Development of Faculty of Education of Northeastern University through Professional Learning Community Process
Bibliographic record
Abstract
The objectives of this research were 1) to study the present and the desirable condition of the Faculty of Education of Northeastern University, 2) to develop the faculty through PLC process, and 3) to assess the results. The study used PAR (Participatory Action Research) with the sample of selected groups of 6 administrators, 27 instructors, and 378 students with a total of 411 persons altogether. The research results were as follows: Regarding the present condition, the faculty has been traditionally embedded in family culture with the faculty vision of “Being a Professional Learning Community”, but, still, seriously underperformed in research work and English proficiency; therefore, the desirable condition was to have research work and English competency meet the national higher education standards that ultimately lead to being professionals. As for the results of the development of the faculty through PLC process and PAR, the research works of all staffs and students were nationally acceptable and published in the journals of TCI group 1 and 2 and looking forward to and now making good progress to international level. Over 85% of staffs and students passed the Common European Framework of Reference for Language test required by Thai Higher Education Commission. The development will be on-going and moving toward international level. In sum, the development of research work and English competency of the staffs and students in the Faculty of Education of Northeastern University through PLC process and PAR was academically and professionally effective. The study is rewarding.
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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 | 0.018 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".