The Decision-Making Skills of the Children Who Have Taken 1st and 2nd Grade Life Sciences Courses as Evaluated by Their Parents
Bibliographic record
Abstract
The purpose of this study is to investigate the Life Sciences course decision-making skill of the 3rd grade primaryschool students as evaluated by the parents. The study was conducted in screening model. The participants of thestudy were the parents (41 mothers and 26 fathers) of the students (32 girls, 35 boys) who study in the center of theprovince of Adıyaman in the academic year of 2017-2018. In order to collect the data, “decision-making skill level”survey form, which evaluates the decision-making gains of the 1st and 2nd grade Life Sciences course, was used.According to the findings, the decision-making skill of the students was 94.54 out of 120, which is “very good”. Thedecision-making skill levels of the students did not show a significant difference depending on the parent variable(mother or father), the students’ gender, or the school type attended (central or disadvantaged neighborhood).Depending on their success in school, however, there was a significant difference in their decision-making skilllevels; a positive correlation was detected between the decision-making skill and the success in school. Thedecision-making skill of the students did not show a significant difference depending on their self-confidence levelor their success in the Life Sciences course.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".