Open AccessIndividual Differences in Statistical Learning: Conceptual and Measurement Issues
Author(s) -
Lucy C. Erickson,
Michael P. Kaschak,
Erik D. Thiessen,
Cassie A. S. Berry
Publication year - 2016
Publication title -
collabra
Language(s) - English
Resource type - Journals
ISSN - 2376-6832
DOI - 10.1525/collabra.41
Subject(s) - statistical learning , reliability (semiconductor) , psychology , null hypothesis , statistical model , consistency (knowledge bases) , statistical hypothesis testing , cognitive psychology , construct validity , computer science , artificial intelligence , natural language processing , statistics , psychometrics , developmental psychology , mathematics , power (physics) , physics , quantum mechanics
The ability to adapt to statistical structure (often referred to as “statistical learning”) has been proposed to play a major role in the acquisition and use of natural languages. Several recent studies have explored the relationship between individual differences in statistical learning and language outcomes. These studies have produced mixed results, with some studies finding a significant relationship between statistical learning and language outcomes, and others finding weak or null results. Furthermore, the few studies that have used multiple measures of statistical learning have reported that they are not correlated (e.g., [1]). The current study assesses the reliability of various measures of auditory statistical segmentation, and their consistency over time. That is, do the generally low correlations observed between measures of statistical learning stem from task demands, the psychometric properties of the measures, or the fact that statistical learning may be a highly fragmented construct? Our results confirm previous reports that individual measures of statistical learning tend not to correlate with each other, and suggest that the somewhat weak reliability of the measures may be an important factor in the low correlations. Our data also suggest that aggregating performance across tasks may be an avenue for improving the reliability of the measures