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Record W2795214154 · doi:10.36834/cmej.43351

Becoming a dentist: faculty perceptions of student experiences with threshold concepts in a Canadian dental program

2018· article· en· W2795214154 on OpenAlexaffvenueabout
Jacqueline Green, Kari Rasmussen

Bibliographic record

VenueCanadian Medical Education Journal · 2018
Typearticle
Languageen
FieldHealth Professions
TopicDental Education, Practice, Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCurriculumFocus groupPerceptionMedical educationQualitative researchPsychologyPerspective (graphical)Mathematics educationPedagogyMedicineDentistryComputer scienceSociology

Abstract

fetched live from OpenAlex

BACKGROUND: In each discipline, there are moments where students "get stuck" in their education and/or training and are often unable to move forward. These moments may be caused by threshold concepts as they represent a portal that students must cross in order to become successful in their chosen profession. This study investigated the threshold concepts from the instructors' perspective that students must navigate as they transform from learners to dentists within a dental program. METHODS: Two focus groups with faculty members within the School of Dentistry, University of Alberta were completed in the fall of 2017. Focus groups explored the faculty's perception of the students' transition from learner to dentist, difficult moments in the program, and the students' ability to navigate the program successfully. RESULTS: A qualitative phenomenographic analysis of the faculty focus group transcripts identified four potential threshold concepts within the dental program: 1) dealing with the whole patient, 2) accountability, 3) that you may not know everything, and 4) problem solving and adapting during practice. CONCLUSION: This study demonstrates that there are concepts within a dental program that faculty believe students must navigate in order to transition from learner to dentist. These concepts may inform curriculum design as well as other disciplines in the health sciences.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0640.000

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 head0.075
GPT teacher head0.554
Teacher spread0.479 · 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.

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

Citations6
Published2018
Admission routes3
Has abstractyes

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