Aplicación de un programa de técnicas de dibujo para desarrollar la creatividad en los niños de 4 años de edad de educacion inicial de la I.E. N° 253 "isabel honorio de lazarte" de la urb. La noria en el distito de trujillo
Bibliographic record
Abstract
This study set the main objective: To determine to what extent the program \ndrawing techniques develops the level of creativity in children 4 years old Early \nEducation of IE "Isabel Honorius Lazarte" in urbanization La Noria in the district of \nTrujillo in 2013, around the following hypothesis: If a program is properly executed \ndrawing techniques then significantly develop creativity in children 4 years of age \ninitial Education of IE "Isabel Honorius Lazarte" of Trujillo in 2013. \n \nThe sample consisted of 24 students, aged 4 years early education in "Fuchsia" IE \n"Isabel Honorius Lazarte” of Trujillo, the type of sample used is non-probability or \nintentional. Probabilistic not to the extent that researchers have been selected to \nthe sample following a series of relevant criteria. \n \nThe instrument was applied creativity test, developed by the authors research, \nvalidated by experts and tested for reliability. \n \nIt has been shown that the implementation of the technical drawing significantly \ndevelops creativity in children 4 years old Early Education EI "Isabel Honorio \nLazarte" of the La Noria in the district of Montreal, 2013; since, by applying \nstatistical tests significant differences between pretest and posttest results were \nfound.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".