Scaling Up a Kindergarten and Pre-K Curriculum with a Focus on Teacher Agency
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Early childhood curricula that achieve impressive results in small-scale studies often encounter difficulties scaling up those results across large systems. For example, it is often challenging to preserve both high-quality teacher-student relationships and high-fidelity scaled-up implementation. We describe experiences of a particular curriculum, Tools of the Mind (“Tools”), in grappling with this challenge. Tools is a pre-kindergarten and kindergarten curriculum emphasizing active teacher engagement supporting high-quality play and building school readiness; scale-up of Tools is thus a natural crucible for this implementation challenge. This report is a case discussion, intended to share experiences that may be of value to others facing similar challenges. We use the Active Implementation Frameworks (AIF) to analyze scaling strategies adopted by Tools as they evolved during implementation at scale. Sources for this analysis include our experience implementing Tools, formal and informal feedback we received in doing so, and separate studies by external researchers. We trace how Tools modified its approach to fidelity by integrating key elements of the AIF so that implementing the curriculum went hand-in-hand with building teacher capacity. This involved developing interactive technology that teachers use first directly, in the classroom, and then reflectively, to build their own understanding and self-agency. Results suggest that this strategy can enable teachers not only to implement the curriculum with fidelity, but also to develop their capacity to respond effectively to classroom demands. Based on these encouraging preliminary results, we recommend that researchers and educators more systematically explore connections between curriculum implementation, teacher capacity, and student outcomes.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it