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Record W4384401082 · doi:10.1515/ijnes-2022-0131

Engaging the creative heArts of nurse educators: a novel conceptual model

2023· article· en· W4384401082 on OpenAlexaff
Jackie A. Hartigan-Rogers, Paula d’Eon

Bibliographic record

VenueInternational Journal of Nursing Education Scholarship · 2023
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsThematic analysisNurse educatorConceptual frameworkThe artsNurse educationConceptual modelValue (mathematics)NursingQuality (philosophy)PedagogyPsychologyMedical educationMedicineSociologyComputer scienceQualitative researchPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: Nurse educators are increasingly challenged in preparing future nurses to be creative thinkers. The purpose of this innovative quality improvement initiative is to share nursing students' interpretations of the value arts-based pedagogy (ABP) brings to their nursing practice. METHODS: Braun and Clarke's approach to thematic analysis was utilized to identify and report patterns of ideas within learners' interpretations of engaging in an ABP assignment. RESULTS: The analysis of students' interpretations led to the creation of a novel conceptual model to encourage and support nurse educators in the use of innovative ABP approaches. CONCLUSIONS: ABP can be seamlessly integrated within teaching and learning methodologies to cultivate meaningful student learning. IMPLICATIONS FOR INTERNATIONAL AUDIENCE: The intent of the conceptual model is to encourage and support nurse educators in the use of innovative ABP approaches designed for engaging nursing students in active, creative, and challenging learning environments.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0060.036
Scholarly communication0.0160.014
Open science0.0030.009
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.100
GPT teacher head0.428
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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