The role of working memory capacity in multiple-cue probability learning

Multiple-cue probability learning (MCPL) involves learning to predict a criterion when outcome feedback is provided for multiple cues. A great deal of research suggests that working memory capacity (WMC) is involved in a wide range of tasks that draw on higher level cognitive processes. In three experiments, we examined the role of WMC in MCPL by introducing measures of working memory capacity, as well as other task manipulations. While individual differences in WMC positively predicted performance in some kinds of multiple-cue tasks, performance on other tasks was entirely unrelated to these differences. Performance on tasks that contained negative cues was correlated with working memory capacity, as well as measures of explicit knowledge obtained in the learning process. When the relevant cues predicted positively, however, WMC became irrelevant. The results are discussed in terms of controlled and automatic processes in learning and judgement.     

The effectiveness of feedback in multiple-cue probability learning

How effective are different types of feedback in helping us to learn multiple contingencies? This article attempts to resolve a paradox whereby, in comparison to simple outcome feedback, additional feedback either fails to enhance or is actually detrimental to performance in nonmetric multiple-cue probability learning (MCPL), while in contrast the majority of studies of metric MCPL reveal improvements at least with some forms of feedback. In three experiments we demonstrate that if feedback assists participants to infer cue polarity then it can in fact be effective in nonmetric MCPL. Participants appeared to use cue polarity information to adopt a linear judgement strategy, even though the environment was nonlinear. The results reconcile the paradoxical contrast between metric and nonmetric MCPL and support previous findings of people's tendency to assume linearity and additivity in probabilistic cue learning.     

An investigation of the role of some person and situation variables in multiple cue probability learning

Making decisions using judgements of multiple non-deterministic indicators is an important task, both in everyday and professional life. Learning of such decision making has often been studied as the mapping of stimuli (cues) to an environmental variable (criterion); however, little attention has been paid to the effects of situation-by-person interactions on this learning. Accordingly, we manipulated cue and feedback presentation mode (graphic or numeric) and task difficulty, and measured individual differences in working memory capacity (WMC). We predicted that graphic presentation, fewer cues, and elevated WMC would facilitate learning, and that person and task characteristics would interact such that presentation mode compatible with the decision maker's cognitive capability (enhanced visual or verbal WMC) would assist learning, particularly for more difficult tasks. We found our predicted main effects, but no significant interactions, except that those with greater WMC benefited to a larger extent with graphic than with numeric presentation, regardless of which type of working memory was enhanced or number of cues. Our findings suggest that the conclusions of past research based predominantly on tasks using numeric presentation need to be reevaluated and cast light on how working memory helps us learn multiple cue–criterion relationships, with implications for dual-process theories of cognition.     

Missing information in multiple-cue probability learning

In a multiple-cue probability learning task, participants learned to use six discrete symptoms (i.e., cues) to diagnose which of three possible flu strains a hypothetical patient suffered from. For some patients, information regarding the status of certain symptoms was not available. Various possible ways in which the missing cue information might be processed were distinguished and tested in a series of three experiments (Ns = 80, 109, and 61). The results suggest that the judged probability of the outcome variable (i.e., flu strain) was assessed by "filling in" the missing cue information with a mean value based on previous observations. The predictions of other methods of processing missing cue information are inconsistent with the data.     

An evidential support accumulation model of subjective probability

A model of cue-based probability judgment is developed within the framework of support theory. Cue diagnosticity is evaluated from experience as represented by error-free frequency counts. When presented with a pattern of cues, the diagnostic implications of each cue are assessed independently and then summed to arrive at an assessment of the support for a hypothesis, with greater weight placed on present than on absent cues. The model can also accommodate adjustment of support in light of the baserate or prior probability of a hypothesis. Support for alternatives packed together in a "residual" hypothesis is discounted; fewer cues are consulted in assessing support for alternatives as support for the focal hypothesis increases. Results of fitting this and several alternative models to data from four new multiple-cue probability learning experiments are reported.     

