"It changes the way you see yourself as a teacher". Turning the tide; can we use mentoring and coaching to better effect?
Bibliographic record
Abstract
Coaching and mentoring have a mixed presence in schools, existing on a spectrum of intent, quality and availability. Despite having the potential to be inherently rich educative practices coaching and mentoring of teachers sometimes falls short. This will be an exploratory session through which we will consider the lessons we might learn about the role of coaching and mentoring in supporting teachers to work confidently at all career stages. Evidence from a UCET sponsored study visit to Western Quebec, where their Teacher Induction Programme is the centre-piece of CPD, will be considered. This will be reflected on in relation to practices and policy in England. The premise is that if we can get coaching and mentoring right they might help turn the tide on teacher retention and self-efficacy and contribute to creating a more sustainable teaching profession. We will consider how this premise can be translated into real promise.
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 | 0.013 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.023 | 0.014 |
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".