Personality traits and perceptions of organisational justice

This study examined the association between five‐factor model personality traits and perceptions of organisational justice. The sample for the study comprised 903 participants (35–50 years old; 523 women) studied in 2007 and 2012. Measures used were the Neuroticism, Extraversion, Openness, Five‐Factor Inventory questionnaire and the short organisational justice measure. The results showed that high neuroticism was associated with low distributive, procedural and interactional justice. Furthermore, high agreeableness was associated with high procedural and interactional justice and high openness with high distributive justice. This study suggests that neuroticism, agreeableness and openness are involved in perceptions of organisational justice and that personality should be considered in research and in practices at the workplace.     

Modeling adaptive cooperative and competitive metaphors as mental models for joint decision making

In this paper, joint decision making processes are studied and the role of cognitive metaphors as mental models in them. A second-order self-modeling network model is introduced based on mechanisms known from cognitive and social neuroscience and cognitive metaphor and mental model literature. The cognitive metaphors were modeled as specific forms of mental models providing a form of modulation within the joint decision making process. The model addresses not only the use of these mental models in the decision making, but also their hebbian learning and the control over the learning. The obtained self-modeling network model was applied to two types of metaphors that affect joint decision making in different manners: a cooperative metaphor and a competitive metaphor. By a number of scenarios it was shown how the obtained self-modeling network model can be used to simulate and analyze joint decision processes and how they are influenced by such cognitive metaphors.     

Sequential congruency effects in implicit sequence learning

We deal with situations incongruent with our automatic response tendencies much better right after having done so on a previous trial than after having reacted to a congruent trial. The nature of the mechanisms responsible for these sequential congruency effects is currently a hot topic of debate. According to the conflict monitoring model these effects depend on the adjustment of control triggered by the detection of conflict on the preceding situation. We tested whether these conflict monitoring processes can operate implicitly in an implicit learning procedure, modulating the expression of knowledge of which participants are not aware. We reanalyze recently published data, and present an experiment with a probabilistic sequence learning procedure, both showing consistent effects of implicit sequence learning. Despite being implicit, the expression of learning was reduced or completely eliminated right after trials incongruent with the learned sequence, thus showing that sequential congruency effects can be obtained even when the source of congruency itself remains implicit.     

Computational models for the combination of advice and individual learning

Decision making often takes place in social environments where other actors influence individuals' decisions. The present article examines how advice affects individual learning. Five social learning models combining advice and individual learning-four based on reinforcement learning and one on Bayesian learning-and one individual learning model are tested against each other. In two experiments, some participants received good or bad advice prior to a repeated multioption choice task. Receivers of advice adhered to the advice, so that good advice improved performance. The social learning models described the observed learning processes better than the individual learning model. Of the models tested, the best social learning model assumes that outcomes from recommended options are more positively evaluated than outcomes from nonrecommended options. This model correctly predicted that receivers first adhere to advice, then explore other options, and finally return to the recommended option. The model also predicted accurately that good advice has a stronger impact on learning than bad advice. One-time advice can have a long-lasting influence on learning by changing the subjective evaluation of outcomes of recommended options.     

Second-order conditioning of human causal learning

This article provides the first demonstration of a reliable second-order conditioning (SOC) effect in human causal learning tasks. It demonstrates the human ability to infer relationships between a cause and an effect that were never paired together during training. Experiments 1a and 1b showed a clear and reliable SOC effect, while Experiments 2a and 2b demonstrated that first-order extinction did not affect SOC. These results were similar to those found in animal and human conditioning and suggested that a similar associative mechanism could explain these effects. However, they can also be used to look into the underlying causal mental model people build and store while they are learning this task. From a cognitive view, overall results suggest that an independent rather than a chain causal mental model is stored after second-order learning in human causal tasks.     

On the dynamics and adaptivity of mental processes: Relating adaptive dynamical systems and self-modeling network models by mathematical analysis

In this paper, it is addressed by mathematical analysis how network-oriented modeling relates to the dynamical systems perspective on mental processes. It has been mathematically proven that any dynamical system can be modeled as a temporal-causal network model and that any adaptive dynamical system (of any order) can be modeled by a self-modeling network (of the same order).     

A joint modeling framework of responses and response times to assess learning outcomes

Abstract

A general modeling framework of response accuracy and response times is proposed to track skill acquisition and provide additional diagnostic information on the change of latent speed in a learning environment. This framework consists of two types of models: a dynamic response model that captures the response accuracy and the change of discrete latent attribute profile upon factors such as practice, intervention effects, and other latent and observable covariates, and a dynamic response time model that describes the change of the continuous response latency due to change of latent attribute profile. These two types of models are connected through a parameter, describing the change rate of the latent speed through the learning process, and a covariate defined as a function of the latent attribute profile. A Bayesian estimation procedure is developed to calibrate the model parameters and measure the latent variables. The estimation algorithm is evaluated through several simulation studies under various conditions. The proposed models are applied to a real data set collected through a spatial rotation diagnostic assessment paired with learning tools.     

