Assessing Dental Student and Faculty Views on the Transition to the Clinical Setting
Bibliographic record
Abstract
Introduction: Dental education reform has been a focus for many schools over recent years, particularly in light of the COVID-19 pandemic. The purpose of the presented study was to assess faculty and student preferences for feedback styles, learning modalities in the clinical setting, and transitioning from the preclinical to clinical environments.Methods: Two separate surveys were distributed to clinical faculty and students from classes of 2021, 2022, and 2023.Results: Notably, faculty had significantly more favorable views on interpersonal dynamics within the student clinic compared to students (p = 0.0255). While students and faculty differed in their views on the transition from preclinical to clinical practice, clinical performance, and teaching/learning modality preferences, these results were not statistically significant.Conclusion: Nevertheless, discrepancies in student and faculty responses to questions centering on feedback preferences, teaching/learning modality preferences, and transitioning to the clinical environment indicate potential avenues to explore for future development efforts.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".