AI Article Synopsis
- The study aimed to replicate findings from Endo and Takeda's research on implicit learning, focusing on how individuals select useful aspects of a structure during tasks.
- In Experiment 1, participants engaged in an induction task where they implicitly learned the most beneficial characteristics of the examples presented, including a highly predictive feature for some.
- Experiment 2 showed that while the prominence of certain features influenced participants' awareness, the primary factor for implicit learning was the usefulness of those features rather than their salience.
Article Abstract
In the contextual cueing paradigm, Endo and Takeda (in Percept Psychophys 66:293-302, 2004) provided evidence that implicit learning involves selection of the aspect of a structure that is most useful to one's task. The present study attempted to replicate this finding in artificial grammar learning to investigate whether or not implicit learning commonly involves such a selection. Participants in Experiment 1 were presented with an induction task that could be facilitated by several characteristics of the exemplars. For some participants, those characteristics included a perfectly predictive feature. The results suggested that the aspect of the structure that was most useful to the induction task was selected and learned implicitly. Experiment 2 provided evidence that, although salience affected participants' awareness of the perfectly predictive feature, selection for implicit learning was mainly based on usefulness.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808520 | PMC |
| http://dx.doi.org/10.1007/s00426-009-0227-1 | DOI Listing |
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