From task characteristics to learning: A systematic review

Wielenga‐Meijer, E. G. A., Taris, T. W., Kompier, M. A. J. & Wigboldus, D. H. J. (2010). From task characteristics to learning: A systematic review. Scandinavian Journal of Psychology, 51, 363–375. Although many theoretical approaches propose that job characteristics affect employee learning, the question is why and how job characteristics influence learning. The present study reviews the evidence on the relationships among learning antecedents (i.e., job characteristics: demands, variety, autonomy and feedback), learning processes (including motivational, meta‐cognitive, cognitive and behavioral processes) and learning consequences. Building on an integrative heuristic model, we quantitatively reviewed 85 studies published between 1969 and 2005. Our analyses revealed strong evidence for a positive relation between job demands and autonomy on the one hand and motivational and meta‐cognitive learning processes on the other. Furthermore, these learning processes were positively related to learning consequences.     

Team performance and collective efficacy in the dynamic psychology of competitive team: A Bayesian network analysis

The purpose of this paper was to discover the relationships among 22 relevant psychological features in semi-professional football players in order to study team’s performance and collective efficacy via a Bayesian network (BN). The paper includes optimization of team’s performance and collective efficacy using intercausal reasoning pattern which constitutes a very common pattern in human reasoning. The BN is used to make inferences regarding our problem, and therefore we obtain some conclusions; among them: maximizing the team’s performance causes a decrease in collective efficacy and when team’s performance achieves the minimum value it causes an increase in moderate/high values of collective efficacy. Similarly, we may reason optimizing team collective efficacy instead. It also allows us to determine the features that have the strongest influence on performance and which on collective efficacy. From the BN two different coaching styles were differentiated taking into account the local Markov property: training leadership and autocratic leadership.     

Elimination of bias in introspection: Methodological advances,refinements, and recommendations

Building on past constructive criticism, the present study provides further methodological development focused on the elimination of bias that may occur during first-person observation. First, various sources of errors that may accompany introspection are distinguished based on previous critical literature. Four main errors are classified, namely attentional, attributional, conceptual, and expressional error. Furthermore, methodological recommendations for the possible elimination of these errors have been determined based on the analysis and focused excerpting of introspective scientific literature. The following groups of methodological recommendations were determined: 1) a better focusing of the subject's attention to their mental processes, 2) providing suitable stimuli, and 3) the sharing of introspective experience between subjects. Furthermore, the potential of adjustments in introspective research designs for eliminating attentional, attributional, conceptual, and expressional error is discussed.     

Coherence and correspondence criteria for rationality: experts' estimation of risks of sexually transmitted infections

The aim of this study is to examine both coherence and correspondence criteria for rationality in experts' judgments of risk. We investigated biases in risk estimation for sexually transmitted infections (STIs) predicted by fuzzy‐trace theory, i.e., that specific errors would occur despite experts' knowledge of correct responses. One hundred twenty professionals with specific knowledge of STI risks in adolescents were administered a survey questionnaire to test predictions concerning: knowledge deficits (producing underestimation of risks); gist‐based representation of risk categories (producing overestimation of condom effectiveness); retrieval failure for risk knowledge (producing lower risk estimates); and processing interference in combining risk estimates (producing biases in post‐test diagnosis of infection). Retrieval was manipulated by asking estimation questions that “unpacked” the STI category into infection types or did not specify infection types. Other questions differentiated processing biases from knowledge deficits or retrieval failure by directly providing requisite knowledge. Experts' knowledge of STI transmission and infection risks was verified empirically. Nevertheless, under predictable conditions, they misestimated risk, overestimated the effectiveness of condoms, and also suffered from processing biases. When questions provided better retrieval supports (unpacked format), risk estimates improved. Biases were linked to gist representations, retrieval failures, and processing errors, as opposed to knowledge about STIs. Results support fuzzy‐trace theory's dual‐process assumptions that different types of errors are dissociated from one another, and separate failures of coherence and correspondence among the same sample of experts. Copyright © 2005 John Wiley & Sons, Ltd.     