Choice strategies in multiple-cue probability learning

Choice strategies for selecting among outcomes in multiple-cue probability learning were investigated using a simulated medical diagnosis task. Expected choice probabilities (the proportion of times each outcome was selected given each cue pattern) under alternative choice strategies were constructed from corresponding observed judged probabilities (of each outcome given each cue pattern) and compared with observed choice probabilities. Most of the participants were inferred to have responded by using a deterministic strategy, in which the outcome with the higher judged probability is consistently chosen, rather than a probabilistic strategy, in which an outcome is chosen with a probability equal to its judged probability. Extended practice in the learning environment did not affect choice strategy selection, contrary to reports from previous studies, results of which may instead be attributable to changes with practice in the variability and extremity of the perceived probabilities on which the choices were based.     

The role of working memory capacity in multiple-cue probability learning

Multiple-cue probability learning (MCPL) involves learning to predict a criterion when outcome feedback is provided for multiple cues. A great deal of research suggests that working memory capacity (WMC) is involved in a wide range of tasks that draw on higher level cognitive processes. In three experiments, we examined the role of WMC in MCPL by introducing measures of working memory capacity, as well as other task manipulations. While individual differences in WMC positively predicted performance in some kinds of multiple-cue tasks, performance on other tasks was entirely unrelated to these differences. Performance on tasks that contained negative cues was correlated with working memory capacity, as well as measures of explicit knowledge obtained in the learning process. When the relevant cues predicted positively, however, WMC became irrelevant. The results are discussed in terms of controlled and automatic processes in learning and judgement.     

Note on subjects' hypotheses in multiple-cue probability learning

Subjects' hypotheses in multiple-cue probability learning was studied by trial-by-trial verbal reports in tasks with linear and nonlinear cue-criterion relations. In accordance with earlier findings, the results of the present experiment show that subjects learned linear tasks rapidly, while nonlinear tasks were not learned at all. The subjects' verbal hypotheses show that the subjects were concerned with rules for combining cue values, rather than with cue-criterion functions. This explains why the subjects fail to learn nonlinear multiple-cue tasks. It also shows that, although the subjects seem to learn multiple-cue tasks through a hypothesis testing process of the same kind as in single-cue probability tasks, the hypotheses tested in multiple-cue tasks are different from those tested in single-cue tasks. Finally, the present results suggest that the picture of the subjects' cognitive models of multiple-cue probability learning tasks provided by the customary multiple regression analysis may be fundamentally misleading in that it suggests that the subjects learn the validity of each cue rather than a combination rule.     

Note on detection of cue intercorrelation in multiple-cue probability learning

Abstract.— After completion of learning tasks with two different levels of cue intercorrelation (r _u=0.00 and 0.80) the detection of cue intercorrelation was tested with either a reproduction or a recognition method in a 2×2 factorial design. The reproduction method yielded an almost perfect matching between the reproduced intercorrelations and the intercorrelations of the tasks, while the recognition method resulted in systematically lower subjective intercorrelations. For the recognition method the subjective intercorrelation was found to vary with the criterion of recognition, so that the stricter the criterion, the higher the subjective intercorrelation.     

An hypothesis generation model for judgment in nonmetric multiple-cue probability learning

The purpose of this paper is to present a two-phase hypothesis generation model to describe behavior in multiple-cue probability learning tasks with nonmetric cues. The model assumes that on each trial the subject generates two sets of hypotheses: (a) a hypothesis concerning which cue dimension (or pattern) will lead to a correct prediction on that trial and (b) a hypothesis concerning which response will be correct given the cue dimension attended to on that trial.Five-hundred-twelve subjects were assigned to 20 groups in a binary choice task involving two binary cue dimensions. Each group observed cues which differed in validity. Analysis of the data indicated that subjects attend to both cue dimensions in making judgments even when one cue has zero validity. A test of the fit of the observed data to the asymptotic response proportions predicted by the model indicated a reasonable fit.     

When more is less: feedback effects in perceptual category learning

Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether their response was correct or incorrect, but are not informed of the correct category assignment. With full feedback subjects are informed of the correctness of their response and are also informed of the correct category assignment. An examination of the distinct neural circuits that subserve rule-based and information-integration category learning leads to the counterintuitive prediction that full feedback should facilitate rule-based learning but should also hinder information-integration learning. This prediction was supported in the experiment reported below. The implications of these results for theories of learning are discussed.     

