Department-wide peer mentoring for teaching: assessing the impact of a new faculty professional development program in the department of biological sciences
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
Prioritizing faculty development around teaching and curricular design by establishing a peer mentoring community that addresses instructor needs and interests, can yield dual benefits – innovative learning environments for students and scaffolded educator growth. Emerging peer mentoring models highlight discussions to build a network of diverse perspectives, supports, and potential partnerships. We designed a department-wide, peer-mentored faculty development program focused on teaching, for colleagues across career stages, over the 2023–2024 academic year. We curated discussions based on participants’ needs and evaluated the impact of this faculty development program using surveys and interviews. Faculty uptake and satisfaction with the program was high; most reported that the sessions were helpful in adopting evidence-based teaching strategies to enhance student learning. Here, we outline the program and its impact, and offer recommendations to aid departments interested in implementing similar professional development initiatives.
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 | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it