions have no effect on these outcome variables. Results of a third study are inconsistent with cognitive load as an explanation for these effects. Taken together, these results indicate that inferences, and not merely associations, spontaneously form when processing information about self-informants. The results also show that the inferences and judgments that occur in spontaneous trait transference are not caused by the misidentification of third-party informants as self-informants.     

Effects of anxiety on inferential reasoning task performance

Three experiments were conducted in which high anxiety and low anxiety subjects were required to construct inferences. In Experiment 1 there was no anxiety-related performance deficit when inferring a necessary anaphoric relation, a process argued to be automatic. Experiments 2 and 3 involved the verification of unnecessary inferences, a process argued to involve the utilization of the working memory system. In both Experiments 2 and 3 there was an anxiety-related performance deficit. The results are consistent with a working memory-oriented account of anxiety-related performance effects, as deficits were restricted to capacity-demanding tasks.     

Stimulus exposure effects in human associative learning

Learning that one cue (CS) predicts a second, salient cue (US) can often be slowed by prior exposure to one or both stimuli. In animals, CS-US learning is more strongly retarded following uncorrelated exposure to both CS and US than following exposure to the US alone. In this paper we present several studies showing a similar effect in humans, using a computer-based task. Experiments 1 and 2 used a between-groups design and demonstrated a strong CS/US exposure effect, whether or not the US was signalled by a neutral cue during exposure. Experiment 3 demonstrated similar effects using a within-subjects design. Overall, these results are consistent with several theoretical interpretations and suggest that uncorrelated CS/US exposure leads to a robust retardation of subsequent CS-US learning in humans.     

Associationism and cognition: human contingency learning at 25

A major topic within human learning, the field of contingency judgement, began to emerge about 25 years ago following publication of an article on depressive realism by Alloy and Abramson (1979). Subsequently, associationism has been the dominant theoretical framework for understanding contingency learning but this has been challenged in recent years by an alternative cognitive or inferential approach. This article outlines the key conceptual differences between these approaches and summarizes some of the main methods that have been employed to distinguish between them.     

Computer-managed inferential statistical analysis of EEG data

Much of the neuroelectrical/psychophysiologic research of the past has involved the use of “group-type” statistics. Often, this has resulted in large variances that make it difficult, if not impossible, to find significant differences. Using the INNOVATE technique of single-subject design, we are able to consistently demonstrate significant differences in EEG spectra related to experimental and clinical effects previously masked.     

Inferences about unobserved causes in human contingency learning

Estimates of the causal efficacy of an event need to take into account the possible presence and influence of other unobserved causes that might have contributed to the occurrence of the effect. Current theoretical approaches deal differently with this problem. Associative theories assume that at least one unobserved cause is always present. In contrast, causal Bayes net theories (including Power PC theory) hypothesize that unobserved causes may be present or absent. These theories generally assume independence of different causes of the same event, which greatly simplifies modelling learning and inference. In two experiments participants were requested to learn about the causal relation between a single cause and an effect by observing their co-occurrence (Experiment 1) or by actively intervening in the cause (Experiment 2). Participants' assumptions about the presence of an unobserved cause were assessed either after each learning trial or at the end of the learning phase. The results show an interesting dissociation. Whereas there was a tendency to assume interdependence of the causes in the online judgements during learning, the final judgements tended to be more in the direction of an independence assumption. Possible explanations and implications of these findings are discussed.     

The role of similarity in human associative learning

In 2 experiments, humans received sequences of patterns that were similar (AX-->BX, AY-->BY, AZ-->BZ) or dissimilar (CX-->DY, CY-->DZ, CZ-->DX). The patterns were portrayed as bugs that could be eliminated with 2 insecticide sprays (red or blue). Either spray eliminated bugs with Features A and C, and participants learned by trial and error to use one spray (e.g., red) to eliminate bugs with Feature B and the other spray (e.g., blue) to eliminate those with Feature D. In Experiment 1, participants' spray choice for bugs with Feature A came to match that used to eliminate bugs with Feature B, but there was no such associative transfer between Features C and D. That is, similarity promoted associative transfer of responding between paired patterns when the features used to manipulate similarity (i.e., X, Y, and Z) were irrelevant. In Experiment 2, in which X, Y, and Z were relevant to the solution of configural discrimination, similarity hindered such associative transfer. These results complement those found in pigeons (R. A. Rescorla & D. J. Gillan, 1980) and indicate that similarity should not be accorded independent status as a principle of associative learning.     

Different developmental patterns of simple deductive and probabilistic inferential reasoning

In three studies, we examined simple counterexample-based and probabilistic reasoning in children 6, 7, and 9 years of age. In the first study, participants were asked to make conditional (if-then) inferences under both categorical (certain or uncertain) and probabilistic instructions. Results showed that 6-year-olds respond to both forms of inference in similar ways, but whereas probabilistic conditional inferences showed little development over this period, categorical inferences clearly improved between 6 and 7 years of age. An analysis of the children's justifications indicated that performance under categorical instructions was strongly related to counterexample generation at all ages, whereas this was true only for the younger children for inferences under probabilistic instructions. These findings were replicated in a second study, using problems that referred to concrete stimuli with varying probabilities of inference. A third study tested the hypothesis that children confused probability judgments with judgments of confidence and demonstrated a clear dissociation between these two constructs. Overall, these results show that children are capable of accurate conditional inferences under probabilistic instructions at a very early age and that the differentiation between categorical and probabilistic conditional reasoning is clear by at least 9 years ofage. These results are globally consistent with dual-process theories but suggest some difficulties for the way that the analytic-heuristic distinction underlying these theories has been conceptualized.     

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     

Generalization gradients for acquisition and extinction in human contingency learning

Two experiments investigated the perceptual generalization of acquisition and extinction in human contingency learning. In Experiment 1, the degree of perceptual similarity between the acquisition stimulus and the generalization stimulus was manipulated over five groups. This successfully generated a generalization gradient of acquisition. In the subsequent phase, the response to the generalization stimulus was extinguished in each group. Finally, the acquisition stimulus was presented again. The response recovered differently over groups, thereby establishing the generalization gradient of extinction. In Experiment 2, the acquisition stimulus itself was extinguished before the set of generalization stimuli was tested between groups. One group evidenced a response recovery at test, which suggests that the gradient of acquisition is somewhat broader than the gradient of extinction.