From the Access Ramp To Equity and Quality: Alberta Teachers’ Experiences of Educating Deaf/Hard of Hearing Students
Bibliographic record
Abstract
This study examines the current state of education for Deaf/Hard of Hearing (DHH) students in Alberta, Canada, based on the perspectives and experiences of classroom teachers and Teachers of the Deaf/Hard of Hearing (TDHHs). The research was conducted in three phases: Phase 1 involved interviews, which informed the design of two survey instruments used in Phase 2. In Phase 3, participants helped corroborate and clarify data collected in the previous phases. The study was guided by Piper et al.’s (2006) theoretical framework of access, equity, and quality. The central research question was: What is the current state of education for students who are DHH in Alberta, from the perspectives and experiences of classroom teachers and TDHHs? The findings reveal that while general classroom teachers are welcoming and provide basic accommodations that support visual and auditory access to the classroom, they often have limited awareness of the specialized instructional needs of DHH students. TDHHs possess specialized expertise in assessment and instructional needs of DHH students, but have few opportunities to apply their knowledge with teachers or students. A dearth of qualified professional, paraprofessional support in classrooms and professional development opportunities in DHH Education hinder teachers’ ability to identify and address the specialized instructional needs of this low incidence, heterogenous student population. These challenges highlight the need for improved training, collaboration, and resource allocation to enhance educational outcomes for DHH students.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".