Transformation of Early Childhood Education: A Descriptive Quantitative Analysis of Critical Thinking Skill Development in Banten Province, Indonesia
Bibliographic record
Abstract
This study explores the perceptions of PAUD teachers in Lebak, Banten, about critical thinking skills in learning for children aged 4-6 years, learning strategies, and challenges faced. A descriptive quantitative approach was used with an open-ended questionnaire filled out by 131 teachers. Data were analyzed using descriptive statistics with presentation in the form of visual graphs. The results showed that teachers' understanding of critical thinking indicators varied, with 39.6% understanding critical thinking more as the ability to analyze, 14.4% as interpretation, 12.6% as evaluation, 8.2% as inference, 5.4% as explanation, and 4.5% as self-regulation. Teachers emphasized analysis and interpretation through interactive methods, while evaluation and inference were less applied. The novelty of this study lies in the mapping of teachers' understanding based on critical thinking indicators and their impact on learning strategies. Recommendations for training based on direct practice and reflection to improve the implementation of critical thinking evenly are contributions to the research results as well as being the basis for improving policies and developing teacher training in areas with low HDI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".