Action Research as a Tool for Professional Development in the K-12 ELT Classroom
Bibliographic record
Abstract
Professional development in the K-12 English language teaching (ELT) classroom is an evolving entity that focuses on meeting the needs of changing demographics and latest educational trends. As a result, many texts have been published with the intention of providing the necessary skills educators need for success in their classrooms and to instruct a highly heterogeneous English for Speakers of Other Languages (ESOL) student population. Nonetheless, many of these resources focus on specific scenarios and instructional approaches that may not be applicable for all ESOL teachers. In this Perspectives article, I propose the incorporation of action research as a practice for K-12 teachers with the vision of empowering them to take control of their professional development and continue improving their instructional practices. Furthermore, I share three examples of how I have used action research in my own practice and the benefits obtained by my ESOL department, my ESOL students, and myself as a teacher researcher. Le perfectionnement professionnel dans les classes d’anglais du système d’éducation K-12 est une réalité changeante qui cherche à concilier les besoins de l’évolution démographique avec ceux des dernières tendances éducatives. De nombreux textes ont été publiés afin de procurer aux éducatrices et éducateurs les compétences nécessaires à leur réussite en classe, et également dans le but de renseigner une population étudiante hautement hétérogène dans le système d’enseignement de l’anglais à des apprenants étrangers (ESOL). Toutefois, plusieurs de ces sources mettent l’accent sur des scénarios spécifiques et des démarches pédagogiques qui peuvent ne pas convenir à toutes les enseignantes et tous les enseignants ESOL. Dans cet article de Perspectives, je recommande la pratique de la recherche-action aux enseignantes et enseignants du système d’éducation K-12 en vue de leur permettre de s’autonomiser pour prendre en main leur propre perfectionnement professionnel et continuer d’améliorer leurs pratiques pédagogiques. Je donne également trois exemples de la façon dont j’ai recouru à la recherche-action dans ma propre activité et des avantages qu’en ont tirés mon département ESOL, mes étudiantes et étudiants ESOL, et moi-même comme enseignant chercheur.
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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 | 0.174 | 0.106 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.023 | 0.017 |
| Open science | 0.006 | 0.023 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".