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Record W7073575256

Kindergarten Children Demonstrating Numeracy Concepts through Drawings and Explanations: Intentional Teaching within Play-based Learning

2016· other· en· W7073575256 on OpenAlexaboutno aff

Bibliographic record

VenueAustralasian Journal of Paramedicine · 2016
Typeother
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsnot available
Fundersnot available
KeywordsNumeracyQuality (philosophy)Early childhood educationEarly childhoodTeaching methodComprehension
DOInot available

Abstract

fetched live from OpenAlex

Using both child-guided and adult-guided learning, Intentional Teaching in the early years can be a powerful tool for enhancing young children’s numeracy skills. As Epstein (2009) notes, this can include providing “opportunities for children to represent things by drawing, building and moving” (p. 47). This paper investigates how kindergarten (four-five year olds) children represented and demonstrated numeracy concepts through their drawings and explanations, completed for a research study that used arts-based strategies to enhance children’s environmental understanding. This research study involved kindergarten children in Australia creating and exchanging postcards (drawings and explanations) of their local environments with their peers in Canada. Findings include that the kindergarten children, through creating postcards of their physical environments and explanations, demonstrated their growing understanding of numeracy concepts, such as spatial orientation, quantification and attributes of objects. The study argues for quality Intentional Teaching and the development of an ‘early childhood numeracy progress monitoring framework’ that maps and assesses children’s mathematical development.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.682
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.343
Teacher spread0.322 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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