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Record W3147096403

3D 프린팅을 활용한 수업이 예비유아교사의 의사소통능력, 문제해결력, 창의적 인성에 미치는 영향

2019· article· ko· W3147096403 on OpenAlexvenueno aff
김현수, 성소영

Bibliographic record

VenueEarly childhood education · 2019
Typearticle
Languageko
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
Fundersnot available
Keywords3d modelComputer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

본 연구는 3D 프린팅을 활용한 수업이 예비유아교사의 의사소통능력, 문제해결력, 그리고 창의적 인성에 미치는 효과를 탐구하였다. 본 연구를 위해 3D 프린팅 기술을 활용한 수업이 고안되었으며, 2019년 9월부터 12월까지 실험집단을 대상으로 적용되었다. 자료분석 결과, 3D 프린팅 기술을 활용한 수업은 예비유아교사들의 의사소통능력, 문제해결력 그리고 창의적 인성에 긍정적인 영향을 미치는 것으로 나타났다. 이러한 연구결과는 예비유아교사들의 핵심역량을 증진할 수 있는 프로그램을 개발하는데 중요한 시사점을 제공할 것으로 사료된다.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.006
Scholarly communication0.0080.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.003

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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