Universal Design for Learning Infusion in Online Higher Education
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 qualitative case study explored the development of online teaching capacity to incorporate the universal design for learning (UDL) framework in an online graduate program. The participants in the study were purposefully selected from multiple levels at a Canadian university: (1) the program level, (2) the faculty level, and (3) the institution level. Using a series of semi-structured interviews and document analysis, four themes were identified: (1) leadership, (2) community of practice, (3) educational development, and (4) challenges. In addition to highlighting the roles of academic leaders in fostering UDL adoption in online learning, the findings also revealed forms of support that need to be in place to increase online teaching capacity. The findings from the study provide valuable input toward setting the stage for UDL to be meaningfully adopted in an online learning setting.
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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 | 0.000 | 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 | 0.001 |
| 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