Medical Teaching Resources for Faculty Developers
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
Abstract This module is a collection of 40 video vignettes developed for use by faculty developers in a variety of settings. The vignettes depict effective and ineffective teaching methods. There is an accompanying resource manual with guiding questions and suggestions for how the vignettes may be used in training. While many of the video vignettes target those who train medical faculty, others may be used by those involved in training the learners at all educational levels. Each video has been kept deliberately short so that it can be used to quickly demonstrate a technique, or as a starter for discussions. Using these, participants may be asked to critically analyze good and not-so-good ways of teaching. This DVD is divided into four major categories: presentation skills, active learning strategies, small-group teaching, and clinical teaching. Each category has been further divided into specific teaching methods. Questions added under each of the categories, may be used to actively engage participants watching the videos. This resource has been used as part of the 2-day Teaching Improvement Project Systems (TIPS) workshops to train faculty and residents at the College of Medicine, University of Saskatchewan, Canada. TIPS is mandatory for all new faculty. All residents take TIPS in their first and second year of training. During TIPS, these videos are used to trigger discussions, as well as identify effective and ineffective teaching methods.
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 | 0.001 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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