Peer-Assisted Learning Is More Effective at Higher Task Complexity and Difficulty.

This paper presents two studies in which a peer-assisted learning condition was compared to an individual learning condition. The first study used the paired-associates learning task and the second study used an incrementally more complex task-the remote associate test. Participants in the peer-assisted learning condition worked in groups of four. They had to solve a given problem individually and give a first answer before being able to request to see their peers' solutions; then, a second answer was issued. After six sessions of peer-assisted practice, a final individual test was administered. Peer interaction was found to benefit learning in both studies but the benefit transferred to the final test only in the second study. Fine-grained behavioral analyses and computational modeling suggested that the benefits of peer interaction were (partially) offset by its costs, particularly increased cognitive load and error exposure. Overall, the superiority of peer-assisted learning over individual learning was more pronounced in the more complex task and for the more difficult problems in that task.

Effects of Choice Restriction on Accuracy and User Experience in an Internet-Based Geopolitical Forecasting Task.

Large-scale geopolitical forecasting tournaments have emerged in recent years as effective testbeds for conducting research into novel forecasting tools and methods. A challenge of such tournaments involves the distribution of forecasting load across forecasters, since there are often more forecasting questions than an individual forecaster can answer. Intelligent load distribution, or triage, may therefore be helpful in ensuring that all questions have sufficient numbers of forecasts to benefit from crowd-based aggregation and that individual forecasters are matched to the questions for which they are best suited. A possible downside of triage, however, is that it restricts the choices of forecasters, potentially degrading motivation and accuracy. In two studies involving pools of novice forecasters recruited online, we examined the impact of limiting forecaster choice on forecasters' accuracy and subjective experience, including motivation. In Study 1, we tested the impact of restricted choice by comparing the forecasting accuracy and subjective experience of users who perceived they did or did not have choice in the questions they forecasted. In Study 2, we further tested the impact of restricted choice by providing users with different menu sizes of questions from which to choose. In both studies, we found no evidence that limiting forecaster choice adversely affected forecasting accuracy or subjective experience. This suggests that in large-scale forecasting tournaments, it may be possible to implement choice-limiting triage strategies without sacrificing individual accuracy and motivation.

Trust Miscalibration Is Sometimes Necessary: An Empirical Study and a Computational Model.

The literature on trust seems to have reached a consensus that appropriately calibrated trust in humans or machines is highly desirable; miscalibrated (i.e., over- or under-) trust has been thought to only have negative consequences (i.e., over-reliance or under-utilization). While not invalidating the general idea of trust calibration, a published computational cognitive model of trust in strategic interaction predicts that some local and temporary violations of the trust calibration principle are critical for sustained success in strategic situations characterized by interdependence and uncertainty (e.g., trust game, prisoner's dilemma, and Hawk-dove). This paper presents empirical and computational modeling work aimed at testing the predictions of under- and over-trust in an extension of the trust game, the multi-arm trust game, that captures some important characteristics of real-world interpersonal and human-machine interactions, such as the ability to choose when and with whom to interact among multiple agents. As predicted by our previous model, we found that, under conditions of increased trust necessity, participants actively reconstructed their trust-investment portfolios by discounting their trust in their previously trusted counterparts and attempting to develop trust with the counterparts that they previously distrusted. We argue that studying these exceptions of the principle of trust calibration might be critical for understanding long-term trust calibration in dynamic environments.

The Case of the Cognitive (Opti)miser: Electrophysiological Correlates of Working Memory Maintenance Predict Demand Avoidance.

