Teaching about Ethics through Socioscientific Issues in Physics and Chemistry: Teacher Candidatesâ Beliefs
Bibliographic record
Abstract
The purpose of this qualitative study was to identify and explain the origins of physics and chemistry teacher candidatesâ beliefs about teaching about ethics through socioscientific issues (SSI). This study utilized a series of in-depth interviews, while the participants (n ¼ 12) were enrolled in a 9-month teacher education program at an urban university in Canada. Our data analysis revealed that beliefs about teaching physics and chemistry using SSI derive from a complex web of fundamental beliefs exemplified by four archetypes representing the subject-specific identities of our teacher candidatesâModel Scientist/Engineer, Model Individual, Model Teacher, and Model Citizen. Furthermore, we found that the justification for belief change required by a particular teacher candidate depends on these subject discipline identities. Thus, the presence of each archetype in preservice classrooms has ramifications for the way a teacher educator should encourage his or her students to include SSI in their teaching.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".