Abstract from the International Medical Education Conference 2007 (OA)
Bibliographic record
Abstract
Introduction: A new curriculum for undergraduate medical education has been introduced for all universities in Bangladesh since 2002.It is expected that this new curriculum will improve the qualitative level of medical education.According to this curriculum the assessment system for the students has also been modified.This new scheme gives more emphasis on certain evaluation procedures in written examination to be customized.For example, short essay questions (SEQ) are preferred to long descriptive and short answer questions (SAQ).Questions should be specificanswer oriented and targeted towards assessing the level of cognitive domain of the examinees.No study has been carried out about the state of orientation and implementation of the new curriculum in Bangladesh. Material and Methods:This study analyzed all new and old curriculum based written questions of the assessment examinations (except MCQ) for undergraduate Physiology course from 2001 to 2006, under 4 different universities in Bangladesh.In total 63 physiology question papers were included for evaluation.Data was statistically analyzed by "mean of percentage with SD", "Student's t-test" and "One way ANOVA", using SPSS software. Results and Discussion:The analysis indicates that there are significant improvement in type of questions (SEQ, SAQ and combined) and language (specific vs. non specific) field.However improvement in the fields of level of cognitive domain addressed (Recall, Understanding, Application, Combined -according to Bloom's taxonomy of educational objectives) was statistically insignificant.From this analysis it is indicated that, to get the desired benefits from the new curriculum for undergraduate medical education, proper orientation and implementation of the educators and evaluators are imperative.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.315 | 0.088 |
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".