Best of both worlds: Learner perspectives of inclusivity in a blended course
Bibliographic record
Abstract
Objective: Neurodiversity among learners and related learning needs requires educators to move beyond existing dominant forms of traditional didactic lecturing and rigid assessment methods to inclusive practices. To support neurodiverse learners, a first-year undergraduate nursing course adopted a blended delivery model in the Fall 2022 and 2023 semesters, integrating Universal Design for Learning (UDL) principles through synchronous and asynchronous instructional strategies.  Methods: In this convergent mixed methods descriptive case study, researchers explored how students rated and described their experiences with the UDL-based course design, using surveys (n = 39) and focus groups (n = 12).   Results: While survey and focus group interview findings generally aligned, some learners found the asynchronous weekly units less effective. Thematic analysis revealed five key themes: instructor accessibility and feedback; flexibility and choice; engagement and collaboration; relevant and relatable content; and the impact of stress and anxiety on learning. Although course modifications scored lowest in surveys, focus group participants appreciated instructor flexibility.  Conclusions: Overall, the blended UDL approach supported diverse learning needs. Future recommendations include balancing delivery formats and incorporating ongoing student feedback to enhance inclusivity and better support neurodiverse learner needs.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".