The Relation Between Students’ Theoretical Knowledge and Practical Skills in Endodontics: Retrospective Analysis
Bibliographic record
Abstract
BACKGROUND: Dental undergraduate students are required to show sufficient practical skills prior to treating patients. Practical skills and the underlying theoretical knowledge are taught in preclinical courses. Usually, the learning outcome is assessed in written multiple-choice examinations (theoretical knowledge) and practical skills tests. However, students' assessment of practical skills is more time consuming and prone to bias than objective multiple-choice examinations. OBJECTIVE: This study aims to analyze the relation between students' theoretical knowledge and practical skills in endodontics. Furthermore, the predictive validity of a theoretical knowledge assessment on students' practical skills was assessed. METHODS: Examination results from all students who participated in the preclinical phantom course in Operative Dentistry (sixth semester of the undergraduate dental curriculum in Germany) between the 2015 summer term and the 2022 summer term were retrospectively evaluated (N=447). The effects of age, sex, previous course participation, and theoretical knowledge on students' practical skills were assessed, using Pearson correlations, Wilcoxon rank sum tests, and a linear regression analysis. Subsequently, students' theoretical knowledge and practical skills were compared via a Fisher exact test to identify a suitable pass mark for students' theoretical knowledge that was associated with sufficient practical skills (≥60%). RESULTS: =.02; r=0.13). By using the current pass mark for theoretical knowledge (ie, 60%), a significant differentiation between insufficient practical skills (<60%) and sufficient practical skills (≥60%) was achieved (P=.02). However, for the discrimination between students with sufficient practical skills and students with insufficient practical skills, an adapted pass mark for theoretical knowledge would be more appropriate. The ideal pass mark amounted to 58% (P=.02). CONCLUSIONS: Students' practical skills and theoretical knowledge are significantly correlated. By objectively measuring students' theoretical knowledge, a rough estimation of students' practical skills (ie, a differentiation between sufficient and insufficient practical skills) is possible.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".