The Professional Development of Rural ESL Instructors: Program Administrators’ and Instructors’ Views
Bibliographic record
Abstract
In this article, we report perceived professional development (PD) needs, interests, and challenges of ESL instructors in rural Alberta from the perspectives of instructors and administrators. We collected questionnaire responses from instructors who taught in programs offered in five rural locations with a large recent influx of newcomers requiring ESL instruction. This was followed by focus-group interviews with the instructors and individual interviews with their program administrators. The findings highlight the importance of PD designed to meet the specific needs of rural instructors and to facilitate effective ESL teaching and learning in their communities. We offer recommendations for designing PD for ESL programs. Dans cet article, nous évoquons les besoins, les intérêts et les défis en perfectionnement professionnel pour les enseignants d’ALS dans les régions rurales de l’Alberta tels qu’ils sont perçus par les enseignants et les administrateurs. Nous avons recueilli les réponses aux questionnaires complétés par des enseignants qui travaillaient dans des programmes d’ALS offerts dans cinq milieux ruraux ayant récemment reçu un important afflux de nouveaux arrivants. Par la suite, nous avons mené des entrevues auprès de groupes de consultation composés d’enseignants et des entrevues individuels auprès d’administrateurs de programmes. Les résultats soulignent l’importance du perfectionnement professionnel conçu pour répondre aux besoins spécifiques des enseignants ruraux et pour faciliter l’enseignement et l’apprentissage efficaces de l’ALS dans leurs communautés. Nous offrons des recommandations portant sur la conception du perfectionnement professionnel dans le cadre de programmes d’ALS.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".