Blended Learning And Lab Reform: Self-Paced Sotl And Reflecting On Student Learning
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
As part of a large exercise physiology laboratory (lab) reform project, we used blended learning to support graduate teaching assistants and lab technicians in developing their pedagogical knowledge and create an entry point to reflective conversations about teaching and learning. Because self-paced asynchronous online modules can enable reflective and self-determined learning, this asynchronous professional development course is punctuated with reflective questions for the instructional team preparing to teach reformed exercise physiology labs. Asynchronous course content was shared via short videos, podcasts, and readings. We debriefed this self-paced, SoTL-informed course together, in-person. This social debriefing kicked off our weekly synchronous reflective conversations about teaching and learning in a community of practice. Developing a shared language for talking about teaching, enabling student learning, practicing effective teaching, and beginning to contemplate teaching philosophies were described by graduate teaching assistants as notable aspects of this blended learning journey. Lab technicians described discovering SoTL and discussing learning challenges as helpful to their teaching.
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) | 0.001 | 0.001 |
| 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 | 0.005 |
| 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