Sad mood,emotion regulation,and response inhibition

ABSTRACT

Affect-as-information models, resource allocation models, and arousal biased competition theory predict different effects of mood on cognition. To test these theories, this study examines the effect of sad mood on response inhibition (RI) and whether emotion dysregulation impacts this potential relationship. Participants were 273 undergraduates who wrote about either a typical day or a sad event from their life. They self-reported mood and emotion regulation difficulties, and RI was a composite score of Colour-Word Stroop, Stop-Signal, and go/no-go computerised tasks. The intensity of self-reported sad mood did not affect RI as predicted, but those who wrote about sad events had worse RI. Worse emotion regulation also predicted worse RI. Cognitive loads, rumination, and mind-wandering are discussed as possible mechanisms. Findings are extended from well-established areas such as working memory to the less-established area of RI.     

A Bayesian hierarchical diffusion model decomposition of performance in Approach–Avoidance Tasks

Common methods for analysing response time (RT) tasks, frequently used across different disciplines of psychology, suffer from a number of limitations such as the failure to directly measure the underlying latent processes of interest and the inability to take into account the uncertainty associated with each individual's point estimate of performance. Here, we discuss a Bayesian hierarchical diffusion model and apply it to RT data. This model allows researchers to decompose performance into meaningful psychological processes and to account optimally for individual differences and commonalities, even with relatively sparse data. We highlight the advantages of the Bayesian hierarchical diffusion model decomposition by applying it to performance on Approach–Avoidance Tasks, widely used in the emotion and psychopathology literature. Model fits for two experimental data-sets demonstrate that the model performs well. The Bayesian hierarchical diffusion model overcomes important limitations of current analysis procedures and provides deeper insight in latent psychological processes of interest.     

The development of bystander intentions and social–moral reasoning about intergroup verbal aggression

A developmental intergroup approach was taken to examine the development of prosocial bystander intentions among children and adolescents. Participants as bystanders (N = 260) aged 8–10 and 13–15 years were presented with scenarios of direct aggression between individuals from different social groups (i.e., intergroup verbal aggression). These situations involved either an ingroup aggressor and an outgroup victim or an outgroup aggressor and an ingroup victim. This study focussed on the role of intergroup factors (group membership, ingroup identification, group norms, and social–moral reasoning) in the development of prosocial bystander intentions. Findings showed that prosocial bystander intentions declined with age. This effect was partially mediated by the ingroup norm to intervene and perceived severity of the verbal aggression. However, a moderated mediation analysis showed that only when the victim was an ingroup member and the aggressor an outgroup member did participants become more likely with age to report prosocial bystander intentions due to increased ingroup identification. Results also showed that younger children focussed on moral concerns and adolescents focussed more on psychological concerns when reasoning about their bystander intention. These novel findings help explain the developmental decline in prosocial bystander intentions from middle childhood into early adolescence when observing direct intergroup aggression.     

Assessing Mathematics Misunderstandings via Bayesian Inverse Planning

Online educational technologies offer opportunities for providing individualized feedback and detailed profiles of students' skills. Yet many technologies for mathematics education assess students based only on the correctness of either their final answers or responses to individual steps. In contrast, examining the choices students make for how to solve the equation and the ways in which they might answer incorrectly offers the opportunity to obtain a more nuanced perspective of their algebra skills. To automatically make sense of step-by-step solutions, we propose a Bayesian inverse planning model for equation solving that computes an assessment of a learner's skills based on her pattern of errors in individual steps and her choices about what sequence of problem-solving steps to take. Bayesian inverse planning builds on existing machine learning tools to create a generative model relating (mis)-understandings to equation solving choices. Two behavioral experiments demonstrate that the model can interpret people's equation solving and that its assessments are consistent with those of experienced teachers. A third experiment uses this model to tailor guidance for learners based on individual differences in misunderstandings, closing the loop between assessing understanding, and using that assessment within an educational technology. Finally, because the bottleneck in applying inverse planning to a new domain is in creating the model of possible student misunderstandings, we show how to combine inverse planning with an existing production rule model to make inferences about student misunderstandings of fraction arithmetic.