Making Teaching Communal: Peer Mentoring through Teaching Squares
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Teaching can often seem like an independent endeavor, and seeking out ways to engage in dialogue and exchanges surrounding teaching can be beneficial. Opportunities to observe peers’ teaching and discuss teaching practices, challenges, and experiences with peers can lead to an increased sense of community, a fruitful exchange of ideas, and ultimately more thoughtful and effective teaching (Hendry and Oliver, 2012; Lemus-Martinez et al., 2021). One venue for such engagement is the teaching square, an exercise in which teachers observe each other’s teaching practice, typically with the goal of self-reflection of one’s own practice rather than evaluation of a peer performance. We suggest that even as the common philosophy behind teaching squares emphasizes self-reflection, they can also be catalysts for peer mentoring among participants. This article discusses teaching squares as a peer mentorship opportunity, drawing attention to the benefits of cultivating peer mentorship focused on teaching practices. We provide an account of our experience in undertaking a teaching square and the informal peer mentorship that resulted.
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.
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 | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.016 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it