‘My Most Tricky Pickle!’ Balancing Reading Instruction in Play-Based Kindergarten: Educator Self-Efficacy Beliefs and Pedagogical Content Knowledge Needs
Bibliographic record
Abstract
Many kindergarten educators grapple with how best to teach reading in play-based kindergarten classrooms. The purpose of this mixed-methods study was to ascertain the instructional strengths and needs of kindergarten educators as they teach reading in play-based programs. Fifteen kindergarten teachers participated in an online questionnaire and focus group conversations that explored their concepts of self-efficacy and professional content knowledge to gain an understanding of the tensions these educators expressed, and to compare and confirm these with existing literature. Educators felt quite confident that they were effectively weaving foundational reading skills with learning opportunities into authentic experiences throughout the day. They indicated that balancing competing priorities within their programs was a challenge, and that supporting multilinguals and deepening their understanding of how to effectively build oral language and phonological awareness in their students were areas where they wanted to build their professional content knowledge.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".