Investigating support for scholarship of teaching and learning; We need SoTL educational leaders
Bibliographic record
Abstract
In this paper, we focus on the experience of faculty learning to do the Scholarship of Teaching and Learning (SoTL). Our two studies uncovered similar threshold concepts in SoTL in two contrasting contexts; one study done in the United Kingdom with teaching-focused academics while the other study, done in North America, focussed on educational leaders at a research-intensive university. Both studies revealed similar ontological and epistemological transformations of learning and doing SoTL. Underpinning the results of these studies is the reality that educational leaders are situated within a complex cultural network of personal, professional, and financial tensions. There are two levels of institutional culture: university level and departmental level. But, institutional policies are only useful if also supported locally. This paper is of interest to those developing their expertise in supporting SoTL, as well as faculty on a teaching and scholarship career route.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".