Development of a Training Manual for Reducing Use of Pesticides by Para Rubber Farmers at Bueng Khan Province, Thailand
Bibliographic record
Abstract
It is widely known that systematically developed training manuals can be used to improve knowledge and practical skills and promote positive attitude of trainees. This research thus aimed to develop a training manual to help reduce the use of pesticides by para rubber farmers in Nonkheng Sub-district, So Phisai District, Bueng Khan Province, Thailand. The research was divided in to 3 stages. The first stage investigated the scenarios in which pesticides were used of the para rubber famers while the second stage dealt with the development of a training manual for promoting the reduction of the use of pesticides and hazardous chemicals by the farmers. The final stage was the evaluation for the efficiency of the developed training manual by applying it with 48 volunteered para rubber famers for 2 days. The findings revealed that the training manual had an efficiency of index at 80.38/80.89. After training with the manual, the farmers’ levels of knowledge increased tal 67.40%, while the overall post-test scores on knowledge, attitude, and practice skills in reducing the use of pesticides were found to be significantly higher (p < 0.05) than those of the pre-test. It can be concluded that the developed training manual can be effectively used to improve the knowledge, attitude, and practical skills of the trainees.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".