Students’ Perceptions of Effective Classroom and Clinical Teaching in Dental and Dental Hygiene Education
Bibliographic record
Abstract
Effective teaching behaviors have been studied in various arenas in higher education. However, there is limited research documenting effective teaching behaviors in dentistry and dental hygiene. Our qualitative study attempts to define effective teaching in both the classroom and clinic for dentistry and dental hygiene students. A total of 175 dental and dental hygiene undergraduate students nominated a total of forty instructors for teaching awards, providing a total of 695 qualitative statements reflecting their teaching in two learning contexts: the classroom and the clinic. Seven categories of effective teaching qualities were identified: individual rapport, organization, enthusiasm, learning, group interaction, exams and assignments, and breadth. Based on the frequency of the themes, effective teaching in the classroom was best defined by organization and rapport, whereas in the clinic, rapport was the most frequently described behavior. Moreover, dentistry students perceived enthusiasm as an effective teaching quality more frequently than did dental hygiene students, whereas dental hygiene students provided more responses to learning. These findings can provide guidance in preparing undergraduate dental and dental hygiene educators to enter the teaching environment. The ultimate goal to be achieved from identification of effective teaching qualities, as determined in this study, is improvement in clinical and classroom teaching for dentistry and dental hygiene programs.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".