Development of Participative Management System in Learning Environment Management for Small Sized Primary Schools
Bibliographic record
Abstract
The research aimed to: 1) study the factors of a participative management system in learning environment management, 2) study the current situation, desirable outcomes, and further needs for developing a participative management system in learning management, 3) develop a working participative management system, and 4) assess the system’s viability by studying the findings from usage of the system in the context of a small sized primary school. Research and Development process was implemented by analyzing the documents, theoretical approaches and related research literature. Then, the chosen factors used in the system were investigated by seven experts. The current situation, desirable outcomes, and further needs for developing a participative management system in learning environment management for small sized primary schools were studied by using a questionnaire that asked participants for their opinions, measuring using a 5-point Likert scale. Data were analyzed by calculating the Mean, Standard Deviation, and (PNImodified). The development of the system was implemented by conducting field trip studies in schools recommended for their effective learning management system and use of best practices. The system was outlined, and the handbook was provided to implement the system. In addition, the propriety of both the proposed system and its handbook was investigated by nine experts. The results show that 21 sub-factors were considered in the development of the participative management system in learning environment management for small sized primary schools. These included six input factors, six process factors, seven product factors, and two feedback factors, each of which were assessed at the highest level of propriety by the panel of experts. The overall current situation was judged to be at a “Moderate” level of propriety, and the sense of desirable outcomes was assessed at the highest level of propriety. The needs for further development were ranked in order from high to low as follows: feedback factor, input factor, product factor, and process factor respectively. The system evaluative finding by experts found that in the overall propriety was assessed at the highest level. The standards of feasibility, propriety, utility, and system design were all rated at the highest level. In addition, the handbook for system implementation was also found to be at the highest level of propriety.
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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 | 0.027 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".