Manipulating attentional load in sequence learning through random number generation.
Bottom Line: This discrepancy probably results from the specific type of secondary task that is used.In a third experiment, we compared the effects of RNG and TC.Nevertheless, we failed to observe effects of the secondary task in subsequent sequence generation.
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.
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Mentions: Figure 2 (left panel) shows averageexclusion and inclusion scores for both conditions. It appears that moresequential elements were produced under inclusion than under exclusioninstructions and that participants in the RNG condition generally producedfewer sequential triplets than participants in the control condition. Thisfinding is confirmed by a two-way ANOVA with Instruction(exclusion/inclusion) as a within-subjects variable and Condition(Control/RNG) as a between-subjects variable in which both main effects weresignificant. The significant main effect of instruction type indicates thatinclusion scores are higher than exclusion scores (.44 vs. .38),F(1, 38) = 6.8, MSE = 0.076,p < .05, η2 .15. The main effect ofcondition was also significant: Participants in the RNG condition producedfewer sequential triplets than participants in the control conditionregardless of instruction type (.36 vs. .46), F(1, 38) =5.9, MSE = 0.172, p = .020,η2 .13. In contrast to our expectations, theInstruction × Condition interaction was not significant,F(1, 38) = 1.8, MSE = 0.0202,p = .18, η2 .04. In other words, thepattern of performance in the generation task did not differ between our twogroups of participants.
No MeSH data available.