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26-11-2018 | Original Article

Can we learn to learn? The influence of procedural working-memory training on rapid instructed-task-learning

Auteurs: Maayan Pereg, Nitzan Shahar, Nachshon Meiran

Gepubliceerd in: Psychological Research | Uitgave 1/2019

Abstract

Humans have the unique ability to efficiently execute instructions that were never practiced beforehand. In this Rapid Instructed-Task-Learning, not-yet-executed novel rules are presumably held in procedural working-memory (WM), which is assumed to hold stimulus-to-response bindings. In this study, we employed a computerized-cognitive training protocol targeting procedural WM to test this assumption and to examine whether the ability to rapidly learn novel rules can itself be learned. 175 participants were randomly assigned to one of three groups: procedural WM training (involving task-switching and N-back elements, all with novel rules; Shahar and Meiran in PLoS One 10(3):e0119992, 2015), active-control training (adaptive visual-search task), and no-contact control. We examined participants’ rapid instructed-task-learning abilities before and after training, by administrating 55 novel choice tasks, and measuring their performance in the first two trials (where participants had no practice). While all participants showed shorter reaction-times in post vs. pretest, only participants in the procedural WM training group did not demonstrate an increased error rate at posttest. Evidence accumulation modelling suggested that this result stems from a reduction in decision threshold (the amount of evidence that needs to be gathered to reach a decision), which was more pronounced in the control groups; possibly accompanied by an increased drift-rate (the rate of evidence accumulation) only for the training group. Implication are discussed.

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Other transfer measures that were administered are reported in a different report (Shahar et al., 2018).

Paraphrasing Shahar et al. (2018)

We wish to thank the anonymous reviewer who has suggested this analysis.

The rationale behind this transformation is as follows. Individual differences in minimal RT are eliminated by replacing the individual’s minimal RT with the group-average of that value. Individual differences in the dispersion of values are eliminated, by the within-group standardizing of the discrepancy-from-the minimum. This standardization expands the dispersion for individuals whose RT dispersion is low (their SDRT is low) and similarly, shrinks the dispersion for individuals whose dispersion is high.

Given that the behavioral results did not show a decisive difference between the silent control group and the training group, we also ran Models 8 and 9. These models assume that the different group at posttest is the active training group. In Model 8, Δboundary was same for the training and silent groups but different for the active training, and in Model 9 both Δboundary and Δdrift-rate were different for active control relative to the other groups. Both these models did worse than Models 5 and 7 (BIC Model 8 = 1218.00; BIC Model 9 = 1223.27). These results suggest than indeed pooling the controls and contrasting them with the training group best fits the data.

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Titel: Can we learn to learn? The influence of procedural working-memory training on rapid instructed-task-learning
Auteurs: Maayan Pereg
Nitzan Shahar
Nachshon Meiran
Publicatiedatum: 26-11-2018
Uitgeverij: Springer Berlin Heidelberg
Gepubliceerd in: Psychological Research / Uitgave 1/2019
Print ISSN: 0340-0727
Elektronisch ISSN: 1430-2772
DOI: https://doi.org/10.1007/s00426-018-1122-4

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