Assessment of Higher Ordered Thinking in Medical Education: Multiple Choice Questions and Modified Essay Questions
Bibliographic record
Abstract
This article was migrated. The article was marked as recommended. Background: Multiple choice questions and Modified Essay Questions are two widely used methods of assessment in medical education. There is a lack of substantial evidence whether both forms of questions can assess higher ordered thinking or not. Objective: The objective of this paper is to assess the ability of a well-constructed Multiple-Choice Question (MCQ) to assess higher ordered thinking skills as compared to a Modified Essay Questions (MEQ) in medical education. Methods: The medical education literature was searched for articles related to comparison between multiple choice questions and modified essay questions, looking for credible evidence for using multiple choice questions for assessment of higher ordered thinking. Results and Conclusion: A well-structured MCQ has the capacity to assess higher ordered thinking and because of many other advantages that this format offers. Multiple choice questions should be considered as a preferable choice in undergraduate medical education as literature shows that different levels of Bloom's taxonomy can be assessed by this assessment format and its use for assessing only lower ordered thinking i.e. recall of knowledge, is not very convincing.
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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 | 0.020 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".