An Application of Project-Based Learning on the Development of Young Local Tour Guides on Tai Phuan’s Culture and Tourist Attractions in Sisatchanalai District, Sukhothai Province
Bibliographic record
Abstract
This paper presents an investigation of a research entitled, “ An Application of Project-based Learning on the Development of Young Local Tour Guides on Tai Phuan’s Culture and Tourist Attractions in Sisatchanalai District, Sukhothai Province. It was intended to develop young local tour guides on Tai Phuan’s culture and tourist attractions in Sisatchanalai, Sukhothai Province. The study explored the improvement in students’ communicative ability and examined to what extent the students revealed both positive and negative attitudes towards project-based learning. The study also aimed to develop a set of recommendations for future practice in project-based learning in Thai educational institutions. The research was conducted in classroom of 50 grade 10 students with purposive sampling of Muangchalieng School in Sisatchanalai, Sukhothai Province. The questionnaire aimed to evaluate the students’ satisfaction of the methodology called project-based learning in terms of their attitude in English language development and the practice of young local tour guides. A focus-group interview with each group provided in-depth information regarding their learning and provided ideas for a set of recommendations for future practice. It is anticipated that the information gained from this study will benefit both the teachers in their choices of suitable methodologies and students’ outcomes with the respect to improved competency in their skills in English and increased confidence in project-based learning in small groups.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".