Finding New Paths: Leveraging the Scholarship of Teaching and Learning for Enhanced Librarianship
Bibliographic record
Abstract
The Scholarship of Teaching and Learning (SoTL) can offer new ways for librarians to consider and study our practice, suggest new partners in classroom-based research, provide new opportunities for dissemination, and lead to better integration of our work and expertise within academia. There are strong parallels between SoTL and information literacy (IL) research and the fields have much to offer each other. The SoTL literature offers a broad range of discipline-based methods that may spark ideas for investigating student learning and research that can inform our teaching. The presenters will review SoTL basics, and ask participants to scan recent SoTL research and discuss ways to adapt ideas from these studies to their own teaching and research work. We will conclude by sharing ideas on how librarians can get started in their own SoTL work or partner with other faculty who are conducting pedagogical research.
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 | 0.033 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.034 | 0.055 |
| Open science | 0.004 | 0.049 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".