Participation of a Student with Significant Disabilities in an Inclusive Classroom
Bibliographic record
Abstract
In British Columbia, students with significant disabilities are often included in general education classes with their peers. Being fully included means students participate in the social and academic life of the classroom (Katz, 2012), but many students with significant disabilities are not fully participating at school (Kurth, Morningstar, & Kozleski, 2014; Sokal & Katz, 2015). The present study used a qualitative case study design to explore how a student with significant disabilities participates in an inclusive classroom. Using the Canadian Model of Occupational Performance and Engagement (CMOP-E) as a theoretical framework, interactions between factors of the person, environment, and the activity were explored (Polatajko, Townsend, & Craik, 2007). Results of this study suggest key factors that influence participation include: (a) student’s ability to communicate; (b) classroom culture that respects diversity, fosters a sense of belonging and safety, and values personal and social responsibility; (c) access to adapted materials and Assistive Technology; (d) elements of Universal Design for Learning; (e) interactive learning; (f) weaving individualized learning outcomes into classroom activities and routines. Additional findings suggest that interactions of personal factors of all the members of the class influence participation, indicating the social environment must also be considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".