Design of Community-Based Transdisciplinary Learning for Social Studies Teachers in the Diverse School Contexts, Northern of Thailand
Bibliographic record
Abstract
The objectives of this study are: 1) to study problems and the needs in community-based transdisciplinary learning for social studies teachers in the diverse school contexts, Northern of Thailand 2) to develop and find the efficiency of handbook of community-based transdisciplinary learning for social studies teachers in the diverse school contexts, Northern of Thailand and 3) to examine the implementation results of the handbook. This research is based on the research foundation of a mixed method in education research. The population involved in this study included 1) educational connoisseurship of area-based who are selected by means of purposive sampling, from not less than 5 persons and 2) social studies teachers in the Northern-region provinces of Thailand who are selected by means of accidental sampling, from not less than 334 persons. The research instruments are: 1) a questionnaire on problems and the needs in community-based transdisciplinary learning 2) an appropriateness assessment form on the handbook and 3) an evaluation form of teacher professional competence in community-based transdisciplinary learning. The qualitative data are analyzed and shown on content analysis and descriptive analysis. The quantitative statistics employed for data analysis are mean and standard deviation through statistical program. The research findings revealed as follows; 1) Problems and the needs: teacher professional competence needs to be improved in community-based transdisciplinary learning through 7 skills, namely; Integrated learning Management, Technology Integrated Learning, Integrating Ethics Learning, Community Resource Management, Transdisciplinary Innovation Integrated Learning, Creative Educational Measurement Design, and Competency of Networking skill. 2) The result of handbook development: “SOCIAL Action Learning Model”, includes 6 steps, should be implemented in community-based transdisciplinary learning for social studies teachers. Due to the evaluation of the handbook, the result is at the highest level of appropriation (x = 4.58, S.D. = 0.57) 3) The result of handbook using: the handbook of community-based transdisciplinary learning for social studies teachers found the evaluation result at a high level (x = 3.96, S.D. = 0.89)
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".