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Manipulating attentional load in sequence learning through random number generation.

Wierzchoń M, Gaillard V, Asanowicz D, Cleeremans A - Adv Cogn Psychol (2012)

Bottom Line: In a third experiment, we compared the effects of RNG and TC.Most importantly, our data suggest that RNG is more demanding and impairs learning to a greater extent than TC.Nevertheless, we failed to observe effects of the secondary task in subsequent sequence generation.

View Article: PubMed Central - PubMed

ABSTRACT
Implicit learning is often assumed to be an effortless process. However, some artificial grammar learning and sequence learning studies using dual tasks seem to suggest that attention is essential for implicit learning to occur. This discrepancy probably results from the specific type of secondary task that is used. Different secondary tasks may engage attentional resources differently and therefore may bias performance on the primary task in different ways. Here, we used a random number generation (RNG) task, which may allow for a closer monitoring of a participant's engagement in a secondary task than the popular secondary task in sequence learning studies: tone counting (TC). In the first two experiments, we investigated the interference associated with performing RNG concurrently with a serial reaction time (SRT) task. In a third experiment, we compared the effects of RNG and TC. In all three experiments, we directly evaluated participants' knowledge of the sequence with a subsequent sequence generation task. Sequence learning was consistently observed in all experiments, but was impaired under dual-task conditions. Most importantly, our data suggest that RNG is more demanding and impairs learning to a greater extent than TC. Nevertheless, we failed to observe effects of the secondary task in subsequent sequence generation. Our studies indicate that RNG is a promising task to explore the involvement of attention in the SRT task.

No MeSH data available.


Mean proportions of generated second-order conditional transitions(SOCs) that were part of the training sequence (i.e., meangeneration scores) under inclusion or exclusion instructions inExperiment 2. Error bars represent standard errors of the means.
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Figure 4: Mean proportions of generated second-order conditional transitions(SOCs) that were part of the training sequence (i.e., meangeneration scores) under inclusion or exclusion instructions inExperiment 2. Error bars represent standard errors of the means.

Mentions: Generation scores are presented in Figure4. The ANOVA with Instruction (inclusion/exclusion) as awithin-subjects variable and Condition (RNG/TC/control) as abetween-subjects variable yielded a significant main effect of instruction,F(1, 57) = 30.9, MSE = 0.251,p < .001,η2 .35; more sequentialelements were reproduced in the inclusion (.40) condition than in theexclusion condition (.30).3However, the Condition factor was not significant, F <1, nor was the Instruction × Condition interaction,F(2, 57) = 1.5, MSE = 0.013,p = .22, η2 .055.


Manipulating attentional load in sequence learning through random number generation.

Wierzchoń M, Gaillard V, Asanowicz D, Cleeremans A - Adv Cogn Psychol (2012)

Mean proportions of generated second-order conditional transitions(SOCs) that were part of the training sequence (i.e., meangeneration scores) under inclusion or exclusion instructions inExperiment 2. Error bars represent standard errors of the means.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376889&req=5

Figure 4: Mean proportions of generated second-order conditional transitions(SOCs) that were part of the training sequence (i.e., meangeneration scores) under inclusion or exclusion instructions inExperiment 2. Error bars represent standard errors of the means.
Mentions: Generation scores are presented in Figure4. The ANOVA with Instruction (inclusion/exclusion) as awithin-subjects variable and Condition (RNG/TC/control) as abetween-subjects variable yielded a significant main effect of instruction,F(1, 57) = 30.9, MSE = 0.251,p < .001,η2 .35; more sequentialelements were reproduced in the inclusion (.40) condition than in theexclusion condition (.30).3However, the Condition factor was not significant, F <1, nor was the Instruction × Condition interaction,F(2, 57) = 1.5, MSE = 0.013,p = .22, η2 .055.

Bottom Line: In a third experiment, we compared the effects of RNG and TC.Most importantly, our data suggest that RNG is more demanding and impairs learning to a greater extent than TC.Nevertheless, we failed to observe effects of the secondary task in subsequent sequence generation.

View Article: PubMed Central - PubMed

ABSTRACT
Implicit learning is often assumed to be an effortless process. However, some artificial grammar learning and sequence learning studies using dual tasks seem to suggest that attention is essential for implicit learning to occur. This discrepancy probably results from the specific type of secondary task that is used. Different secondary tasks may engage attentional resources differently and therefore may bias performance on the primary task in different ways. Here, we used a random number generation (RNG) task, which may allow for a closer monitoring of a participant's engagement in a secondary task than the popular secondary task in sequence learning studies: tone counting (TC). In the first two experiments, we investigated the interference associated with performing RNG concurrently with a serial reaction time (SRT) task. In a third experiment, we compared the effects of RNG and TC. In all three experiments, we directly evaluated participants' knowledge of the sequence with a subsequent sequence generation task. Sequence learning was consistently observed in all experiments, but was impaired under dual-task conditions. Most importantly, our data suggest that RNG is more demanding and impairs learning to a greater extent than TC. Nevertheless, we failed to observe effects of the secondary task in subsequent sequence generation. Our studies indicate that RNG is a promising task to explore the involvement of attention in the SRT task.

No MeSH data available.