Promising Practices for Motivating and Engaging Kindergarten Writers Through Play-based Pedagogy: An Ethnographic Case Study
Bibliographic record
Abstract
The purpose of this qualitative, ethnographic case study was to gain an understanding of how teachers provide a play-based environment in kindergarten while simultaneously meeting curriculum expectations in writing in an authentic, integrated, and meaningful way. The overarching research question was How do two teachers, with a play-based pedagogical approach to learning, provide opportunities for students to become writers in kindergarten? The research, rooted in sociocultural theory and using a constructivist lens, demonstrated the importance of a collaborative approach to learning as well as ample time for children to talk and play which related to their interests. Methods included classroom observations, semi-structured interviews, and document analysis. Classroom observations included a purposeful sampling of seven children to investigate their lives as composers of writing in their play-based worlds. Document analysis involved examination of Ontario’s Kindergarten Program, relevant accompanying ministry documents, teachers’ resources, and children’s writing - inclusive of drawings, early stages of orthographic representation, and digital photos and videos documenting play stories. Two kindergarten teachers and one administrator were interviewed on their perspectives and beliefs of play-based learning in children’s developing literacy lives to triangulate data. The findings revealed that there were multiple affordances that led the student participants to choose writing as an activity in a classroom filled with options as well as to see writing as playful and fun. These affordances included 1) the honouring of student voices and interests, 2) collaboration among children, 3) a strong sense of classroom and school community, 4) powerful stories taught through playful pedagogy involving drama, 5) long blocks of uninterrupted play, and 6) an environment acting as the third teacher. The research showed that the school’s focus on professional learning through a collaborative approach was also a significant contributor to developing promising practices to teaching writing, while respecting and celebrating the importance and value of play in kindergarten. Finally, this research allowed moving from theory to practice, offering promising practices on how to develop and motivate children’s emergent and early writing skills in an authentic and meaningful way in a play-based kindergarten environment.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.016 | 0.013 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".