Morning Report Blog: A Web-Based Tool to Enhance Case-Based Learning
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
BACKGROUND: Morning report is an interactive case-based teaching session common to internal medicine training programs across North America. DESCRIPTION: We report here on a morning report web log ("blog"), created and updated after morning report sessions by the Chief Medical Resident with pertinent clinical topics, links to journal articles, and medical images. Trainees on their internal medicine rotation were e-mailed a web link with each posting. The aim was to enhance learning on clinical topics discussed at morning report by reinforcing topics and promoting further reading. EVALUATION: The educational impact of the blog was evaluated using detailed web metrics and surveys of attendees. The intended audience spent on average more than 5 min reading the blog and viewed more than 3 pages per visit. Almost half of attendees accessed the blog after completing their internal medicine rotation. The blog was also accessed by a global audience. Trainees rated the blogs a useful learning tool and cited it to be among the top 3 educational resources accessed during their rotation. CONCLUSIONS: In summary, a morning report blog was perceived by learners to be an effective complement to case-based teaching sessions. The combination of novel web metrics and survey data allowed for a multifaceted evaluation of the educational impact of the blog.
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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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