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.     

“Meaningful” social inferences: Effects of implicit theories on inferential processes

Perceivers’ shared theories about the social world have long featured prominently in social inference research. Here, we investigate how fundamental differences in such theories influence basic inferential processes. Past work has typically shown that integrating multiple interpretations of behavior during social inference requires cognitive resources. However, three studies that measured or manipulated people’s beliefs about the stable versus dynamic nature of human attributes (i.e., their entity vs. incremental theory, respectively) qualify these past findings. Results revealed that, when interpreting others’ actions, perceivers’ theories selectively facilitate the consideration of interpretations that are especially theory-relevant. While experiencing cognitive load, entity theorists continued to incorporate information about stable dispositions (but not about dynamic social situations) in their social inferences, whereas incremental theorists continued to incorporate information about dynamic social situations (but not about stable traits). Implications of these results for how perceivers find meaning in behavior are discussed.     

Theoretical accounts of spatial learning: A neurobiological view (commentary on Pearce, 2009)

Theories of learning have historically taken, as their starting point, the assumption that learning processes have universal applicability. This position has been argued on grounds of parsimony, but has received two significant challenges: first, from the observation that some kinds of learning, such as spatial learning, seem to obey different rules from others, and second, that some kinds of learning take place in processing modules that are separate from each other. These challenges arose in the behavioural literature but have since received considerable support from neurobiological studies, particularly single neuron studies of spatial learning, confirming that there are indeed separable (albeit highly intercommunicating) processing modules in the brain, which may not always interact (within or between themselves) according to classic associative principles. On the basis of these neurobiological data, reviewed here, it is argued that rather than assuming universality of associative rules, it is more parsimonious to assume sets of locally operating rules, each specialized for a particular domain. By this view, although almost all learning is associative in one way or another, the behavioural-level characterization of the rules governing learning may vary depending on which neural modules are involved in a given behaviour. Neurobiological studies, in tandem with behavioural studies, can help reveal the nature of these modules and the local rules by which they interact.     

Methodological vs. strategic control in artificial grammar learning: A commentary on Norman, Price and Jones (2011)

Norman et al. (2011) reported that participants exposed in succession to two artificial grammars could be able to learn implicitly about them, and could apply their knowledge strategically to select which string corresponds to one of these two grammars. In this commentary, I identify an artifact that could account for the learning obtained not only in this study, but also in some previous studies using the same procedures. I claim that more methodological control is needed before jumping to conclusions on the kind of strategic control that could be achieved unconsciously.     

The influence of temporal regularities on the implicit learning of pitch structures

Implicit learning is the acquisition of complex information without the intention to learn. The aim of this study was to investigate the influence of temporal regularities on the implicit learning of an artificial pitch grammar. According to the dynamic attending theory (DAT) external regularities can entrain internal oscillators that guide attention over time, inducing temporal expectations that influence perception of future events. In the present study, the presentation of the artificial pitch grammar in the exposure phase was temporally either regular or irregular for one of two participant groups. Based on the DAT, it was hypothesized that the regular temporal presentation would favour implicit learning of tone structures in comparison to the irregular temporal presentation. Results demonstrated learning of the artificial grammar for the group with the regular exposure phase and partial learning for the group with the irregular exposure phase. These findings suggest that the regular presentation helps listeners to develop perceptual expectations about the temporal occurrence of future tones and thus facilitates the learning of the artificial pitch grammar.     

Attention and expectation in human predictive learning: The role of uncertainty

Three localized, visual pattern stimuli were trained as predictive signals of auditory outcomes. One signal partially predicted an aversive noise in Experiment 1 and a neutral tone in Experiment 2, whereas the other signals consistently predicted either the occurrence or absence of the noise. The expectation of the noise was measured during each signal presentation, and only participants for whom this expectation demonstrated contingency knowledge showed differential attention to the signals. Importantly, when attention was measured by visual fixations, the contingency-aware group attended more to the partially predictive signal than to the consistent predictors in both experiments. This profile of visual attention supports the Pearce and Hall (1980) Pearce, J. M. and Hall, G. 1980. A model for Pavlovian learning: Variations in the effectiveness of conditioned but not unconditioned stimuli. Psychological Review, 87: 532–552. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar] theory of the role of attention in associative learning.     

