gaze-action-head-mounted-eye-tracking-children-s-dynamic-visual

Gaze in Action: Head-mounted Eye Tracking of Children's Dynamic Visual Attention During Naturalistic Behavior

Young children's visual environments are dynamic, changing moment-by-moment as children physically and visually explore spaces and objects and interact ...

Indiana University

Objects in the world usually have names at different hierarchical levels (e.g., beagle, dog, animal). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use co-occurrence information to learn hierarchical labels in contexts where the labels for individual objects and labels for categories were presented in completely separated blocks, in interleaved blocks, or mixed in the same trial. Temporal presentation schedules significantly affected the learning of individual object labels, but not the learning of category labels. Learners' subsequent generalization of category labels indicated sensitivity to the structure of statistical input.

Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics.

In the word-learning domain, both adults and young children are able to find the correct referent of a word from highly ambiguous contexts that involve many words and objects by computing distributional statistics across the co-occurrences of words and referents at multiple naming moments (Yu & Smith, 2007; Smith & Yu, 2008). However, there is still debate regarding how learners accumulate distributional information to learn object labels in natural learning environments, and what underlying learning mechanism learners are most likely to adopt. Using the Human Simulation Paradigm (Gillette, Gleitman, Gleitman & Lederer, 1999), we found that participants' learning performance gradually improved and that their ability to remember and carry over partial knowledge from past learning instances facilitated subsequent learning. These results support the statistical learning model that word learning is a continuous process.

Article	Year
Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics. Cognitive science\| PubMed ID: 28685848	2018
Statistical Word Learning is a Continuous Process: Evidence from the Human Simulation Paradigm. CogSci ... Annual Conference of the Cognitive Science Society. Cognitive Science Society (U.S.). Conference\| PubMed ID: 29226281	2015

Yayun Zhang

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