What Price Excellence in Learning and Teaching? Exploring the Costs and Benefits for Diverse Academic Staff Studying for a GCHE Supporting the SoTL
Bibliographic record
Abstract
In the wake of policy, technology, and ideological disruptions in Western higher education, it is in universities’ interests to improve the quality of their learning and teaching to meet changed expectations. In some countries, particularly anglophone countries such as Australia, Canada, New Zealand, and the United Kingdom, the medium for this improvement is often professional development of academic staff provided through a Graduate Certificate in Higher Education (GCHE). This paper presents mixed methods research conducted at an Australian University. It addresses the questions of how a GCHE contributes to teaching quality and the Scholarship of Teaching and Learning (SoTL) from the perspective of course participants and their educators in the context of a university wide strategy to promote a culture of excellence in learning and teaching. Data and analysis indicate significant benefits to academic staff, their students, and the host institution from completion of a GCHE. However, tensions around academic workloads, compulsion, and some contradictions in espoused educational values and managerialist impositions emerge in these advancements. The educators in the GCHE (academic developers) were sometimes caught in the crossfire. Their reflections on this experience are included in the data and analysis.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.012 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".