Assessing four- and five-year old children’s play-based writing: use of a collaboratively-developed assessment tool
Bibliographic record
Abstract
In this study, we make the case for using texts children create as part of their play as a means for assessing their developing print literacy knowledge. We assessed 4- and 5-year-old children’s authentic texts using categories and criteria from the Assessing Young Children’s Marks/Drawing/Print tool, a research-based, classroom assessment we co-created with educators. We describe patterns we identified from our assessment of 104 texts the children created as part of their play within six themed centres in three kindergarten classrooms in a small northern town in Ontario, Canada. Overall, our assessment revealed the children’s understanding of spelling and the conventions of writing, and of writing as a social practice. However, since many texts were at the single word level, we were unable to determine the children’s understanding of conventions associated with more complex texts. We conclude by demonstrating how teachers might use the tool to assess children’s play-based texts.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".