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Record W2095621918 · doi:10.1080/1350293x.2011.623534

Play, drawing and writing: a case study of Korean–Canadian young children

2011· article· en· W2095621918 on OpenAlexaboutno aff
Mi Song Kim

Bibliographic record

VenueEuropean Early Childhood Education Research Journal · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracyPsychologyMeaning (existential)SemioticsFeelingSociocultural evolutionContext (archaeology)Meaning-makingSocial semioticsQualitative researchSociocultural perspectivePedagogyEarly childhood educationDevelopmental psychologySocial psychologyLinguisticsSociology

Abstract

fetched live from OpenAlex

From a sociocultural approach to literacy, young children, including culturally and linguistically diverse (CLD) children, can be viewed as active meaning-makers through participation in everyday literacy practices. This theoretical emphasis on the importance of the social context requires teachers and caregivers not only to improve and co-create learning environments but also to consider how to make sense of children's drawings and other non-verbal modes embedded in literacy practices. Drawing on a Vygotskian perspective, this study explores how young children use drawings and other semiotic tools as important mediators through which they represent their experience, feeling and knowledge in terms of the process of meaning-making. Within a qualitative research framework, this study uses data collected during the lesson theme of ‘circle’ to understand how young culturally and linguistically diverse (CLD) learners' drawings serve as a psychological tool for understanding and representing important aspects of their own experiences in terms of social, cognitive, and affective aspects. Implications of this study are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.306
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2011
Admission routes1
Has abstractyes

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