Enhancing the Reading of Peer-Reviewed Research in the Teaching English as a Second Language Community
Bibliographic record
Abstract
Adult ESL instructors’ engagement with research can enhance instruction but is “a minority activity in our field” (Borg, 2010, p. 391). We explored instructors’ engagement with research; applied linguists’ and instructors’ conceptions of teacher-friendly, peer-reviewed research articles; and academics’ commitment to their dissemination. Twenty-three academics completed a survey; 8 adult ESL instructors read three articles, completed a questionnaire, and participated in a focus group interview. Despite a strong commitment to sharing their research with practitioners, academics in this study reported a number of constraints in their efforts to do so. We discuss differences in participants’ perspectives and provide suggestions for academics to enhance practitioners’ engagement with the research literature. Même si la lecture de travaux de recherche peut améliorer l’enseignement, peu d’enseignants d’ALS s’y mettent (Borg, 2010). Pour combler cette lacune, nous nous sommes penchés sur la question de l’implication des enseignants dans la recherche; les conceptions qu’ont les linguistes appliqués et les enseignants d’articles de recherche revus par les pairs et faciles à intégrer en salle de classe; et la mesure dans laquelle les chercheurs se préoccupaient de la diffusion de leur travail. Vingt-trois chercheurs ont complété un sondage, et huit enseignants d’ALS ont lu trois articles, complété un questionnaire et participé à une entrevue collective. Malgré un engagement ferme visant la diffusion de leur recherche parmi les praticiens, les chercheurs ont évoqué plusieurs obstacles qui limitaient leurs efforts. Nous discutons des différences dans les perspectives des participants et offrons des suggestions aux chercheurs voulant stimuler la lecture et l’intégration de leur recherche par les praticiens.
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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 | 0.150 | 0.288 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".