Promoting healthy food education for elementary school children at post Merapi eruption area of Cangkringan district, Yogyakarta, Indonesia: A quasi experimental study using ‘learning with fun’ approach
Bibliographic record
Abstract
Background : Knowledge and attitudes towards healthy food intake influence the growth and development of school-aged children. Cangkringan district of Yogyakarta, Indonesia was the worst area affected by the Mount Merapi eruption in 2010 and has a long-term consequence of less healthy food available for school-age children. This study aimed to determine the effect of health education to increase knowledge and attitudes towards healthy food intake for elementary school children at Cangkringan. Methods : Respondents of this study were 338 elementary school children (134 boys and 204 girls, ages between 8-10 years old) at Cangkringan. There were 20 elementary schools involved and participants were divided into 36 groups to make small groups of 6 to 8 students. Interventions of this study involved serial health education via ‘learning with fun’ approach using a student-centered learning method. The authors developed all tools and instruments based on the guidelines from The Food and Agriculture Organization (FAO). We analyzed the knowledge and attitude of the subjects after administering a pre and posttest using paired t-test and Wilcoxon range test. Results : The results showed significant increase of knowledge and attitudes towards healthy food intake ( p < .001 for both knowledge and attitude) of all subjects in this study. Conclusions : Health education using ‘learning with fun’ method may increase knowledge and attitudes of elementary school children. Furthermore, a series of cooking-classes as a student-centered learning approach, which emphasized contextual, collaborative and constructive methods of learning served well to increase motivation and satisfaction of the students to learn about healthy food.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".