Comparing students as partners (SaP) in higher education in Australia and Japan
Bibliographic record
Abstract
Students as partners (SaP) is an approach which aims to include students and staff in partnership in a number of settings across higher education. This article is a comparative exploration of SaP in relation to universities in Australia and Japan, through the lens of Matthews’ (2017) five propositions for SaP. Published in 2017, the propositions articulate the transformative potential of genuine, agentic engagement between staff and students in partnership. SaP is well recognized as a teaching and learning strategy in Australian higher education, yet there are changing and evolving perspectives. While the concept of SaP is less widely known in Japan, actively involving and engaging students in their own learning is an approach that is acknowledged and encouraged. Through a collaborative examination of our respective contexts, we found that the value of SaP is retained across the two cultures, along with its potential to transform and enrich both higher education systems.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".