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.     

An adaptive network model covering metacognition to control adaptation for multiple mental models

Learning processes can be described by adaptive mental (or neural) network models. If metacognition is used to regulate learning, the adaptation of the mental network becomes itself adaptive as well: second-order adaptation. In this paper, a second-order adaptive mental network model is introduced for metacognitive regulation of learning processes. The focus is on the role of multiple internal mental models, in particular, the case of visualisation to support learning of numerical or symbolic skills. The second-order adaptive network model is illustrated by a case scenario for the role of visualisation to support learning multiplication at the primary school.     

Adaptive memory: longevity and learning intentionality of the animacy effect

The animacy effect—the finding that animates are better remembered than inanimates—is proving to be a robust empirical phenomenon. Considering the adaptiveness of the animate advantage, one might expect it to remain after long retention intervals and also to be present irrespectively of an intention to learn. The present study explores these two aspects. Different groups of participants learned (intentional learning) or rated the pleasantness (incidental learning) of animate and inanimate words; memory was tested immediately or after a 48?h delay. A significant animacy effect was obtained after both retention intervals and in both learning conditions. Two significant interactions revealed a larger animacy effect, as well as a larger effect of the retention interval, when learning was incidental. Our findings reinforce the robustness of the animacy effect and provide some insight into possible proximate mechanisms of the effect.     

Bio-inspired cognitive model of motor learning by imitation

Learning, and even more so by imitation, is an essential Cognitive Functions because it is carried out throughout life and allows us to adapt our behaviors from other beings through observation. In this work, we propose a model, and implementation of the cognitive function of imitation motor learning (IML), based on psychological and neuroscientific evidence. According to the evidence, learning by imitation includes imitation of action and imitation of action over an object sub-processes. The imitation of action consists of the movement of the limbs. The imitation of action over an object consists of the interaction with an object within the environment. We achieve an implementation of the proposed model for IML and endow a virtual entity with it. In order to validate the proposal, we use a case study to analyze the sub-processes performance. From results, we conclude that both imitation of action and imitation of action over an object sub-processes play an essential role in getting the agent to interact with stimuli within the environment.     

Learning style,judgements of learning,and learning of verbal and visual information

The concept of learning style is immensely popular despite the lack of evidence showing that learning style influences performance. This study tested the hypothesis that the popularity of learning style is maintained because it is associated with subjective aspects of learning, such as judgements of learning (JOLs). Preference for verbal and visual information was assessed using the revised Verbalizer‐Visualizer Questionnaire (VVQ). Then, participants studied a list of word pairs and a list of picture pairs, making JOLs (immediate, delayed, and global) while studying each list. Learning was tested by cued recall. The results showed that higher VVQ verbalizer scores were associated with higher immediate JOLs for words, and higher VVQ visualizer scores were associated with higher immediate JOLs for pictures. There was no association between VVQ scores and recall or JOL accuracy. As predicted, learning style was associated with subjective aspects of learning but not objective aspects of learning.     

Multiple regression analyses in artificial-grammar learning: The importance of control groups

In artificial-grammar learning, it is crucial to ensure that above-chance performance in the test stage is due to learning in the training stage but not due to judgemental biases. Here we argue that multiple regression analysis can be successfully combined with the use of control groups to assess whether participants were able to transfer knowledge acquired during training when making judgements about test stimuli. We compared the regression weights of judgements in a transfer condition (training and test strings were constructed by the same grammar but with different letters) with those in a control condition. Predictors were identical in both conditions—judgements of control participants were treated as if they were based on knowledge gained in a standard training stage. The results of this experiment as well as reanalyses of a former study support the usefulness of our approach.     

Procedural learning,consolidation, and transfer of a new skill in Developmental Coordination Disorder

The aim of this study was to explore the differences in procedural learning abilities between children with DCD and typically developing children by investigating the steps that lead to skill automatization (i.e., the stages of fast learning, consolidation, and slow learning). Transfer of the skill to a new situation was also assessed. We tested 34 children aged 6–12 years with and without DCD on a perceptuomotor adaptation task, a form of procedural learning that is thought to involve the cerebellum and the basal ganglia (regions whose impairment has been associated with DCD) but also other brain areas including frontal regions. The results showed similar rates of learning, consolidation, and transfer in DCD and control children. However, the DCD children's performance remained slower than that of controls throughout the procedural task and they reached a lower asymptotic performance level; the difficulties observed at the outset did not diminish with practice.     

