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23
Stereotype Threat Reinterpreted as a Regulatory Mismatch
, 2009
"... Research documents performance decrements resulting from the activation of a negative task-relevant stereotype. We combine a number of strands of work to identify causes of stereotype threat in a way that allows us to reverse the effects and improve the performance of individuals with negative task ..."
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Cited by 21 (7 self)
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Research documents performance decrements resulting from the activation of a negative task-relevant stereotype. We combine a number of strands of work to identify causes of stereotype threat in a way that allows us to reverse the effects and improve the performance of individuals with negative task-relevant stereotypes. We draw on prior work suggesting that negative stereotypes induce a prevention focus, and other research suggesting that people exhibit greater flexibility when their regulatory focus matches the reward structure of the task. This work suggests that stereotype threat effects emerge from a prevention focus combined with tasks that have an explicit or implicit gains reward structure. We find flexible performance can be induced in individuals who have a negative task-relevant stereotype by using a losses reward structure. We demonstrate the interaction of stereotypes and the reward structure of the task using chronic stereotypes and GRE math problems (Experiment 1), and primed stereotypes and a category learning task (Experiments 2a and 2b). We discuss implications of this research for other work on stereotype threat.
Regulatory Fit and Systematic Exploration in a Dynamic Decision-Making Environment
"... This work explores the influence of motivation on choice behavior in a dynamic decision-making environment, where the payoffs from each choice depend on one’s recent choice history. Previous research reveals that participants in a regulatory fit exhibit increased levels of exploratory choice and fle ..."
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Cited by 17 (6 self)
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This work explores the influence of motivation on choice behavior in a dynamic decision-making environment, where the payoffs from each choice depend on one’s recent choice history. Previous research reveals that participants in a regulatory fit exhibit increased levels of exploratory choice and flexible use of multiple strategies over the course of an experiment. The present study placed promotion and prevention-focused participants in a dynamic environment for which optimal performance is facilitated by systematic exploration of the decision space. These participants either gained or lost points with each choice. Our experiment revealed that participants in a regulatory fit were more likely to engage in systematic exploration of the task environment than were participants in a regulatory mismatch and performed more optimally as a result. Implications for contemporary models of human reinforcement learning are discussed.
Working-Memory Load and Temporal Myopia in Dynamic Decision Making
"... We examined the role of working memory (WM) in dynamic decision making by having participants perform decision-making tasks under single-task or dual-task conditions. In 2 experiments participants performed dynamic decision-making tasks in which they chose 1 of 2 options on each trial. The decreasin ..."
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Cited by 13 (11 self)
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We examined the role of working memory (WM) in dynamic decision making by having participants perform decision-making tasks under single-task or dual-task conditions. In 2 experiments participants performed dynamic decision-making tasks in which they chose 1 of 2 options on each trial. The decreasing option always gave a larger immediate reward but caused future rewards for both options to decrease. The increasing option always gave a smaller immediate reward but caused future rewards for both options to increase. In each experiment we manipulated the reward structure such that the decreasing option was the optimal choice in 1 condition and the increasing option was the optimal choice in the other condition. Behavioral results indicated that dual-task participants selected the immediately rewarding decreasing option more often, and single-task participants selected the increasing option more often, regardless of which option was optimal. Thus, dual-task participants performed worse on 1 type of task but better on the other type. Modeling results showed that single-task participants ’ data were most often best fit by a win-stay, lose-shift (WSLS) rule-based model that tracked differences across trials, and dual-task participants ’ data were most often best fit by a Softmax reinforcement learning model that tracked recency-weighted average rewards for each option. This suggests that manipulating WM load affects the degree to which participants focus on the immediate versus delayed consequences of their actions and whether they employ a rule-based WSLS strategy, but it does not necessarily affect how well people weigh the immediate versus delayed benefits when determining the long-term utility of each option.
The motivation–cognition interface in learning and decision making
- Current Directions in Psychological Science
, 2010
"... In this article we discuss how incentive motivations and task demands affect performance. We present a three-factor framework that suggests that performance is determined from the interaction of global incentives, local incentives, and the psychological pro-cesses needed to achieve optimal task perf ..."
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Cited by 13 (5 self)
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In this article we discuss how incentive motivations and task demands affect performance. We present a three-factor framework that suggests that performance is determined from the interaction of global incentives, local incentives, and the psychological pro-cesses needed to achieve optimal task performance. We review work that examines the implications of the motivation–cognition interface in classification and choice and on phenomena such as stereotype threat and performance pressure. We show that, under some conditions, stereotype threat and pressure accentuate performance. We discuss the implications of this work for neuropsychological assessment and outline a number of challenges for future research.