Unconscious reward facilitates motion perceptual learning

Reward signal plays an important role in guiding human learning behaviour. Recent studies have provided evidence that reward signal modulates perceptual learning of basic visual features. Typically, the reward effects on perceptual learning were accompanied with consciously presented reward during the learning process. However, whether an unconsciously presented reward signal that minimizes the contribution of attentional and motivational factors can facilitate perceptual learning remains less well understood. We trained human subjects on a visual motion detection task and subliminally delivered a monetary reward for correct response during the training. The results showed significantly larger learning effect for high reward-associated motion direction than low reward-associated motion direction. Importantly, subjects could neither discriminate the relative values of the subliminal monetary reward nor correctly report the reward-direction contingencies. Our findings suggest that reward signal plays an important modulatory role in perceptual learning even if the magnitude of the reward was not consciously perceived.     

The impact of feedback frequency on learning and task performance: Challenging the “more is better” assumption

Previous research on feedback frequency suggests that more frequent feedback improves learning and task performance (Salmoni, Schmidt, & Walter, 1984). Drawing from resource allocation theory (Kanfer & Ackerman, 1989), we challenge the “more is better” assumption and propose that frequent feedback can overwhelm an individual’s cognitive resource capacity, thus reducing task effort and producing an inverted-U relationship with learning and performance over time. We then propose that positive and negative affective states will moderate the inverted-U relationship between feedback frequency and task performance. We test these propositions in an experimental study where the frequency of task feedback is manipulated. Results show that feedback frequency exhibits an inverted-U relationship with task performance, and this relationship is mediated by task effort. This curvilinear relationship is then moderated by individual’s positive affective state.     

Explicit feedback maintains implicit knowledge

The role of feedback was investigated with respect to conscious and unconscious knowledge acquired during artificial grammar learning (AGL). After incidental learning of training sequences, participants classified further sequences in terms of grammaticality and reported their decision strategy with or without explicit veridical feedback. Sequences that disobeyed the learning structure conformed to an alternative structure. Feedback led to an increase in the amount of reported conscious knowledge of structure (derived rules and recollections) but did not increase its accuracy. Conversely, feedback maintained the accuracy of unconscious knowledge of structure (intuition or familiarity-based responses) which otherwise degraded. Results support a dual-process account of AGL. They suggest that implicit learning of the to-be-rejected structure at test contaminates familiarity-based classifications whereas feedback allows competing familiarity signals to be contextualised, which is incompatible with theories that consider familiarity context-insensitive.     

Testing multiple motives in feedback seeking: The interaction of instrumentality and self protection motives

Research indicates that information received from feedback seeking is valuable for both individual and organizational outcomes. Previous research examining the feedback seeking process has consistently suggested that individual's feedback behaviors are directly influenced by three motives. Specifically, individuals are instrumentally motivated to obtain valued information but are also motivated to protect and/or enhance their ego and to protect others' impressions of them (Ashford, Blatt and VandeWalle, 2003). The current study simultaneously examined these motives by testing the interactive effects of them on feedback seeking behavior. As predicted, they did significantly interact and the results present a deeper understanding of these motives and how employees weigh various factors in deciding whether to seek feedback within the organization.     

Stereotype threat and feedback seeking in the workplace

This study examined stereotype threat (Steele & Aronson, 1995) in workplace settings and investigated relationships of stereotype threat to feedback seeking and feedback acceptance. Results from a sample of 166 African American managers showed that solo status in the work group predicted perceptions of stereotype threat. In addition, stereotype threat related positively to indirect feedback seeking and discounting of performance feedback from superiors. These findings have important implications for understanding the causes of group differences in job performance.     

How egocentrism and optimism change in response to feedback in repeated competitions

People tend to egocentrically focus on how adverse or beneficial conditions in competitions affect the self, while inadequately considering the comparable impact on opponents. This leads to overoptimism for a victory in easy tasks and underoptimism in hard tasks. Four experiments investigated whether experience and performance feedback in a multi-round competition would influence egocentric weighting and optimism biases across rounds. The results indicated that egocentric weighting and optimism biases decreased across rounds. However, this apparent debiasing occurred under restrictive conditions, and participants did not generalize their learned, non-egocentric tendencies to novel contexts. The roles of differential confidence and surface/structural similarity are discussed as reasons why optimism biases were generally pervasive.