Teacher assistants in Canadian inclusive classrooms : an investigation into their deployment, preparedness, and impact
Bibliographic record
Abstract
Current trends in Canada and the world reflect a gradual increase in the utilization of Teacher Assistants (TAs; otherwise known as education assistants, learning support assistants, or paraprofessionals, hereafter TAs) in inclusive classrooms to support students with special educational needs. Due to the increased number of TAs in schools, teachers will likely encounter and work with TAs in their own classrooms and likewise, students are likely to be supported by them. Seemingly, the purpose of TAs is to provide support for students with special educational needs thereby increasing their academic achievement and social inclusion. However, research internationally has found that TA support is not always fulfilling this purpose; instead, increased TA support can lead to lower academic achievement and social exclusion for these students. Studies internationally have identified a number of factors as contributing to ineffective TA support. However, research on TA support in Canada is sparse. The current study employed an online survey within British Columbia completed by 329 TAs and 48 teachers to gain a better understanding of the roles of TAs from the perspective of teachers and TAs including, how prepared they are for their work, and the impact they are perceived to be making on student outcomes. Findings suggested that the TA’s role is ever changing and diverse, but most of their time is spent working one-to-one with students with special educational needs. They report that they are well-trained initially and have much experience, but lack ongoing professional development opportunities in areas such as instruction and decision-making about student work. Issues were raised throughout the study such as the lack of collaboration and communication between TAs and teachers and little respect, appreciation, and recognition for TAs. This research is one of the first in Canada on this topic and has provided insights into changes that can be made to how TAs are deployed and prepared in order to maximize their impact on student outcomes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".