A note on DeCaro, Thomas, and Beilock (2008): Further data demonstrate complexities in the assessment of information-integration category learning

DeCaro et al. [DeCaro, M. S., Thomas, R. D., & Beilock, S. L. (2008). Individual differences in category learning: Sometimes less working memory capacity is better than more. Cognition, 107(1), 284-294] explored how individual differences in working memory capacity differentially mediate the learning of distinct category structures. Specifically, their results showed that greater working memory capacity facilitates the learning of novel category structures that are verbalisable and discoverable through logical reasoning processes. Conversely, however, greater working memory was shown to impede the learning of novel category structures thought to be non-verbalisable, inaccessible to conscious reasoning and discoverable only through implicit (procedural) learning of appropriate stimulus-category responses. The present paper calls into question the specific nature of the category learning tasks used, in particular their ability to discriminate between different modes of category learning.     

The nature of the memory buffer in implicit learning: Learning Chinese tonal symmetries

Previous research has established that people can implicitly learn chunks, which (in terms of formal language theory) do not require a memory buffer to process. The present study explores the implicit learning of nonlocal dependencies generated by higher than finite-state grammars, specifically, Chinese tonal retrogrades (i.e. centre embeddings generated from a context-free grammar) and inversions (i.e. cross-serial dependencies generated from a mildly context-sensitive grammar), which do require buffers (for example, last in-first out and first in-first out, respectively). People were asked to listen to and memorize artificial poetry instantiating one of the two grammars; after this training phase, people were informed of the existence of rules and asked to classify new poems, while providing attributions of the basis of their judgments. People acquired unconscious structural knowledge of both tonal retrogrades and inversions. Moreover, inversions were implicitly learnt more easily than retrogrades constraining the nature of the memory buffer in computational models of implicit learning.     

The emergence of words: attentional learning in form and meaning

Children improve at word learning during the 2nd year of life—sometimes dramatically. This fact has suggested a change in mechanism, from associative learning to a more referential form of learning. This article presents an associative exemplar-based model that accounts for the improvement without a change in mechanism. It provides a unified account of children's growing abilities to (a) learn a new word given only 1 or a few training trials ("fast mapping"); (b) acquire words that differ only slightly in phonological form; (c) generalize word meanings preferentially along particular dimensions, such as object shape (the "shape bias"); and (d) learn 2nd labels for already-named objects, despite a persisting resistance to doing so ("mutual exclusivity"). The model explains these improvements in terms of increased attention to relevant aspects of form and meaning, which reduces memory interference. The interaction of associations and reference in word learning is discussed.     

Beyond IQ: A latent state-trait analysis of general intelligence, dynamic decision making, and implicit learning

The present study investigated cognitive performance measures beyond IQ. In particular, we investigated the psychometric properties of dynamic decision making variables and implicit learning variables and their relation with general intelligence and professional success. N = 173 employees from different companies and occupational groups completed two standard intelligence tests, two dynamic decision making tasks, and two implicit learning tasks at two measurement occasions each. We used structural equation models to test latent state-trait measurement models and the relation between constructs. The results suggest that dynamic decision making and implicit learning are substantially related with general intelligence. Furthermore, general intelligence is the best predictor for income, social status, and educational attainment. Dynamic decision making can predict supervisor ratings even beyond general intelligence.     

The effect of statistical learning on internal stimulus representations: Predictable items are enhanced even when not predicted

Statistical learning is the automatic and unconscious learning of environmental regularities and is a basic mechanism of learning in a variety of human perceptual and cognitive domains. Previous studies have mainly focused on the associative mechanisms of statistical learning. However, an unexplored question is whether the internal representations of individual stimuli are altered as their associations are learned. Using a temporal statistical learning paradigm, we examine this question across three experiments and find clear evidence that the internal representations of individual stimuli are differentially altered according to their degree of temporal predictability. These findings complement previous accounts of statistical learning and reveal an enriched mechanism of human learning, such that learning to associate items also enhances the representations of certain items relative to others.     

A Comment on ‘Rank Disagreement: A Comparison of Multi-Criteria Methodologies’

In a recent paper in this journal, Buede and Maxwell found reasonable agreement between MAVT and conventional AHP most preferred alternatives in a large-scale simulation. We show that MAVT would have had total agreement on preferred alternatives with two modified forms of AHP, referenced AHP and linking pin AHP, under simulation. © 1997 John Wiley & Sons, Ltd.     

