Exploring the Use of Universal Design for Learning to Support In-Service Teachers in the Design of Socially-Just Blended Teaching Practices
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
This chapter examines the pivot to online and bended learning which occurred during the COVID health crisis and highlights how blended learning has emerged by far as the most popular and sustainable delivery option. The COVID pivot has also demonstrated, however, that blended learning too often ignores social inequities, and as a result allows them to become exacerbated. The chapter examines ways to support K-12 teachers as they seek to support social justice objectives within blended learning environments and suggests that universal design for learning can serve as a user-friendly and hands-on framework to address learner diversity in these innovative hybrid learning environments. The chapter further explores the repercussions this reflection has in relation to pre-service teacher training, in-service professional development, and leadership culture.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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