Teachers’ Performance Motivation System in Thai Primary Schools
Bibliographic record
Abstract
This research aims to 1) study the present conditions and desirable condition of the motivation systems as well as how to find methods for motivating the performance of teachers in primary schools, 2) develop a motivation system for the performance of teachers in primary schools, 3) study the effects of using the motivation system for compliance with work of the teachers in primary schools by using research and development process. The research was consisted of three phases: Phase 1 the study of current conditions and desirable conditions of motivation system and methods for motivating the performance of teachers in the schools under the Office of Basic Education. Questionnaires were used to collect data from the sample which was consisted of 1,016 school administrators and teachers. Phase 2 development of motivation system for the performance of teachers in primary schools. The system was later validated by nine experts. Phase 3 results of the study on motivation system after implementation in a primary school. Data was collected from eight school administrators and teachers. Instruments in collecting data were: 1) questionnaire, 2) semi-structured interviews,3) evaluate form of operational level, 4) evaluation form of satisfaction. Statistical used in data analysis were percentage and standard deviation. The results showed that: 1) the current conditions of the motivation system for the performance of teachers by the input factor was at a moderate level, by the process factor was at a high level, and by the output factor was at a moderate level. As the desirable conditions, all three factors were at the highest level. 2) The motivation system for the performance of teachers in primary schools that the researchers have developed consists of six sub-systems, including: work-based motivation, award-based motivation, good communication, creating organizational relationship, environment in the workplace, workplace fairness. The input factors included: administrators, teachers, materials, and technology. Output included work performance standard and personal performance standard. 3) Results after the implementation of the system revealed that the teachers were motivated to perform at a high level and their preference for a motivation system was also at a high level.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".