The Syllabus Is the System: Opportunities for UDL Integration in Course Design
Bibliographic record
Abstract
Universal Design for Learning (UDL) is an education design framework that emphasizes accessibility and learner agency. It has been receiving increasing attention in higher education from both teaching faculty and centers for improving teaching. Our mixed-methods study aimed to collect a rich dataset describing instructors’ perspectives on UDL while simultaneously analyzing artifacts that represent learners’ experiences in the instructors’ courses. We collected survey data and recent syllabi from 35 instructors from multiple countries. Our findings revealed significant interconnections among the domains of the UDL framework that many instructors expressed in a “humanizing pedagogy.” We drew from exemplar syllabi to illustrate how successful applications of UDL in syllabus design often resulted in the embracing and foregrounding of the humanity of both learners and instructors. Our research can provide a path for further study and potential applications for instructional practice by suggesting an essential, personal element present for many instructors who have successfully integrated UDL into their course design.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".