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Record W3042488068

유아의 즉지하기가 수학 패턴에 미치는 효과

2019· article· ko· W3042488068 on OpenAlexvenueno aff
서영민, 정혜린

Bibliographic record

VenueEarly childhood education · 2019
Typearticle
Languageko
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology
DOInot available

Abstract

fetched live from OpenAlex

이 연구는 유아 패턴이 수학 패턴에 영향을 미치는 효과를 알아보는데 목적이 있다. 서울과 경기도에 위치한 2 개의 사립 유치원에서 4 살과 5 살의 115 명의 아이들을 조사하였다. 이 연구는 일대일 인터뷰에서 유아의 즉지하기과 수학적 패턴을 조사했다. SPSS 20.0 프로그램을 사용하여 분석했다. 기술통계, t- 검정, Pearson의 상관 관계 및 다중 회귀 분석을 실시했다. 연구 결과는 첫째, 연령에 따라 세분화 및 수학적 패턴의 공간적 구조에 차이가 있었다. 둘째, 성별에 따른 차이는 보고되지 않았다. 그리고 세번째는 수학 패턴의 반복 패턴과 공간 구조 패턴에 영향을 미쳤다. 이 연구는 수 세기 전에 이전의 즉지하기의 영향을 알아 내려고 시도했음에 의의가 있다. 또한, 유아 교육 기관의 즉지하기 방법과 유아 수학 프로그램의 구성을 위한 기초 자료로 활용될 수 있을 것이다.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0030.010
Scholarly communication0.0100.007
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0200.005

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 head0.004
GPT teacher head0.198
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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