Trends in Basic Sciences Education in Dental Schools, 1999–2016
Bibliographic record
Abstract
The purpose of this study was to examine data published over the past two decades to identify trends in the basic sciences curriculum in dental education, provide an analysis of those trends, and compare them with trends in the basic sciences curriculum in medical education. Data published from the American Dental Association (ADA) Surveys of Dental Education, American Dental Education Association (ADEA) Surveys of Dental School Seniors, and two additional surveys were examined. In large part, survey data collected focused on the structure, content, and instructional strategies used in dental education: what was taught and how. Great variability was noted in the total clock hours of instruction and the clock hours of basic sciences instruction reported by dental schools. Moreover, the participation of medical schools in the basic sciences education of dental students appears to have decreased dramatically over the past decade. Although modest progress has been made in implementing some of the curriculum changes recommended in the 1995 Institute of Medicine report such as integrated basic and clinical sciences curricula, adoption of active learning methods, and closer engagement with medical and other health professions education programs, educational effectiveness studies needed to generate data to support evidence-based approaches to curriculum reform are lacking. Overall, trends in the basic sciences curriculum in medical education were similar to those for dental education. Potential drivers of curriculum change were identified, as was recent work in other fields that should encourage reconsideration of dentistry's approach to basic sciences education. This article was written as part of the project "Advancing Dental Education in the 21st Century."
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.011 | 0.021 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".