The Development and Effects of a Teaching-Learning Model for Early Childhood Pre-service Teachers' Early Childhood Economic Education
Bibliographic record
Abstract
This study was conducted in order to understand theoretically the contents and methods of early childhood economic education for early childhood pre-service teachers, to develop an efficient teaching-learning model applicable in the field and test its effects, and to use the results as basic materials for qualitative improvement in education at teachers colleges. The subjects of this study were 54 students in the experimental group and another 54 in the control group sampled from D College and S College in a large-sized city in Korea. According to the results of this study, first, we developed a team project learning model for early childhood pre-service teachers early childhood economic education. Second, we applied the economic education teaching-learning model developed for early childhood pre-service teachers to the experimental group for 16 weeks, tested their economic education teaching efficacy, and obtained statistically significant results. Based on these results, we discussed the developed team project learning-teaching model and early childhood pre-service teachers economic education teaching efficacy.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".