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Record W2228659763 · doi:10.21225/d5qw3q

An Examination of Interprofessional Team Functioning in a BScN Blended Learning Program: Implications for Accessible Distance-Based Nursing Education Programs

2016· article· en· W2228659763 on OpenAlexaffvenue
Lorraine Mary Carter, Bev Beattie, Wenda Caswell, Scott Fitzgerald, Behdin Nowrouzi‐Kia

Bibliographic record

VenueCanadian Journal of University Continuing Education · 2016
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsNipissing UniversityLaurentian UniversityMcMaster University
Fundersnot available
KeywordsPracticumBachelorTeamworkNursingMedical educationCurriculumNurse educationDistance educationPsychologyMedicinePedagogy

Abstract

fetched live from OpenAlex

In this study, the perceptions and experiences of an interprofessional team responsible for the development and delivery of the Registered Practical Nurse (RPN) to Bachelor of Science in Nursing (BScN) Blended Learning Program at Nipissing University were examined. In this program, RPNs can acquire a BScN through distance-based part-time study, including online courses and clinical practicum. In three years, the program has grown from an initial intake of 60 students to a current enrolment of over 600 students (Fitzgerald, Beattie, Carter, & Caswell, 2014).The success of the program is attributed to three factors: a part-time curriculum that permits students to work as they study; partnerships with hospitals and other clinical facilities to support the nurse-learner’s clinical placements; and the performance of a highfunctioning interprofessional team. This study of teamwork will benefit nursing and adult learning educators as well as e-learning professionals involved in the development and delivery of flexible programs for working nurses.

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)0.000
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 score0.701
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.021
GPT teacher head0.371
Teacher spread0.351 · 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

Citations4
Published2016
Admission routes2
Has abstractyes

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