Components and Indicators of Innovators Among Primary School Teachers
Bibliographic record
Abstract
The objectives of this study were: 1) to study the components and indicators of innovators in primary school teachers, and 2) to examine the consistency of the components model and indicators of innovators in primary school teachers with empirical data. The participants were 220 primary teachers under the Office of the Basic Education Commission in the Northeastern Region. The researcher determined the sample size based on a 20:1 ratio of the number of parameters and used a multi-stage random sampling. The research instrument was a questionnaire for developing elements and indicators of innovator in primary school teachers. The Item-Objective Congruence (IOC) index ranges from 0.80 to 1.00, the discriminatory power using Pearson Product-Moment Correlation ranges from 0.24 to 0.83, and the reliability of the entire instrument, as measured by Cronbach’s alpha coefficient (α), is 0.97. Data were analyzed using confirmatory factor analysis (CFA). The results revealed the following: 1) the elements and indicators of innovators in primary school teachers were identified through a synthesis of relevant documents and research, consisting of (1) initiative, (2) observation and asking questions, (3) interaction with others, (4) applying, and (5) adapting to the situation, with a total of 11 indicators. 2) The examination of the consistency of the components model and indicators of innovators in primary school teachers with empirical data found that (χ2) was equal to 15.073, the degrees of freedom (df) was equal to 22, the chi-square value is the correlation (χ2/df) is equal to 0.685. The statistical significance (p-value) was 0.859, and the goodness-of-fit index (GFI) was 0.988. The Relative Harmony Index (CFI) was equal to 1.000. The Harmonic Harmony Index (NFI) was equal to 0.985. The Root Mean Residual Index (RMR) was equal to 0.004. The square root of the mean square of the estimation (RMSEA) was equal to 0.000, indicating that this tool can be used to evaluate the innovators of primary school teachers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".