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Record W4408497653 · doi:10.5430/jnep.v15n5p1

Collaborative online international learning in pre-licensure nursing: A case study

2025· article· en· W4408497653 on OpenAlexvenueno aff
Terri W. Enslein, HE Moore, Rhea Goodwyn

Bibliographic record

VenueJournal of Nursing Education and Practice · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsnot available
Fundersnot available
KeywordsLicensureNursingOnline learningPsychologyMedical educationMedicineComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Background: Despite the many noted benefits of collaborative online international learning (COlL) projects, it has rarely been used in nursing education. Nursing curricula must employ multiple strategies to prepare graduates for professional practice. With COIL’s benefits, its application to nursing education should be explored.Methods: A qualitative case study approach guided by social constructivist theory was used to assess the impact of COIL on pre-licensure students' understanding of community/public health nursing, and the impact on preparedness for practice. 10 participants completed COIL projects and two surveys.Results: Three themes were identified: enhanced perspectives of public health issues/practices/interventions; enhanced knowledge; and broadened understanding of role and scope of practice. 10 participants noted an impact on preparation for professional practice. 7/10 demonstrated a difference in definitions of community/public health nursing.Conclusions: Further inclusion in pre-licensure curricula should be explored, particularly for its potential impact on preparation for professional practice.

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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.083
GPT teacher head0.541
Teacher spread0.458 · 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 designQualitative
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

Citations1
Published2025
Admission routes1
Has abstractyes

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