MétaCan
Menu
Back to cohort
Record W2335936233 · doi:10.1515/ijnes-2015-0031

Professional Development Needs of Novice Nursing Clinical Teachers: A Rapid Evidence Assessment

2016· article· en· W2335936233 on OpenAlexaff
Farah Jetha, Geertje Boschma, Marion Clauson

Bibliographic record

VenueInternational Journal of Nursing Education Scholarship · 2016
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of British Columbia HospitalUniversity of British ColumbiaBritish Columbia Institute of Technology
Fundersnot available
KeywordsProfessional developmentNursingNeeds assessmentMedicineNurse educationFaculty developmentMedical educationClinical PracticeQuality (philosophy)MEDLINEPsychologySociology

Abstract

fetched live from OpenAlex

The current nursing profession is challenged with a decreasing supply of competent clinical teachers due to several factors consequently impacting the quality of nursing education. To meet this demand, academic nursing programs are resorting to hiring expert nurses who may have little or no teaching experience. They need support during their transition from practice to teaching. Using the systematic approach of a Rapid Evidence Assessment (REA), scholarly literature was reviewed to identify existing professional development needs for novice clinical teachers as well as supportive strategies to aid the transition of experienced nurses into teaching practice. The REA included 29 relevant studies. Findings revealed three main professional development needs for novice clinical teachers and key supportive strategies. Based on these findings recommendations for best practices to support and prepare novice clinical teachers are presented.

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.167
GPT teacher head0.554
Teacher spread0.387 · 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

Citations44
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Nursing Education ScholarshipSame topicInnovations in Medical EducationFrench-language works237,207