Mobilize the School to Become a 21st-Century School
Bibliographic record
Abstract
The initiative to implement the "Mobilize Sarakulnawitaya School to Become a 21st-century School" project was part of a broader research program that aimed at improving education in the 21st Century by prioritizing active learning, integrating technology into learning, and by increasing the adoption of e-office solutions. The project was conducted using the Participatory Action Research (PAR) methodology, which involved a cyclical process of Planning, Acting, Observing, and Reflecting (PAOR), with two cycles scheduled to take place during the Academic Year of 2022. It was expected that the implementation of this project would result in the following outcomes: 1) improvement in both the research participants' practices and the school's performance as a 21st-century school by the defined focus areas; 2) learning from the actions taken at the individual, group, and school levels; and 3) the knowledge gained from the implemented actions, which could serve as a model for the continuous development of this school in the future. In this research project, there were 20 teachers, who participated as researchers, and 50 students, who were involved in the development process. The findings revealed the following outcomes: 1) there were significant improvements observed in both the research participants' practices and the school's performance as a 21st-century school, in accordance with the defined focus areas, after the completion of Cycle 1 and Cycle 2; 2) the research team, research participants, and Sarakulnawitaya school learned many aspects, particularly the importance of seeking new knowledge as a way to foster out-of-the-box thinking, which results in more efficient work practices; 3) the knowledge, gained from the implemented actions, demonstrated the cause-and-effect relationship between the driving forces that promoted change, the barriers that hindered it, and the strategies used to overcome those barriers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".