Children’s perspective-taking and decision-making on forests and land use
Bibliographic record
Abstract
Students' reasoning and decision making on complex socioscientific issues are critical for developing scientific literacy for 21st century citizenship. By incorporating a scenario-based approach, this study aims to understand the complexity of students' decision making on environmental issues: forests and land use. To help students grasp the context of these issues, we developed scenarios reflecting their experiences and understanding of forests within local communities. Through scenario-based surveys, students in Grade 5-6 science classrooms were encouraged to explore diverse stakeholders' perspectives and articulate their decisions regarding the scenarios. Additionally, students in focus groups participated in semi-structured discussions and interviews. The data collected from the surveys and students' dialogues were thematically analyzed. The study found that students prioritized environmental concerns, demonstrated skepticism toward politicians' perspectives, and emphasized righteousness in their decision making. These findings suggest that a holistic approach is essential to engage students' diverse perspectives in socioscientific and environmental problem solving. However, this also highlights the ongoing challenge of disciplinary boundaries within school curricula and pedagogical practices in science classrooms.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".