Understanding Educator Perceptions in Assessment of Kindergarten Children’s Development
Bibliographic record
Abstract
Race-related data are not routinely collected as part of the Canadian kindergarten teacher reported Early Development Instrument (EDI) data collection even though they could be used to inform provision of supports for students and educators. Therefore, the goal of our exploratory study was to gather an understanding of teacher perceptions regarding the assessment of items on the EDI in the context of children's race, gender, and family status and teacher positionality. We conducted a series of four focus groups with educators (kindergarten teachers and designated early childhood educators) from a school board in Ontario, Canada. The major themes identified were: (1) intersections of social identity; (2) systemic biases and preconceived expectations; (3) educator reflections on feelings, attitudes, and circumstances; (4) teacher-child-family relationships; and (5) teacher training, education, and administrative resources. Our findings suggest that educators' assessment may be influenced and informed by their perception of their own and their students' identity. Potential of a bias might be reduced by adequate training and education.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".