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Record W2765838514 · doi:10.5430/jnep.v8n2p104

Renewal of an entry to practice baccalaureate nursing curriculum: Adapting to complexity

2017· article· en· W2765838514 on OpenAlexvenueno aff
Catherine Fetherston, Caroline Browne, Prue Andrus, Sharryn Batt

Bibliographic record

VenueJournal of Nursing Education and Practice · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsnot available
Fundersnot available
KeywordsBachelorCurriculumContext (archaeology)Process (computing)Adaptation (eye)Engineering ethicsReflection (computer programming)PedagogySociologyMedical educationComputer sciencePsychologyMedicineEngineeringPolitical science

Abstract

fetched live from OpenAlex

Curriculum re-design in entry to practice nursing degrees requires a rigorous and multifaceted approach to align the needs of students, professional and industry stakeholders, community needs, the faculty’s vision and university and regulator requirements. This paper relates the initial steps in the process taken to achieve this re-design in one Australian university’s Bachelor of Nursing program, and describes our experiences in two parts. The first part outlines the context in which the need for curriculum renewal was triggered and the ensuing processes undertaken in the development of our new course aim, course outcomes and graduate attributes. The second part discusses how undertaking these activities then came to influence the adoption of Complexity Thinking in the design of our conceptual model, which then guided our program structure and overarching learning and teaching approaches. We share these experiences to illustrate the steps we undertook on this journey, to outline and example the program we created, and to continue the scholarly discussions around the design of baccalaureate nursing program structures, especially those that implement pedagogies inspired by the concepts related to Complexity Theory. The choice of complexity thinking as a guiding theory was key in providing the lens through which we were inspired to graduate nurses with the skills to provide care in complex situations and value the learning that comes through uncertainty, reflection, adaptation and emergence.

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)0.009
metaresearch head score (Gemma)0.067
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.067
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0010.000
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 head0.362
GPT teacher head0.567
Teacher spread0.205 · 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 designOther design
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

Citations3
Published2017
Admission routes1
Has abstractyes

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