Developing the Program to Strengthen Working Achievement Motivation Competencies of Welfare School’s Teachers
Bibliographic record
Abstract
This research aimed: 1) to investigate the components and indicators of working achievement motivation competencies of welfare school’s teachers; 2) to examine the needs to develop working achievement motivation competencies of welfare school’s teachers; and 3) to develop the program to strengthen working achievement motivation competencies of welfare school’s teachers. The mixed methods research was employed by divided into three phases. Phase one, investigated the components and indicators of the working achievement motivation competencies. Components and indicators were verified by 7 experts. Phase two, examined the needs to develop working achievement motivation competencies of welfare school’s teachers. The respondents were 340 welfare school’s teachers. Phase three, to develop the program to strengthen working achievement motivation competencies of welfare school’s teachers and verified the program by 9 experts. The research instruments were the components and indicators evaluation form, the existing and desirable situations questionnaire of working achievement motivation competencies, and the program evaluation form. Statistics used in analyzing data were mean, standard deviation and priority needs index modification. The research findings were: 1) The components and indicators of working achievement motivation competencies of welfare school’s teachers were categorized into 6 components and 32 indicators; 2) The needs to develop working achievement motivation competencies of welfare school’s teachers were ranked from high to low: creativity, performance commitment, performance evaluation, flexibility, the quest for information, and development of operational competence; and 3) The program to strengthen working achievement motivation competencies of welfare school’s teachers consisted of rationale, objectives, content, model and methods, 6 modules of program structure, and application and evaluation.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".