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Selective Attention in Cross-Situational Statistical Learning: Evidence From Eye Tracking

A growing set of data show that adults are quite good at accumulating statistical evidence across individually ambiguous learning contexts with multiple novel words and multiple novel objects (Yu and Smith, 2007; Fitneva and Christiansen, 2011; Kachergis et al., 2012; Yurovsky et al., under resubmis...

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Detalles Bibliográficos
Autores principales: Yu, Chen, Zhong, Yiwen, Fricker, Damian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3374955/
https://www.ncbi.nlm.nih.gov/pubmed/22712020
http://dx.doi.org/10.3389/fpsyg.2012.00148
Descripción
Sumario:A growing set of data show that adults are quite good at accumulating statistical evidence across individually ambiguous learning contexts with multiple novel words and multiple novel objects (Yu and Smith, 2007; Fitneva and Christiansen, 2011; Kachergis et al., 2012; Yurovsky et al., under resubmission); experimental studies also indicate that infants and young children do this kind of learning as well (Smith and Yu, 2008; Vouloumanos and Werker, 2009). The present study provides evidence for the operation of selective attention in the course of cross-situational learning with two main goals. The first was to show that selective attention is critical for the underlying mechanisms that support successful cross-situational learning. The second one was to test whether an associative mechanism with selective attention can explain momentary gaze data in cross-situational learning. Toward these goals, we collected eye movement data from participants when they engaged in a cross-situational statistical learning task. Various gaze patterns were extracted, analyzed and compared between strong learners who acquired more word-referent pairs through training, and average and weak learners who learned fewer pairs. Fine-grained behavioral patterns from gaze data reveal how learners control their attention after hearing a word, how they selectively attend to individual objects which compete for attention within a learning trial, and how statistical evidence is accumulated trial by trial, and integrated across words, across objects, and across word–object mappings. Taken together, those findings from eye movements provide new evidence on the real-time statistical learning mechanisms operating in the human cognitive system.