Exploring Preservice Teachers Engagement With Live Models of Universal Design for Learning and Blended Learning Course Delivery
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
Universal Design for Learning (UDL) and Blended Learning (BL) formats, are widely adopted across K–12 learning environments. Upon graduation, preservice teachers may be expected to implement UDL and BL practices. The present study was motivated by the need to provide preservice teachers with live modeling of UDL and BL concepts. Learning analytics data from 197 preservice teachers was examined for engagement with UDL/BL Access features (location, day-of-the-week, time-of-day, and regularity), Content features (screencasts and quizzes), and to determine if there was a relationship between engagement and achievement. Examination of the learning management system login data revealed regular access to the digital content across differing locations, week days, and time of day. Associations were significant between academic performance and all features. Designing the BL digital course components following UDL principles appears to have served as a self-regulation enabler for preservice teachers themselves while providing exemplars to adopt in their future practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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