Learning Management Development Model for Early Childhood Teachers
Bibliographic record
Abstract
The purpose of this research is to develop the learning management model of early childhood teachers in Roi Et Province. The sample group includes early childhood teachers is obtained by selecting a simple random sample of the sample 400 people. The tools used in the research include questionnaires assessment form and learning quizzes for Primary teachers. The statistics used in the data analysis include averages, standard deviations, and other factors and linear structural relationship analysis SEM. The results showed that: The development of learning management of early childhood teachers consists of: Teacher Professional Competency (CPT) Teacher Spirit (ST) Inspiration to have a public mind (PM) and learning management behavior (TBT). The element of inspiration to have a public spirit. (PM) It has a direct influence on learning management behavior (TBT) of early childhood teachers at the level of 0.01 with an influence value equal to 0.58. The elements of the model of inspiration for having a public spirit (PM) it has a direct influence on learning management behavior (TBT) of early childhood teachers can be 90.00% and can explain the variability of one other internal latent variable, namely: Inspiration to have a public spirit (PM) 88.00% of which can write structural equations.
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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 | 0.002 |
| 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 | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".