Creating a Foundation for SoTL and Academic Advancement at Queen’s University
Bibliographic record
Abstract
Engagement in the scholarship of teaching and learning (SoTL) has become an increasingly important dimension of the work of teachers in higher education.An underlying reason is the academy's desire to create a climate where teaching is a visible and therefore valued activity, particularly as it relates to understanding and improving student learning (Huber, 2004).Supporting individual faculty members' initiatives thereby encouraging the development of communities of practice, is one strategy adopted to advance SoTL.A second strategy is to ensure that SoTL is well represented and promoted through institutional reward systems such as promotion polices (Bunton & Mallon, 2007;Feder & Madara, 2008; O'Meara, 2005;Simpson et al. 2004;Simpson et al, 2007).Indeed, it is suggested that institution-wide strategies are critical to creating an organizational culture in which individual faculty initiatives focusing on SoTL can flourish (Gallos, 2008).In this article we document one university's development of an infrastructure to support faculty wishing to engage in SoTL.We then examine the extent to which the institution-wide process for academic promotion encourages advancement through SoTL.This is accomplished by examining how department heads represent SoTL as a viable pathway for academic advancement.Preliminary results indicate a high degree of variation amongst department heads with respect to their understanding and support of the possibility of academic advancement through SoTL.It is argued that this lack of consistency contributes to "cultural inertia".Cultural inertia exists when there is a disconnect between the institutional intention to value SoTL versus the actual practice of academic promotion (Simpson et al, 2007).
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.009 |
| Scholarly communication | 0.016 | 0.003 |
| Open science | 0.001 | 0.021 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".