A Study of the Use of Picture Books by Preschool Educators in Outlying Islands of Taiwan
Bibliographic record
Abstract
The objectives of the study were to investigate the current status of applying picture books when teaching children and to also compare the differences in picture book teaching between teachers with different background variables and who are from Taiwan’s outlying islands. The researcher distributed 179 questionnaires, and after eliminating invalid questionnaires, 177 valid questionnaires were obtained, achieving a questionnaire efficiency of 98.88%. The quantitative data were analyzed by a t-test, ANOVA, Pearson Product Moment Correlation and Multiple Regression. The results were: 1. The overall status for picture book selection by early childhood educators was considered moderate to high. 2. The primary considerations for picture book selection were ‘theme’ and ‘adopting a child’s viewpoint’. 3. The overall status for the application of picture book teaching strategies among early childhood educators was considered moderate to high. 4. The application of picture book teaching strategies was centered on ‘strategies for the promotion of thinking and activities’ and ‘developing diverse abilities in children’. 5. There is a positive correlation and predictive power between selecting and using picture books by preschool educators.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".