People are often considered cognitive misers. When given a free choice between two tasks, people tend to choose tasks requiring less cognitive effort. Such demand avoidance (DA) is associated with cognitive control, but it is still not clear to what extent individual differences in cognitive control can account for variations in DA. We sought to elucidate the relation between cognitive control and cognitive effort preferences by investigating the extent to which sustained neural activity in a task requiring cognitive control is correlated with DA. We hypothesized that neural measures of efficient filtering will predict individual variations in demand preferences. To test this hypothesis, we had participants perform a delayed-match-to-sample paradigm with their ERPs recorded, as well as a separate behavioral demand-selection task. We focused on the ERP correlates of cognitive filtering efficiency (CFE)-the ability to ignore task-irrelevant distractors during working memory maintenance-as it manifests in a modulation of the contralateral delay activity, an ERP correlate of cognitive control. As predicted, we found a significant positive correlation between CFE and DA. Individuals with high CFE tended to be significantly more demand avoidant than their low-CFE counterparts. Low-CFE individuals, in comparison, did not form distinct cognitive effort preferences. Overall, our results suggest that cognitive control over the contents of visual working memory contribute to individual differences in the expression of cognitive effort preferences. This further implies that these observed preferences are the product of sensitivity to cognitive task demands.

Cognitive Model of Trust Dynamics Predicts Human Behavior within and between Two Games of Strategic Interaction with Computerized Confederate Agents.

When playing games of strategic interaction, such as iterated Prisoner's Dilemma and iterated Chicken Game, people exhibit specific within-game learning (e.g., learning a game's optimal outcome) as well as transfer of learning between games (e.g., a game's optimal outcome occurring at a higher proportion when played after another game). The reciprocal trust players develop during the first game is thought to mediate transfer of learning effects. Recently, a computational cognitive model using a novel trust mechanism has been shown to account for human behavior in both games, including the transfer between games. We present the results of a study in which we evaluate the model's a priori predictions of human learning and transfer in 16 different conditions. The model's predictive validity is compared against five model variants that lacked a trust mechanism. The results suggest that a trust mechanism is necessary to explain human behavior across multiple conditions, even when a human plays against a non-human agent. The addition of a trust mechanism to the other learning mechanisms within the cognitive architecture, such as sequence learning, instance-based learning, and utility learning, leads to better prediction of the empirical data. It is argued that computational cognitive modeling is a useful tool for studying trust development, calibration, and repair.

The effect of practice on n-2 repetition costs in set switching.

Inhibition in set switching is inferred from so-called n-2 repetition costs: slower response times to ABA sequences compared to CBA sequences (where A, B, and C are arbitrary labels for different tasks). These costs are thought to reflect the persisting inhibition of task A when it was disengaged recently (as is the case in an ABA sequence). In this study we were interested in whether more inhibition may be required when the tasks are relatively novel. To this end, we examined the effect of practice on the n-2 repetition cost in nine participants across five experimental sessions, with 1222 trials performed in each session. The results show a clear reduction in the n-2 repetition cost, being altogether absent from the final sessions. Such a reduction is predicted by both: (a) a recent computational model of the n-2 repetition cost (Grange, Juvina, & Houghton, 2013) due to the gradual strengthening of task-related memory elements with practice to the point where inhibition has less impact; and (b) prior work showing smaller n-2 repetition costs with greater cue-target association strength (Houghton, Pritchard, & Grange, 2009). In this paper, we integrate these two theoretical derivations by extending our computational model, which fit the current data-at the mean level, block level, and individual-subject (i.e., individual differences) level-well.

On costs and benefits of n-2 repetitions in task switching: towards a behavioural marker of cognitive inhibition.

Inhibition in task switching is inferred from slower reaction times returning to a recently performed task after one intervening trial (i.e. an ABA sequence) compared to returning to a task not recently performed (CBA sequence). These n-2 repetition costs are thought to reflect the persisting inhibition of a task after its disengagement. As such, the n-2 repetition cost is an attractive tool for the researcher interested in inhibitory functioning in clinical/neurological/neuroscience disciplines. In the literature, an absence of this cost is often interpreted as an absence of inhibition, an assumption with strong implications for researchers. The current paper argues that this is not necessarily an accurate interpretation, as an absence of inhibition should lead to an n-2 repetition benefit as a task's activation level will prime performance. This argument is supported by three instances of a computational cognitive model varying the degree of inhibition present. An inhibition model fits human n-2 repetition costs well. Removal of the inhibition-the activation-only model-predicts an n-2 repetition benefit. For the model to produce a null n-2 repetition cost, small amounts of inhibition were required-the reduced-inhibition model. The authors also demonstrate that a lateral-inhibition locus of the n-2 repetition cost cannot account for observed human data. The authors conclude that a null n-2 repetition cost provides no evidence on its own for an absence of inhibition, and propose reporting of a significant n-2 repetition benefit to be the best evidence for a lack of inhibition. Implications for theories on task switching are discussed.

