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Peekbank: An open, large-scale repository for developmental eye-tracking data of children’s word recognition

Author(s)
Zettersten, Martin; Yurovsky, Daniel; Xu, Tian L.; Uner, Sarp; Tsui, Angeline S. M.; Schneider, Rose M.; Saleh, Annissa N.; Meylan, Stephan C.; Marchman, Virginia A.; Mankewitz, Jessica; MacDonald, Kyle; Long, Bria; Lewis, Molly; Kachergis, George; ... Show more Show less
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Abstract
Abstract The ability to rapidly recognize words and link them to referents is central to children’s early language development. This ability, often called word recognition in the developmental literature, is typically studied in the looking-while-listening paradigm, which measures infants’ fixation on a target object (vs. a distractor) after hearing a target label. We present a large-scale, open database of infant and toddler eye-tracking data from looking-while-listening tasks. The goal of this effort is to address theoretical and methodological challenges in measuring vocabulary development. We first present how we created the database, its features and structure, and associated tools for processing and accessing infant eye-tracking datasets. Using these tools, we then work through two illustrative examples to show how researchers can use Peekbank to interrogate theoretical and methodological questions about children’s developing word recognition ability.
Date issued
2022-08-24
URI
https://hdl.handle.net/1721.1/152197
Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Publisher
Springer US
Citation
Zettersten, Martin, Yurovsky, Daniel, Xu, Tian L., Uner, Sarp, Tsui, Angeline S. M. et al. 2022. "Peekbank: An open, large-scale repository for developmental eye-tracking data of children’s word recognition."
Version: Author's final manuscript

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