Comparison of Postbaccalaureate and Baccalaureate Graduates’ Performance in First and Second Years of Dental School
Bibliographic record
Abstract
Postbaccalaureate programs help predental students strengthen their basic science knowledge and improve their study skills before applying or reapplying for dental school admission. A high percentage of postbac students are admitted to and graduate from dental schools, but gaining greater understanding of how well these students perform in key areas of the first two years' curriculum would be useful for the design of those programs. The aim of this study was to evaluate postbac dental students' performance in the D1 and D2 years at one U.S. dental school compared to dental students with a four-year baccalaureate degree only. Performance assessed was the students' dental school grades in basic science courses, in all D1 and D2 didactic courses, and on preclinical simulation lab practical exams. Didactic and practical scores were gathered anonymously for the Classes of 2013-18 at the College of Dental Medicine-Arizona (CDMA) at Midwestern University, where postbac students with master's degrees from the affiliated College of Health Sciences made up 6-19% of each class. The two cohorts chosen for comparison were students with baccalaureate degrees only and students with one-year Master of Arts degrees from the College of Health Sciences. The scores of these postbac dental students and their non-postbac peers were found to be comparable in the basic science courses. However, for all the didactic courses combined, the non-postbac cohort had significantly higher mean scores than the postbac cohort for the fall quarter 2 and winter quarter 2 in 2013-15 and all years combined. The practical scores for the two cohorts were not significantly different for any year. Overall, this study demonstrated that the MA program in the College of Health Sciences prepared the postbac students to compete on an equal level with the non-postbac students in the CDMA D1 and D2 curriculum.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".