(Re)Considering the Scholarship of Learning: Inviting the Elephant in the Room to Tea
Bibliographic record
Abstract
This essay argues that the SoT(L) field has mistakenly equated learning solely to teaching and the teaching classroom, and has systematically ignored the other moments and opportunities within higher education institutes where learning and scholarly learning occurs—particularly within academic support and development programming. Therefore, we endeavour to discuss what we see as the elephant in the SoT(L) living room—learning, scholarly learning, and the Scholarship of Learning—and examine the ways in which learning and the Scholarship of Learning can be brought back into the SoT(L) discussion through an examination of academic support and development programming. Through the creation of a new theoretical and diagrammatic SoTL framework, this essay presents a more integrated, enhanced, and expanded understanding of the Scholarship of Teaching and Learning, and does so to further dialogue and to recognize the Scholarship of Learning as a strong and important contribution to the SoTL literature.
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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.038 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".