Event-related fMRI of category learning: differences in classification and feedback networks

Eighteen healthy young adults underwent event-related (ER) functional magnetic resonance imaging (fMRI) of the brain while performing a visual category learning task. The specific category learning task required subjects to extract the rules that guide classification of quasi-random patterns of dots into categories. Following each classification choice, visual feedback was presented. The average hemodynamic response was calculated across the eighteen subjects to identify the separate networks associated with both classification and feedback. Random-effects analyses identified the different networks implicated during the classification and feedback phases of each trial. The regions included prefrontal cortex, frontal eye fields, supplementary motor and eye fields, thalamus, caudate, superior and inferior parietal lobules, and areas within visual cortex. The differences between classification and feedback were identified as (i) overall higher volumes and signal intensities during classification as compared to feedback, (ii) involvement of the thalamus and superior parietal regions during the classification phase of each trial, and (iii) differential involvement of the caudate head during feedback. The effects of learning were then evaluated for both classification and feedback. Early in learning, subjects showed increased activation in the hippocampal regions during classification and activation in the heads of the caudate nuclei during the corresponding feedback phases. The findings suggest that early stages of prototype-distortion learning are characterized by networks previously associated with strategies of explicit memory and hypothesis testing. However as learning progresses the networks change. This finding suggests that the cognitive strategies also change during prototype-distortion learning.     

Thirty years of research on online learning

This paper presents a personal account of developments in research on online learning over the past 30 years. Research on how to design online instruction represents an example of applying the science of learning to education. It contributes to the science of learning (as exemplified by developments in cognitive load theory, the cognitive theory of multimedia learning, and incorporating metacognitive, motivational, and affective aspects of learning), the science of instruction (as exemplified by the continuing development of research‐based principles of instructional design), and the science of assessment (as exemplified by supplementing self‐report surveys and retention tests with multilevel transfer tests, log file data during learning, and cognitive neuroscience measures of cognitive processing during learning). Some recurring themes are that learning is caused by instructional methods rather than instructional media, so research should focus on features that are uniquely afforded by digital learning environments; instructional practice should be grounded in rigorous and systematic research, including value‐added experiments aimed at pinpointing the active ingredients in online instruction; research in online learning should identify boundary conditions under which instructional techniques are most effective; and research in online learning should test and contribute to learning theory.     

Three- and four-year-olds spontaneously use others' past performance to guide their learning

A wealth of human knowledge is acquired by attending to information provided by other people – but some people are more credible sources than others. In two experiments, we explored whether young children spontaneously keep track of an individual’s history of being accurate or inaccurate and use this information to facilitate subsequent learning. We found that 3- and 4-year-olds favor a previously accurate individual when learning new words and learning new object functions and applied the principle of mutual exclusivity to the newly learned words but not the newly learned functions. These findings expand upon previous research in a number of ways, most importantly by showing that (a) children spontaneously keep track of an individual’s history and use it to guide subsequent learning without any prompting, and (b) children’s sensitivity to others’ prior accuracy is not specific to the domain of language.     

Frames of Reference for Human Perceptual-Motor Coordination: Space-Based Versus Joint-Based Adaptation

In this study, the authors addressed the issue of whether space-based motor planning occurs at a higher, equal, or lower level of central nervous system control than joint-based motor planning by using a computerized adaptation paradigm. Visual displays of participants' (N = 32) reaching movements to spatial targets were distorted either with respect to spatial hand displacements (space-based distortion) or with respect to joint angle displacements (joint-based distortion). Participants adapted more easily to space-based distortion than to joint-based distortion. The results suggest that when the participants were confronted with new visuomotor mappings, they aimed for virtual spatial targets whose positions were adjusted to compensate for the distortions associated with the new mappings. That strategy was preferred over a joint- or posture-based strategy, in which a posture is selected for the displayed spatial target and is then modified so that the new mapping between adopted and seen positions can be accommodated. The results support the widely held view that space-based planning occurs at a higher level than joint-based planning.     

The effects of situational goal orientation and cultural learning values on team performance and adaptation to change

In this paper, we examine the unique effects of situational goal orientation and cultural learning values on team adaptation to change and the moderating role of cultural learning values in the relationship between goal orientation and team performance and adaptation. To do this, we conducted an experiment using a 2 × 2 × 2 repeated-measures factorial design, consisting of high and low levels of learning values, situational goal orientation (i.e., learning goals and performance goals). The experimental task involved two phases: we looked at team performance in Phase 1 and team adaptation to change in Phase 2. Forty 3-person teams were randomly assigned to four experimental conditions and all teams engaged in a complex bridge-planning task. Performance was measured in terms of the quality of the planned bridge. Results showed independent effects of situational goal orientation and cultural learning values on team performance and adaptation to change. Cultural learning values also moderated the relationship between goal orientation and performance and adaptation to change. Finally, the combination of learning goals and high learning values resulted in the highest levels of initial team performance (Phase 1) and adaptation to change and improved performance (Phase 2), as compared to all other examined conditions.