Re-positioning SoTL toward the T-shaped Community
Bibliographic record
Abstract
Amongst a range of changes that have taken place within tertiary education, perhaps the most revolutionary has been a shift to student-centred approaches focused on life-long learning. Accompanying this approach to holistic higher education (HE) has been a growing interest in, and understanding of, the Scholarship of Teaching and Learning (SoTL). SoTL has, at its core, a deep concern with student learning and is therefore well-aligned with higher education’s renewed focus on its students. In this conceptual paper, we examine the impact of the T-shaped person which many tertiary institutions are operationalizing to inform and connect the development of students’ deep disciplinary knowledge with non-academic and employment readiness skills (such as communication, problem-solving, teamwork, and critical thinking). Importantly, we argue for a re-positioning of SoTL to complement and support this model, with SoTL as both the fulcrum and the fluid, multiple threads of discourse that are intricately entwined around the structure of the T-shaped model. We encourage our colleagues to strive to be T-shaped practitioners and we cast a vision of a T-shaped community. Here, all stakeholders within HE connect both their academic knowledge and holistic skills in collaborative ways to produce learners who flourish in modern society. The SoTL community plays a pivotal role in achieving this vision and is well-positioned to expand the current notion of SoTL toward a more holistic, interconnected, central role in HE.
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 | 0.026 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.017 | 0.074 |
| Scholarly communication | 0.024 | 0.024 |
| Open science | 0.003 | 0.034 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".