The Implementation of the National Professional Standard for K-12 Teachers, 2012 (NPST) at Regional and Local Level in China: A Case Study of Regional Teacher Professional Development Standards Implementation in Qingyang District, Chengdu, China
Bibliographic record
Abstract
The Ministry of Education of P. R. China published National Professional Standards for K-12 Teachers (NPST) in 2012. Guiding by the standards and the recommendations for its implementation, provincial and municipal governments across China have carried out education reforms, focusing on institution and mechanism innovation, in order to realize the regulation and guidance role of the national standards. This paper starts with recent educational reforms for implementing Qingyang District Teacher Professional Development Standards,2012(QDTPDS-2012) issued by Qingyang District, Chengdu, Sichuan Province, a model of successful education reform in southwest China, and continue to make a comparison of teachers’ awareness, influences on teachers and schools, and implementation process of NPST and QDTPDS-2012 in Qingyang District by means of delivering questionnaires in teachers and interviewing with local school authorities, teacher educators, and education researchers; especially focuses on implementation process and approaches of QDTPDS-2012. The survey shows that the core value and principles of NPST are embodied in QDTPDS-2012; and QDTPDS-2012, as regional teacher professional development standards, is much more practical and feasible than NPST. In light of these findings, some implementation principles of national teacher professional standards in China, such as unifying objectives, implementing regionally, clarifying standards, innovating curriculums, emphasizing practice, making operational planning, establishing supporting system and adopting multi-evaluation approaches, are proposed in this paper.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".