Integrating Socio-Scientific Issues to Enhance the Bioethical Decision-Making Skills of High School Students
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Scientific literacy has been focused on the construction of students’ knowledge to use appropriate and meaningful concepts, critically think, and make balanced, well-informed decisions relevant to their lives. This study presents the effects of integrating socio-scientific issues to enhance the bioethical decision-making skills of biology students. Using a quasi-experimental research design, results of the independent and related samples t-test on the pre- and posttest mean scores of 72 students significantly revealed that integrating socio-scientific issues in biology lessons are useful to enhance their bioethical decision-making skills. Moreover, as socio-scientific issues were integrated in their lessons, students’ classroom interactions and argumentations improved significantly and enabled them to give a positive, more elaborate, and in-depth responses with a wider range of explanations.
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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 | 0.003 | 0.028 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it