A Multiple Perspective Study of Specific Language Impairment and Verbal Communication: Exploring Perceptions of Collaborative Learning
Bibliographic record
Abstract
In Canada, a general education classroom teacher will encounter students with speech or language difficulties at some point in their teaching career. As children with disabilities and learning exceptionalities spend more time in inclusive classrooms, it is necessary for general education teachers to expand and modify their instructional and assessment practices as well as differentiate the learning environment to meet a broad range of abilities and needs. The goals of this study were to gain a deeper understanding of the challenges and barriers that students with specific language impairment (SLI) encounter during peer collaboration activities, as well as the supports and resources that enable students with SLI to successfully engage and participate in collaborative groupwork. This study utilized a phenomenological approach to explore the perspectives of teachers and speech-language pathologists. The first research question asked: what challenges and barriers do students with SLI encounter during peer collaborative activities in elementary classrooms? The analysis revealed three themes: skill development, impact of social dynamics, and reflections on COVID-19. The second research question posed in this study was: what supports and resources do students with SLI receive from teachers and speech-language pathologists to support verbal communication during collaborative learning? Four main themes were identified: Classroom practices, school and community support, classroom environment, and teacher reflection. Three key suggestions for practice are to develop strong relationships with stakeholders involved in the child’s learning, to provide opportunities for students to build communication skills in a supportive classroom environment, and to use best practices, such as UDL and DI to ensure students’ learning and communication needs are met.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".