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Individual Differences in Statistical Learning: Conceptual and Measurement Issues

机译:统计学习中的个体差异:概念和度量问题

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p class="p1"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. /p.
机译:class =“ p1”>已提出适应统计结构的能力(通常称为“统计学习”)在自然语言的习得和使用中起主要作用。最近的几项研究探索了统计学学习中的个体差异与语言结果之间的关系。这些研究产生的结果参差不齐,有些研究发现统计学习与语言结果之间存在显着关系,而另一些研究则发现结果微弱或无效。此外,少数使用多种统计学习量度的研究报告说它们没有相关性(例如[1])。当前的研究评估听觉统计细分的各种措施的可靠性,以及它们随时间变化的一致性。也就是说,统计学习测度之间观察到的通常较低的相关性是源于任务需求,测度的心理测量特性,还是统计学习可能是高度分散的构造这一事实?我们的结果证实了以前的报告,即统计学习的各个指标之间往往不相互关联,并且表明这些指标的可靠性较弱可能是低相关性的重要因素。我们的数据还表明,跨任务汇总性能可能是提高措施可靠性的一种途径。

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