Situations and Needs for Developing Desirable Characteristics of Students in the New Normal Era under the Secondary Educational Service Area Office Nakhon Phanom
Bibliographic record
Abstract
Desirable characteristics of students in the New Normal Era in educational institutions are important mechanism that will bring success and enhance student learning quality. This independent study aims to (1) study the current and desirable conditions in developing desirable characteristics of students in the New Normal. (2) To assess the need to develop desirable characteristics of students in the New Normal. This study’s sample consisted of 319 school administrators and teachers with the determination sample size using percentages selected by Stratified Random Sampling. The tools used in the study were (1) a questionnaire on current conditions in the development of desirable characteristics of students in the New Normal with the Index of item Congruence (IC) between .80 - 1.00, the discrimination between .46 - .73, and the reliability of .93; and (2) a questionnaire on the desirable conditions for the development of desirable characteristics of students in the New Normal of item Congruence (IC) between .80 - 1.00, the discrimination between .30-.89, and the reliability of .94. The statistics employed in data analysis were percentage, mean, and standard deviation, and the modified priority need assessment index (PNIModified). The results revealed that (1) The current condition in the development of the desirable characteristics of students in the New Normal era was at a high level and the overall desirable condition was at the highest level. (2) Necessary needs for the development of desirable characteristics of students in the New Normal. It was found that the aspects that were higher than the overall value were ordered in descending order of need. There are 2 aspects that are higher than the overall value, namely, the 4th aspect, creating innovation, equal to 0.385, and the 6th aspect, recognizing and appreciating oneself and others, equaling 0.363, respectively.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".