Components and Indicators Framework of the Growth Mindset for Enhancing Learning Management of Teachers in the Primary Schools Under the Office of the Basic Education Commission
Bibliographic record
Abstract
This research aims to explore the components and indicators framework of the growth mindset for enhancing learning management and examines establish the alignment of the model and its indicators with empirical data for teachers in Primary schools. The study is divided into two steps; the first step involved the development of indicators for the growth mindset to enhance teachers’ learning management in Primary schools. This has involved a sample of nine experts in the field of the growth mindset using purposive sampling. The research instrument employed is a questionnaire with a 5-point rating scale consisting of 5 components and 21 indicators. The second step involved examining the components and indicators of the growth mindset for enhancing the learning management of teachers in Primary schools. The sample consisted of 433 teachers in Primary Schools by multi-stage random sampling. The research tool was a 70-item, 5-level closed-end rating scale questionnaire called the Growth Mindset Framework for teachers by collecting empirical data. The index of the discrimination indicators of 0.359 to 0.874 and the reliability of 0.979. The data analysis used descriptive statistics, Pearson correlation coefficients, and affirmative component analysis with Mplus 8.0. The results showed that A) There are 6 components and 21 indicators by synthesizing relevant papers and research. They have been assessed by 9 qualified experts suggesting that they are overall at the highest level. B) The results of the consistent examination of empirical data and models of components and indicators of the growth mindset for enhancing learning management among teachers in Primary schools were consistent. By using chi-square (x2) is equal to 33.927 at 41 degrees of freedom (df), the p-value is equal to 0.7753, the harmonization index (CFI) is 1.000, the TLI is 1.005, the average square quadratic index of estimated difference (RMSEA) is 0.000, the square root of the remaining squared mean in the form of a standard score (SRMR) is 0.036.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".