Using UDL (Universal Design for Learning) to create inclusive science classrooms
Bibliographic record
Abstract
In this study, CHAT (Cultural-Historical Activity Theory) was adopted as a lens to understand teachers’ interpretations of UDL (Universal Design for Learning) principles and guidelines and how they informed teachers’ choice and appropriation of practical tools to create inclusive learning environments in science. CHAT is a conceptual framework that is being used in many disciplines to understand the complexities of human learning, while recognizing that human praxis is socially situated. Ethnographic case study methods were adopted to develop insight into the teachers’ work (12 K-9 teachers) as they adopted UDL. Teachers initially struggled with applying the framework to their planning and classroom practice, distinguishing between UDL and differentiating instruction, and selecting appropriate tools to make their classroom learning environments inclusive. A range of tools were adopted or adapted to help students to represent learning in multiple ways and to engage the interest of learners.
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How this classification was reachedexpand
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".