Predicting performance on the Raven's Matrices: The roles of associative learning and retrieval efficiency

Previous studies have shown that performance on Williams and Pearlberg's (2006) complex associative learning task is a good predictor of fluid intelligence. This task is similar in structure to that used in studying the fan effect (Anderson, 1974), as both tasks involve forming multiple associations and require retrieval in the face of interference. The purpose of the present study was to investigate the relations among complex associative learning, working memory, and fluid intelligence. Specifically, we asked whether retrieval efficiency, as measured by the fan effect, could account for the relation between complex associative learning and performance on Raven's Advanced Progressive Matrices. Consistent with previous findings, complex associative learning predicted Raven's performance, but the fan effect did not account for this relation. Notably, the learning phase of the fan effect task was significantly correlated with both complex associative learning and Raven's performance, providing further support for the importance of learning as a predictor of fluid intelligence.     

The moment‐to‐moment pitch dynamics of child‐directed speech shape toddlers’ attention and learning

Young children have an overall preference for child‐directed speech (CDS) over adult‐directed speech (ADS), and its structural features are thought to facilitate language learning. Many studies have supported these findings, but less is known about processing of CDS at short, sub‐second timescales. How do the moment‐to‐moment dynamics of CDS influence young children's attention and learning? In Study 1, we used hierarchical clustering to characterize patterns of pitch variability in a natural CDS corpus, which uncovered four main word‐level contour shapes: ‘fall’, ‘rise’, ‘hill’, and ‘valley’. In Study 2, we adapted a measure from adult attention research—pupil size synchrony—to quantify real‐time attention to speech across participants, and found that toddlers showed higher synchrony to the dynamics of CDS than to ADS. Importantly, there were consistent differences in toddlers’ attention when listening to the four word‐level contour types. In Study 3, we found that pupil size synchrony during exposure to novel words predicted toddlers’ learning at test. This suggests that the dynamics of pitch in CDS not only shape toddlers’ attention but guide their learning of new words. By revealing a physiological response to the real‐time dynamics of CDS, this investigation yields a new sub‐second framework for understanding young children's engagement with one of the most important signals in their environment.     

A temporal common ground for learning: The moderating effect of shared mental models on the relation between team learning behaviours and performance improvement

In this longitudinal study, we integrated a team process and a learning curve perspective on team learning and empirically analysed whether team learning processes lead to performance improvement. In addition, we tested whether this relation is moderated by the similarity of team members’ task, team, and temporal mental models. We tested our model on a sample of 67 teams (314 individuals) competing in a management simulation over five consecutive time periods, using random coefficient modelling (RCM). Our findings suggest that team learning behaviours do not have a direct effect on the team learning curve, but temporal and task mental models are crucial for the translation of team learning behaviours into performance improvement. We found that when teams have similar task and temporal mental models, engaging in team learning processes is beneficial, whereas, when teams have dissimilar task and temporal mental models, it is detrimental to performance improvement. We did not find a significant effect for the moderating role of team mental model similarity. Our study emphasizes the importance of integrating different perspectives on team learning and provides support for the role of team cognition as a catalyst for team learning.     

The beat goes on: a commentary on Kelley's ‘Expanding the analysis of social orientations…’

Kelley's recent expansion of the analysis of social orientations is seen to be a logical extension of the interdependence concepts emanating from his extraordinary collaboration with the late John Thibaut. This expansion, extending the nomenclature of transitions lists to analysing the control of transition choices, is briefly summarized. The analysis holds much promise, which will be fully realized, however, only when valid assessments of the constituent components are available. © 1997 John Wiley & Sons, Ltd.     

The use of psychological theories by ‘naive’ judges: A study in implicit personality theory

Sixty-three subjects judged the behaviour of one of two fictitious stimulus persons by means of five different types of explanation which corresponded with specific psychological theories. These types of explanation based behaviour on adaptation to external conditions, reward/punishment, fulfilment of role expectations, effects of unconscious motives and the imitation of models. The explanations were evaluated on graphic rating scales as to their truth and convincingness. Two-way analyses of variance with repeated measures on one factor showed significant main effects for type of explanation and interaction effects of stimulus person × type of explanation for both dependent variables. The results are discussed in the light of studies done so far in implicit personality theory.     

Capitalizing on brand personalities in advertising: The influence of implicit self‐theories on ad appeal effectiveness

How can firms use brand personalities to develop the most persuasive advertising appeals? In this article, we examine advertising appeals that capitalize on the signaling opportunities that using these brands can provide (signaling ad appeal) versus the self-improvement opportunities that using these brands can offer (self-improvement ad appeal). In two studies, we find that the effectiveness of these appeals depends on consumers' implicit self-theories. Specifically, signaling ad appeals are more effective for consumers who believe their personal qualities are fixed and cannot be developed through their own efforts (entity theorists), whereas self-improvement ad appeals are more effective for consumers who believe their personal qualities are malleable and can be developed (incremental theorists). Implications for brand personality research and advertising are discussed.