Deconstructing Proactive Control and Reward Incentive Effects on Rapid Instructed Task Learning

Rapid instructed task learning (RITL), the ability to quickly learn and implement a new task from instructions, is hypothesized to rely on proactive cognitive control. In three experiments, we examined self-paced preparation time as an index of proactive control during the performance of novel versus previously practiced tasks. We hypothesized that both between individuals and on a trial-by-trial basis, longer preparation times would be associated with improved performance on novel tasks. Furthermore, we predicted that incentivizing performance with monetary rewards would increase proactive control, as indexed by preparation times and improved task performance. Replicating Cole et al. (2018), we observed that longer preparation times were associated with higher accuracy on novel tasks, both between-subjects and trial-by-trial. However, proactive control appeared to be more important for practiced tasks than previously observed, with a similar pattern to novel tasks observed between subjects. In examining reward incentive effects, we observed that larger rewards were associated with increased proactive control in terms of slower preparation times; however, this effect did not translate to general accuracy benefits on high-reward trials. Exploratory analyses suggest that this surprising result may be due to a more complex relationship between preparation time and accuracy than previously recognized, as subject- and trial-based variation in preparation time interacted in predicting accuracy outcomes. Together, our results highlight the key role of proactive control in the successful learning of new tasks, while also demonstrating that proactive control-related performance benefits may depend on crucial interactions between individual differences and trial-level demands.

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Published
2025-09-04
DOI
https://doi.org/10.31219/osf.io/4egtx_v2
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00

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article

Deconstructing Proactive Control and Reward Incentive Effects on Rapid Instructed Task Learning

Kimberly S. Chiew, Todd S. Braver, Rachel Elizabeth Brough, Michael W. Cole
Online Learning and Analytics
article

Deconstructing Proactive Control and Reward Incentive Effects on Rapid Instructed Task Learning

Kimberly S. Chiew, Todd S. Braver, Rachel Elizabeth Brough, Michael W. Cole
article en

Abstract

Rapid instructed task learning (RITL), the ability to quickly learn and implement a new task from instructions, is hypothesized to rely on proactive cognitive control. In three experiments, we examined self-paced preparation time as an index of proactive control during the performance of novel versus previously practiced tasks. We hypothesized that both between individuals and on a trial-by-trial basis, longer preparation times would be associated with improved performance on novel tasks. Furthermore, we predicted that incentivizing performance with monetary rewards would increase proactive control, as indexed by preparation times and improved task performance. Replicating Cole et al. (2018), we observed that longer preparation times were associated with higher accuracy on novel tasks, both between-subjects and trial-by-trial. However, proactive control appeared to be more important for practiced tasks than previously observed, with a similar pattern to novel tasks observed between subjects. In examining reward incentive effects, we observed that larger rewards were associated with increased proactive control in terms of slower preparation times; however, this effect did not translate to general accuracy benefits on high-reward trials. Exploratory analyses suggest that this surprising result may be due to a more complex relationship between preparation time and accuracy than previously recognized, as subject- and trial-based variation in preparation time interacted in predicting accuracy outcomes. Together, our results highlight the key role of proactive control in the successful learning of new tasks, while also demonstrating that proactive control-related performance benefits may depend on crucial interactions between individual differences and trial-level demands.

Washington University in St. Louis (US)
Multidisciplinary University Research Initiative, Office of Naval Research
Openalex Percentile: Top 73%
Online Learning and Analytics
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Deconstructing Proactive Control and Reward Incentive Effects on Rapid Instructed Task Learning — Kimberly S. Chiew, Todd S. Braver, et al. · (2025) | TGRS Research Map | TGRS