Regulatory fit effects on stimulus identification
, 2010
"... Abstract This article examines the effects of a fit between a person’s global regulatory focus and the local task reward structure on perceptual processing and judgment. On each trial, participants were presented with one of two briefly presented stimuli and were asked to identify it. Participants w ..."
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Cited by 1 (0 self)
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Abstract This article examines the effects of a fit between a person’s global regulatory focus and the local task reward structure on perceptual processing and judgment. On each trial, participants were presented with one of two briefly presented stimuli and were asked to identify it. Participants were placed in a promotion focus (a situationally induced sensitivity to gains) or a prevention focus (a situationally induced sensitivity to losses) and were asked to maximize gains or minimize losses. An asymmetric payoff ratio biased the overall reward toward one identification response over the other. Two experiments tested the role of regulatory fit when internal familiarity and perceptual sensitivity were low or high. When familiarity and sensitivity were low, partic-ipants in a regulatory fit (promotion focus with gains or a prevention focus with losses) showed greater perceptual sensitivity but no response bias differences, relative to participants in a regulatory mismatch. When familiarity and sensitivity were high, participants in a regulatory fit showed a response bias toward the high-payoff stimulus but no differences in perceptual sensitivity. Speculations are offered on the neurobiological basis of this effect, as well as implications of this work for clinical disorders such as depression.
� � Future DirectionsRegulatory Fit Framework
"... � � Need to understand how goals and rewards influence cognition and behavior. � � More complicated than anecdotal notions � � Approach vs. avoidance distinction � � Global incentive vs. local goal pursuit mechanism � � Leads to regulatory fit or mismatch � � Regulatory fit affects cognition and beh ..."
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� � Need to understand how goals and rewards influence cognition and behavior. � � More complicated than anecdotal notions � � Approach vs. avoidance distinction � � Global incentive vs. local goal pursuit mechanism � � Leads to regulatory fit or mismatch � � Regulatory fit affects cognition and behaviorOverview of Talk
Memory & Cognition
"... doi:10.3758/MC.36.8.1460 Ratio and difference comparisons of expected reward in decision-making tasks ..."
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doi:10.3758/MC.36.8.1460 Ratio and difference comparisons of expected reward in decision-making tasks
Motivation-Cognition Interface 1 The Motivation-Cognition Interface in Learning and Decision-Making
, 2009
"... In this article we discuss how incentive motivations and task demands affect performance. We present a three-factor framework that suggests that performance is determined from the interaction of global incentives, local incentives, and the psychological processes needed to achieve optimal task perfo ..."
Abstract
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In this article we discuss how incentive motivations and task demands affect performance. We present a three-factor framework that suggests that performance is determined from the interaction of global incentives, local incentives, and the psychological processes needed to achieve optimal task performance. We review work that examines the implications of the motivation-cognition interface in classification, choice and on phenomena such as stereotype threat and performance pressure. We show that under some conditions stereotype threat and pressure accentuate performance. We discuss the implications of this work for neuropsychological assessment, and outline a number of challenges for future research.
Dynamic Decision-Making 1 Running Head: WORKING MEMORY AND DYNAMIC DECISION MAKING Working-Memory Load and Temporal Myopia in Dynamic Decision-Making
"... We examined the role of working-memory (WM) in dynamic decision-making by having participants perform decision-making tasks under single-task or dual-task conditions. In two experiments participants performed dynamic decision-making tasks where they chose one of two options on each trial. The Decrea ..."
Abstract
- Add to MetaCart
(Show Context)
We examined the role of working-memory (WM) in dynamic decision-making by having participants perform decision-making tasks under single-task or dual-task conditions. In two experiments participants performed dynamic decision-making tasks where they chose one of two options on each trial. The Decreasing option always gave a larger immediate reward, but caused future rewards for both options to decrease. The Increasing option always gave a smaller immediate reward, but caused future rewards for both options to increase. In each experiment we manipulated the reward structure such that the Decreasing option was the optimal choice in one condition and the Increasing option was the optimal choice in the other condition. Behavioral results indicated that Dual-task participants selected the immediately rewarding Decreasing option more often, while Single-task participants selected the Increasing option more often, regardless of which option was optimal. Thus, Dual-task participants performed worse on one type of task but better on the other type. Modeling results showed that Single-task participants ’ data was most often best fit by a Win-Stay-Lose-Shift (WSLS) rule-based model that tracked differences across trials, while Dual-task participants ’ data was most often best fit by a Softmax reinforcement learning model that tracked recency-weighted average rewards for each option. This suggests that manipulating WM load affects the degree to which participants focus on the immediate versus delayed consequences of their actions and whether they employ a rule-based WSLS strategy, but it does not necessarily affect how well people weigh the immediate versus delayed benefits when determining the long-term utility of each option.
