Implementation of a Differentiated Instruction Initiative: Perspectives of Leaders
Bibliographic record
Abstract
Differentiated Instruction (DI) is a framework that supports planning for diversity within K-12 classrooms. Research has grown steadily over the past 15 years that explores DI implementation, as well as beliefs and practices. Literature to date has focused heavily on the experiences of educators, with limited attention given to the role of leadership in implementing DI in schools. The current study explores the perspectives of 19 school and board-level administrators regarding the ways in which a differentiated instruction framework was implemented within their school board as well as facilitators and barriers to the implementation and uptake of the framework. Interviews revealed five themes: a) DI continuum, b) differentiated professional learning supports, c) making space for shared professional learning, d) align/integrate/embed, and e) multi-level leadership. Our findings reflect a strong belief system of most of the participants with respect to the foundations of DI as well as an understanding of effective approaches to professional learning and school change.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.007 |
| 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".