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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01wd375z760
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dc.contributor.advisorTurk-Browne, Nicholas-
dc.contributor.authorKlebanov, Rachel-
dc.date.accessioned2016-07-29T13:41:50Z-
dc.date.available2018-07-01T08:05:39Z-
dc.date.created2016-04-
dc.date.issued2016-07-29-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01wd375z760-
dc.description.abstractPrevious research on visual statistical learning has shown that people can learn patterns of visual information implicitly. However, are they able to express these patterns in a visual format, such as a simple grouping schematic or diagram, through an explicit retrieval grouping task? This experiment strives to evaluate participants’ ability to sort 12 novel abstract shapes into groups after previously seeing the shapes in a stream of spatial or temporal regularities. Despite the presence of a shape-rotation detection distractor task, participants were on average able to group the shapes in both spatial and temporal conditions, indicating that implicit learning occurred, and that overall, they were able to express the patterns in the novel explicit grouping task. In comparing performance between the two conditions, participants who viewed spatial regularities performed significantly better on the task. Overall, both temporal and spatial implicit learning are robust enough to be evaluated using the same explicit grouping task. Such visualizations, like the grouping diagram in this study, have the potential to become preferred formats for facilitating visual learning, and can pave the way for testing implicit visual statistical learning in an active manner.en_US
dc.format.extent68 pages*
dc.language.isoen_USen_US
dc.titleSpatial and Temporal Visual Statistical Learning Evaluated by an Explicit Sorting Tasken_US
dc.typePrinceton University Senior Theses-
pu.embargo.terms2018-07-01-
pu.date.classyear2016en_US
pu.departmentPsychologyen_US
pu.pdf.coverpageSeniorThesisCoverPage-
Appears in Collections:Psychology, 1930-2020

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