Exploring Collaboration between School-Based SLPs and Kindergarten Teachers: A Mixed Methods Study
Bibliographic record
Abstract
This mixed methods study explored the collaborative practices between school-based speech-language pathologists (SLPs) and general education kindergarten (K) teachers, with a focus on the factors that support or hinder interprofessional practice (IPP), specifically for students with speech-language impairment (SLI). Grounded in the pre-implementation stage of implementation science, the study investigated how self-efficacy, learning experiences, and resources influence collaboration. A convergent (QUANT-qual) parallel mixed methods design was employed, integrating quantitative survey data (N = 195) with qualitative responses from the 133 participants that answered open-ended prompts within the survey. Quantitative analyses revealed that K teachers reported significantly higher levels of collaboration and self-efficacy than SLPs. Self-efficacy emerged as a significant predictor of collaboration regardless of role. Hierarchical regression showed that resources accounted for nearly a quarter of the variance in collaboration. Qualitative findings confirmed and expanded upon the quantitative results. SLPs described collaboration as inconsistent and often hindered by structural barriers, including high caseloads, limited planning time, and lack of administrative support. In contrast, K teachers reported more embedded and routine collaborative experiences. Both groups emphasized the importance of mutual respect, shared goals, and communication. Participants with high self-efficacy described more proactive and confident engagement in collaboration, despite facing systemic limitations. Integration of the data revealed that while self-efficacy supports collaboration, it is insufficient without adequate systemic and structural support. The findings highlight the need for school and district leaders to prioritize collaborative infrastructure, including protected planning time, aligned professional development, and provision of resources. This study contributes to the literature by offering a nuanced understanding of school-based IPP and provides a roadmap for improving collaborative practices that support inclusive educational outcomes, particularly for students with SLI.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| 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".