Evaluating the quality of the educational environment for medical interns in an emergency department using the DREEM inventory.
Bibliographic record
Abstract
Moving toward establishing more student center educational environment to meet the ever-changing learning expectations in a challenging climate like emergency department for under graduates is an intimidating task. In our newly founded academic emergency department, every step toward scoring as a dynamic and modern educational environment for both undergraduates and postgraduates would be a great success. The last 18 months of undergraduate medical education in Iran is considered as an internship. Interns have two months mandatory emergency department rotation during that period. This study has design to evaluate the medical students' conception about the educational environment using the Dundee Ready Education Environment Measure (DREEM) questionnaire. 156 undergraduate interns during their two months emergency medicine rotation from October 2009 to March 2010 enrolled into a cross sectional observational study to anonymously fill up the DREEM questionnaire on the last week of the course. The overall mean score of DREEM questionnaire was 134.79 out of 200 for the emergency department. The mean scores are 135.37 in female (n=87) group and 131.56 in male (n=69) group. There was not any significant difference between two genders (P>0.05). A score of 134.79 is compatible with the modern universities. Scores of 100 or less indicate serious problems and scores above 170 is compatible with ultimate student centered and modern educational environment. Such an achievement in the start of the new installed Emergency Medicine program is admirable, hence great effort must be put to pinpoint problems and fix them. DREEM questionnaire helped us moving toward a more student center environment in the emergency department.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".