SLP-educator classroom collaboration: A review to inform reason-based practice
Bibliographic record
Abstract
Background and aims Increasingly, speech language pathologists are engaging in collaborative classroom services with teachers and other educators to support children with developmental language disorder and other communication impairments. Recent systematic reviews have provided a summary of only a small fraction of the available evidence and recommended the use of reason-based practice in the absence of a sufficient empirically driven evidence base. The purpose of this paper was to provide a broad (but critical) review of the existing evidence. Main contribution Papers were gathered through review of reference lists in the recent systematic reviews and other published works, as well as general internet searches. A total of 49 papers were identified either reporting empirical evidence pertaining to SLP-educator collaborative classroom activities, empirical evidence pertaining to consultative services, classroom instruction, or small group intervention in the classroom, or providing information, discussion, surveys, or reviews related to the topic. Evidence pertaining to vocabulary, oral language, phonological awareness, curriculum-based language, and written language were summarized together with qualifications based on elements of the research design. Conclusion and implications Although much of the evidence must be interpreted with considerable caution, the present review is informative for clinicians looking to adopt a reason-based approach to practice.
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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 | 0.013 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".