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Record W2809786566 · doi:10.23965/ajec.43.2.03

Young Children's Language uses during Play and Implications for Classroom Assessment

2018· article· en· W2809786566 on OpenAlexaffabout
Shelley Stagg Peterson, Nazila Eisazadeh, Shakina Rajendram, Christine Portier

Bibliographic record

VenueAustralasian Journal of Early Childhood · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIndigenousIndigenous languageFormative assessmentLanguage acquisitionPsychologyAction researchLanguage developmentProject commissioningPublishingPedagogyDevelopmental psychologyMathematics education

Abstract

fetched live from OpenAlex

THIS PAPER REPORTS ON research examining children's use of language in dramatic play and play with construction materials in kindergarten classrooms within three Indigenous and two non-Indigenous northern Canadian rural communities. Underpinned by sociolinguistic theory, the research involves inductive analysis of video-recorded interactions of five-year-old children during play. Participating children used language for 36 different purposes. Children's construction play talk often involved purposes within the categories of Language for learning and Language for own needs. Children often used language for purposes associated with the Language for learning and Language for imagining categories in dramatic play. As part of collaborative action research, teachers and researchers used these findings to develop a formative oral language observation tool. Using the tool, information gathered can inform practice and communication with parents and speech-language pathologists working with identified children.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

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

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 head0.025
GPT teacher head0.404
Teacher spread0.379 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations7
Published2018
Admission routes2
Has abstractyes

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