Distributional learning on Mechanical Turk and effects of attentional shifts
DOI:
https://doi.org/10.3765/plsa.v2i0.4105Keywords:
distributional learning, Mechanical Turk, replicability, attentionAbstract
This study seeks to determine whether distributional learning can be replicated on an online platform like Mechanical Turk. In doing so, factors that may affect distributional learning, such as level of attention, participant age, and stimuli, are explored. It is found that even distributional learning, which requires making fine phonetic distinctions, can be replicated on Mechanical Turk, and that attention may nullify the effect of distributional learning.
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Published
2017-06-14
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Published by the LSA with permission of the author(s) under a CC BY 4.0 license.
How to Cite
Moeng, Emily. 2017. “Distributional Learning on Mechanical Turk and Effects of Attentional Shifts”. Proceedings of the Linguistic Society of America 2 (June): 48:1–15. https://doi.org/10.3765/plsa.v2i0.4105.