Developing Teachers to Develop Students' 21st Century Skills
Bibliographic record
Abstract
The operation in the research project for developing teachers towards enhancing the 21stCentury skills of students was one of the research projects on 21st Century Skills. It was a research operation that was based on the advancement of digital technology and a knowledge-based society in the 21st Century. Various international perspectives on developing the 21st century skills of students, which had been presented by experts, were gathered utilizing Research and Development methodology, with the aim of creating educational innovations that can be used to empower teachers' learning and subsequently promote students' development. This approach transformed the old belief of "Knowledge is Power" into the idea that "Knowledge and Action are power." It is believed that if teachers learn, they will put their knowledge into practice in the classroom, which, in turn, will lead to more effective results for their students. The research project resulted in an educational innovation called the "Online Self-Training Program for Developing Teachers to develop their Students' 21st Century Skills," which had been previously evaluated by those teachers, who were stakeholders in this educational innovation and who had already passed the experimental research in the field. The innovation has been found to be effective in accordance with the specified criteria. Therefore, it is possible for this educational innovation to be disseminated so that the teachers’ skills can be developed in order to enhance their students' 21st Century Skills in secondary schools that are affiliated with the Basic Education Commission, which is the target group for the widespread dissemination of this research work.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".