Experimental Analysis of Competency-based Training for Paraprofessionals in Canadian Public Schools
Bibliographic record
Abstract
Behaviour analytic interventions are highly effective approaches for addressing the needs of individuals with autism spectrum disorder (ASD). However, despite its strong evidence base, applied behaviour analysis (ABA) is not commonly integrated into regular classrooms where a growing number of students receive instruction. In Canada, reliance on paraprofessionals to provide intervention, support, and direct instruction for students with ASD is widespread, yet paraprofessionals in public education report a lack of training to support students with challenging behaviour. Staff training in schools typically entails didactic workshops, producing brief behaviour change at best; in contrast, training using effective components such as modeling, role-play, and performance-based feedback produces positive gains. To prepare paraprofessionals to support students with behavioural needs, the current research utilized a randomized control design to examine the effectiveness of a competency-based program aligned with the BACB’s Registered Behaviour Technician (RBT) standards. Two training groups were offered in a single academic year and 30 paraprofessionals were randomly assigned to either Fall (treatment) or Winter (service as usual) groups. The paraprofessionals individually supported students with ASD, Grades K-3, with significant support requirements in language, socialization, and challenging behaviour. Data collection occurred across three time periods in the 10-month school year: baseline (Time 1); 4 months post-training (Time 2); and a 3-4-month follow-up for the treatment group only (Time 3). Classroom observations, structured interviews, and surveys were used to assess paraprofessional performance, student behaviour, and perceptions of student success and teamwork. Data were analyzed using a mixed ANOVA and revealed statistically significant group by time interaction effects (p < .05) for paraprofessional use of proactive and reactive strategies; student challenging behaviour; student cooperation with academic tasks; frequency of challenging routines; and paraprofessional ratings of student success. Probing of these interactions showed significant and substantial improvements for the treatment group, but not comparison group, from Time 1 to Time 2. Furthermore, a within-subjects ANOVA at Time 3 indicated maintenance of outcomes for all dependent variables for the treatment group. These findings provide strong support for the effectiveness and social acceptability of competency-based staff training models based on the principles of ABA in public schools.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 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) | 0.006 | 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".