Structured Quiz for Teaching of CVM Stages to the Undergraduate Orthodontic Students
Bibliographic record
Abstract
Introduction: There are several methods of teaching out of which didactic lectures and student centered lecturesa re commonly practiced all over the world in medical and dental schools. The aim of the study was to find out the impact of introducing structured quiz as a method for teaching of cervical vertebral maturation (CVM) stages to the undergraduate orthodontic students. Materials & Method: Current study was conducted on 30 undergraduate orthodontic students of final year. Duration of Study was 2018-19. Initial MCQs test was followed by the lecture and hands-on on quiz pattern and this was followed by the MCQs final-tests. The scores were calculated and presented in form of mean. Student paired t test was applied to compare the initial-test quiz scores with final-test quiz scores. Result: Results showed significant differences between initial-test and final-test which showed a significant improvement. Conclusion: The introduction of structured quiz as a method for teaching of cervical vertebral maturation (CVM) stages resulted in significant improvement in the knowledge of undergraduate orthodontic students.
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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 | 0.003 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".