Evidence map›Paper›PMID 34213788›Full record

ArticleCognitive science2021

Cross-situational Learning From Ambiguous Egocentric Input Is a Continuous Process: Evidence Using the Human Simulation Paradigm.

Yayun Zhang, Daniel Yurovsky, Chen Yu

Abstract read
In one paragraph

Article in Cognitive science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The infant's view redefines the problem of referential uncertainty in early word learning.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yayun ZhangDepartment of Psychology, University of Texas, Austin.
Daniel YurovskyDepartment of Psychology, Carnegie Mellon University.
Chen YuDepartment of Psychology, University of Texas, Austin.

Funding

What you see is what you learn: Visual attention in statistical word learningR01HD093792 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI YU, CHEN · 2018 to 2022
$1.7M
Sensorimotor Dynamics of Parent-Child Interactions Build Word Learning SkillsR01HD074601 · NICHD · TRUSTEES OF INDIANA UNIVERSITY · PI YU, CHEN · 2013 to 2017
$1.6M
NICHD NIH HHS R01 HD074601NICHD NIH HHS R01 HD093792
6 · The paper itself

Abstract

Recent laboratory experiments have shown that both infant and adult learners can acquire word-referent mappings using cross-situational statistics. The vast majority of the work on this topic has used unfamiliar objects presented on neutral backgrounds as the visual contexts for word learning. However, these laboratory contexts are much different than the real-world contexts in which learning occurs. Thus, the feasibility of generalizing cross-situational learning beyond the laboratory is in question. Adapting the Human Simulation Paradigm, we conducted a series of experiments examining cross-situational learning from children's egocentric videos captured during naturalistic play. Focusing on individually ambiguous naming moments that naturally occur during toy play, we asked how statistical learning unfolds in real time through accumulating cross-situational statistics in naturalistic contexts. We found that even when learning situations were individually ambiguous, learners' performance gradually improved over time. This improvement was driven in part by learners' use of partial knowledge acquired from previous learning situations, even when they had not yet discovered correct word-object mappings. These results suggest that word learning is a continuous process by means of real-time information integration.

Indexed as

LanguageVerbal LearningAdultChildComputer SimulationHumansInfantKnowledgeLanguage DevelopmentCross-situational learningEarly language acquisitionStatistical learningWord learning

Identifiers

PMID34213788
PMCPMC8480200

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.