Science and math teachers as Instructional Designers: Linking ID to the ethic of caring
Bibliographic record
Abstract
In this exploratory inquiry into the nature of the relationship between systematic instructional design models and teachers’ planning practices and needs, the researchers conducted open-ended interviews with six teachers of science and math in order to discover how they conceptualized and practiced instructional design. The most important finding to emerge from this research was that, from the teachers’ perspective, caring must be a central component of any instructional design activity. Regardless of gender and grades taught, the teachers indicated that they need to be able to make instructional decisions based upon their caring relationships with individual learners. Les enseignant de sciences et mathématiques comme concepteurs pédagogiques: relier l’identité et l'éthique de la sollicitude Résumé : Dans cette enquête exploratoire de la nature de la relation entre les modèles systématiques de conception pédagogique et les besoins ainsi que la pratique de planification des enseignants, les chercheures ont effectué des entrevues ouvertes avec six enseignants de sciences et mathématiques afin de découvrir leurs représentations et leurs pratiques de la conception pédagogique. Le résultat le plus important émergent de cette enquête a été que selon la perspective des enseignants, la sollicitude se doit d’être une des composantes centrales de n’importe quelle activité de conception pédagogique. Indépendamment du genre et du niveau d’enseignement, les enseignants ont indiqué qu’ils doivent être en mesure de pouvoir faire des décisions pédagogiques en fonction de leurs relations empathiques avec les apprenant individuels.
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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 | 0.027 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.009 | 0.028 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".