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Record W1971040533 · doi:10.1055/s-0032-1311675

Reflection as a Window to Student Development: Insight for Faculty, Preceptors, and Mentors

2012· article· en· W1971040533 on OpenAlexaff
Stella Ng, Doreen J. Bartlett, S. Lucy

Bibliographic record

VenueSeminars in Hearing · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsWestern University
Fundersnot available
KeywordsPreceptorContext (archaeology)Grounded theoryReflection (computer programming)Professional developmentMedical educationPsychologyPedagogySocializationFaculty developmentMedicineQualitative researchSociologyDevelopmental psychologyComputer science

Abstract

fetched live from OpenAlex

This article is the third in a series of five articles explaining the grounded theory named RESPoND: Reflection in the Education and Socialization of Practitioners: Novice Development. Participants in the grounded theory study included a cohort of audiology students, clinical faculty, and preceptors. This particular article focuses on the first of three facets that together explain the role of reflection in novice development, in the context of the RESPoND theory. This facet represents the concept of reflection as a window—for faculty, preceptor, and mentor insight—into student and novice development. The notion of reflection as a professional development approach or mechanism for learners or professional practitioners is well documented. However, there is a lack of theorization about how reflection by health professional students may present opportunities for their faculty, preceptors, and mentors to improve their educational approaches. Findings are discussed in the context of implications for audiology education. We acknowledge that these findings relate specifically to the participant cohort; however, the understanding gained from this research may nonetheless be informative to a wide audience of individuals interested in audiology education.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.102
GPT teacher head0.342
Teacher spread0.240 · 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 designNot applicable
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

Citations7
Published2012
Admission routes1
Has abstractyes

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