The effects of individual and context on aggression in repeated social interaction.

In two studies using variations of the Prisoner's Dilemma game, we explore the impact of individual traits and social context on aggressive behavior. In the first study, we compared defection rates in the Iterated Prisoner's Dilemma when participants were presented with a payoff matrix (Description condition) or learned payoffs through experience (Experience condition). Interpersonal trust and maximizing tendency led to relatively less defection in the Description condition than in the Experience condition, demonstrating that individual characteristics manifest differently depending on the information available to decision-makers. In the second study, we employed a new game paradigm, the Intergroup Prisoner's Dilemma with Intragroup Power Dynamics, to examine the way that power motives influence extreme aggressive behavior. We discovered that certain individuals exhibit very high levels of defection, but only when they play with particular combinations of predefined strategies, further suggesting how the confluence of individual factors and context can induce aggression.

Cognitive control: componential and yet emergent.

In this commentary, I will argue that the componential and emergent views of cognitive control as defined by Cooper (2010) do not necessarily oppose each other, and I will try to make a case for their interdependence. First, I will use the construct of cognitive inhibition-one of the main componential control functions mentioned in the target articles-to illustrate my line of reasoning. Then, I will comment on how some of the target articles, each from a different perspective, bring arguments in favor of this integrative view.

A repetition-suppression account of between-trial effects in a modified Stroop paradigm.

Theories that postulate cognitive inhibition are very common in psychology and cognitive neuroscience [e.g., Hasher, L., Lustig, C., & Zacks, R. T. (2007). Inhibitory mechanisms and the control of attention. In A. Conway, C. Jarrold, M. Kane, A. Miyake, A. Towse, & J. Towse (Eds.), Variation in working memory (pp. 227-249). New York, NY: Oxford, University Press], although they have recently been severely criticized [e.g., MacLeod, C. M., Dodd, M. D., Sheard, E. D., Wilson, D. E., & Bibi, U. (2003). In opposition to inhibition. In H. Ross (Ed.), The psychology of learning and motivation (Vol. 43, pp. 163-214). Elsevier Science]. This paper poses and attempts to answer the question whether a research program with cognitive inhibition as its main theoretical assumption is still worth pursuing. We present a set of empirical data from a modified Stroop paradigm that replicates previously reported findings. These findings refer to between-trial effects previously described in the literature on Stroop, negative priming, and inhibition-of-return. Existing theoretical accounts fail to explain all these effects in an integrated way. A repetition-suppression mechanism is proposed in order to account for these data. This mechanism is instantiated as a computational cognitive model. The theoretical implications of this model are discussed.

Too much control can hurt: a threaded cognition model of the attentional blink.

Explanations for the attentional blink (AB; a deficit in identifying the second of two targets when presented 200-500 ms after the first) have recently shifted from limitations in memory consolidation to disruptions in cognitive control. With a new model based on the threaded cognition theory of multi-tasking we propose a different explanation: the AB is produced by an overexertion of control. This overexertion is produced by a production rule that blocks target detection during memory consolidation. In addition to fitting many known effects in the literature, the model predicts that adding certain secondary tasks will decrease the AB. In Experiment 1, a secondary task is added to the AB task in which participants have to respond to a moving dot. As predicted, AB decreases. Experiment 2 expands this result by controlling for learning, and adds a second variation, rotating the first target. For this variation the model predicts an increase in AB, which is indeed what we found.