Fostering Intercultural Inquiry in Subject-Area Curriculum Courses.
Bibliographic record
Abstract
This study investigates the infusion of intercultural inquiry into subject‐area curricu‐ lum courses in a teacher education program. Drawing from data that include ques‐ tionnaires, student assignments, and interviews, the research focuses on how student teachers responded to critical explorations of diversity within curriculum courses in second language education, early childhood education, and art education. The find‐ ings indicate that most student teachers had limited prior experiences with diversity, leading to anxiety and uncertainty about their preparedness to work in diverse class‐ rooms. Although many were receptive to intercultural inquiry and perceived its value, some resisted efforts to critically challenge social inequality and privilege. Key words: teacher education, diversity, multicultural education, intercultural inquiry Cet article porte sur l’intégration de la recherche interculturelle dans un programme de formation à l’enseignement. Puisant dans des données tirées entre autres de questionnai‐ res, de travaux d’étudiants et d’entrevues, les auteurs cherchent essentiellement à examiner comment des étudiants‐maîtres réagissent aux explorations critiques de la diversité dans des cours en enseignement d’une langue seconde, en éducation préscolaire et en éducation artistique. D’après les résultats obtenus, la plupart des étudiants‐maîtres avaient au départ peu d’expérience de la diversité ; ils se sentaient donc anxieux et peu sûrs d’eux par rap‐ port à la perspective de travailler dans des classes hétérogènes. Si certains voyaient d’un bon œil la recherche interculturelle et étaient conscients de sa valeur, d’autres se mon‐ traient réticents à défier de façon critique des inégalités et des privilèges sociaux. Mots clés : formation à l’enseignement, diversité, éducation multiculturelle, recherche interculturelle
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| 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".