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In the Students’ Own Words: What Are the Strengths and Weaknesses of the Dental School Curriculum?

2007· article· en· W2153541793 on OpenAlexaboutno aff
David Henzi, Elaine Davis, Roma Jasinevicius, William D. Hendricson

Bibliographic record

VenueJournal of Dental Education · 2007
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumSWOT analysisMedical educationAccreditationStrengths and weaknessesPsychologyQuality (philosophy)PedagogyInternshipMedicine

Abstract

fetched live from OpenAlex

Dental students have little input into the selection of course topics and subject matter included in their dental curricula. Curriculum requirements are framed by the Commission on Dental Accreditation, which has stipulated competencies and associated biomedical and clinical knowledge that must be addressed during dental school. Although these competency requirements restrict the variance of educational experiences, students are eager to share their views on the curriculum within the realm of their educational experience. The objective of this research project was to elicit the perspectives of dental students from a broad cross-section of U.S. and Canadian dental schools about their education. A total of 605 students (285 sophomores, 220 seniors, 100 residents) from twenty North American dental schools completed a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis to communicate their perceptions of the curriculum. Students were also asked to provide their impressions of the overall quality of the educational program in an open-ended written format. The students' qualitative comments were then reviewed and categorized into key issues or themes. Resulting themes for each category of the Curriculum SWOT (C-SWOT) analysis were the following. Strengths: 1) clinical learning experience, and 2) opportunity to work with knowledgeable faculty. Weaknesses: 1) disorganized and inefficient clinical learning environment, 2) teaching and testing that focus on memorization, 3) poor quality instruction characterized by curricular disorganization, and 4) inconsistency among instructors during student evaluations. Opportunities: 1) develop strategies to provide students with more exposure to patients, especially early in the curriculum, and 2) opportunities to learn new technology/techniques. Threats: 1) cost of dental education, 2) students' concerns about faculty "brain drain," i.e., lack of sufficient numbers of dental faculty capable of providing high-quality instruction, and 3) questionable treatment of patients in the dental clinic as a consequence of pursuing procedural requirements. This report presents commentaries selected from 2,421 total responses that communicate students' perspectives related to C-SWOT themes. Students at seven schools in this study reported that they completed all or portions of the first two years of the curriculum in combined classes with medical students. Sophomore and senior students at these schools provided their thoughts on this curricular approach; these perceptions are also reported. Findings from this study are compared to results from a similar investigation of dental student perceptions conducted fifty years ago. We conclude that students participating in this study were positive overall about their learning experiences in dental schools, but identified several areas that appear to be problematic for many students at a variety of different schools including fundamental concerns about instructional quality in some areas of the curriculum. Academic program administrators in dental schools can use these findings to guide modifications that will enhance the overall dental education experience.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.356
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations268
Published2007
Admission routes1
Has abstractyes

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