Project Independence: Training Educational Assistants to Work with Students with Disabilities in General Education Settings
Bibliographic record
Abstract
Project Independence (PI) is a 3-year professional learning intervention for Education Assistants (EAs) to learn and deploy evidence based practices (EBPs) that provide support to students with disabilities (SWD) in general education settings. Created in a school division in northwestern Alberta, PI was introduced to address perceived minimal EA preparation, variable student successes, and low levels of SWD independence after high school. Initially the project included strategies for students with autism, but later the scope broadened to include all SWD, modeled on the practice guidelines of the National Clearinghouse on Autism Evidence and Practice (NCAEP). During the first year, a district coach team completed needs assessments, developed a theory-driven implementation plan, and chose AFIRM modules to guide EBP instruction. In Years 2 and 3, PI provided a structured professional development plan for EAs at a participation test site and then expanded to four other sites. Training sessions occurred every six weeks focusing on the use of EBPs, data collection, and collaborative consultation with classroom teachers. Assessment feedback, conversation, and observation of staff practice hint at a greater EA confidence, declining incidents of student behavior, and greater use of inclusive, student focused strategies. Although there were challenges involving time, technology, and data, the project was able to show that targeted PD for EAs could improve outcomes for SWDs and school culture. Results highlight the importance of ongoing training, joint responsibility, and administrative commitment. The project moves forward in Years 4 and 5 by scaling implementation, enhancing communication, and reinforcing the infrastructure for fidelity, data use, and long-term sustainability.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".