Education Leaders’ Perspectives on Special Education Research: A Priority Setting Study
Bibliographic record
Abstract
Research priority setting, an element of knowledge mobilization, makes knowledge users integral to the development of research agendas. To date, the use of research priority setting in educational research has been minimal. The purpose of this study was to explore educational leaders’ perspectives on research priorities in special education. We conducted a cross-sectional research priority setting survey with educational leaders from 60 public school districts in British Columbia, Canada. Seventy-one participants completed the survey. Results of a pre-set list of questions indicated that the top three research priorities were: grade-to-grade transitions, high school graduation, and time to designation. In terms of designation, or student categorization, participants were most interested in “Intensive Behaviour Interventions/Severe Mental Illness.” When asked about other priorities, participants identified research on types of support/interventions. These results have implications for developing a research agenda that can support informed decision-making around policy-development and programming for students with special needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".