Developing a play‐based communication assessment through collaborative action research with teachers in northern Canadian indigenous communities
Bibliographic record
Abstract
Abstract With the goal of developing culturally appropriate approaches for assessing and supporting children's language use, teachers of 4‐to 6‐year‐old children in northern Canadian rural and Indigenous communities are involved in a 6‐year collaborative action research project. Teachers video record children's interactions during dramatic and construction play and then meet with university researchers to carry out inductive analyses of ways in which children use language to achieve social purposes. From these analyses, a Play‐based Communication Assessment has been created. Examples from two teachers' classrooms in one Indigenous community are used to show how play contexts and the still‐evolving play‐based communication assessment provide opportunities for teachers to recognise and build upon the linguistic and cultural resources that children bring to classrooms. Through the play‐based assessment and action research processes, teachers have come to recognise the richness of children's language when they are engaged in play and have gained understandings of their community's culture. Teachers and researchers are exploring ways to capture children's non‐verbal communication abilities through this assessment approach.
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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 | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 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 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".