Does Exposure to a Procedural Video Enhance Preclinical Dental Student Performance in Fixed Prosthodontics?
Bibliographic record
Abstract
To try to alleviate the issue of dental students having an inadequate field of view during live demonstrations of fixed prosthodontic preparations, an instructional video depicting the step-by-step procedures involved in an all-ceramic tooth preparation and provisional crown fabrication (practical exam 1, PE1) was created. Fifty-five second-year dental students were given a personal copy of the video after a lecture and an in-class viewing of the material. Throughout the course, students watched live demonstrations of tooth preparations and then practiced individually on mannequins. The scores achieved by the students on three practical exams (PE1, PE2, and PE3) were compared to those recorded by a class one year prior to the development of the video. The students exposed to the video performed significantly better on PE1 in comparison to the previous year's class, as well as compared to their own performance on the other two practical exams that had no supplementary teaching aids. A significant, moderate-level correlation was detected between exposure to the video and PE1. Ninety-six percent of the students reported on their end-of-year evaluation that the video helped them to prepare for PE1. The results of this study suggest that instructional videos may aid in the teaching of fixed prosthodontics.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".