Co-Teaching in Language Arts: Supporting Students with Learning Disabilities
Bibliographic record
Abstract
In this case study, I have examined teachers’ use of co ‐ teaching models to support students with learning disabilities in an inclusive elementary classroom. Co ‐ teachers progressed from the developmental stage of collegial growth to the compromising stage (Gately & Gately, 2001), but struggled to achieve the third stage of collaboration. Teachers used several methods to support students’ literacy: explicit prompt sheets, scaffolded mini ‐ lessons, and interactional inclusion. Classroom structures and helping routines played key roles in maintaining teachers’ availability to exceptional learners. The students with learning disabilities protected their social status in the classroom, a key factor in their decision to accept teachers’ help. Key words: collaborative practices, literacy learning, interactional inclusion, struggling learners. Dans cette etude de cas, l’auteure examine les modeles de coenseignement utilises en vue de venir en aide a des eleves du primaire ayant des difficultes d’apprentissage dans une classe inclusive. Les coenseignants ont progresse du stade initial de la collegialite au stade des compromis (Gately et Gately, 2001), mais ont eu de la difficulte a atteindre le troisieme stade, celui de la collaboration. Les enseignants ont employe plusieurs methodes pour soutenir les eleves dans leur apprentissage de la litteratie: feuilles de messages ‐ guides explicites, mini ‐ lecons avec soutien a l’apprentissage et inclusion faisant appel a des interactions. C’est principalement grâce aux structures des classes et aux methodes de soutien mises en place que les enseignants ont pu demeurer disponibles pour les eleves en difficulte. Ces eleves ont protege leur statut social en classe, ce qui a joue pour beaucoup dans leur decision d’accepter l’aide des enseignants. Mots cles : methodes de collaboration, apprentissage de la litteratie, inclusion par l’interaction, apprenants en difficulte.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".