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Record W4416115036 · doi:10.17483/747vng22

An Innovative Approach to Adult Education in a Two-Year BScN Program: Creating Partnerships in Learning

2015· article· W4416115036 on OpenAlexaffvenueabout
Baiba Zarins, Lorraine Carter, Tammie McParland

Bibliographic record

VenueQuality Advancement in Nursing Education - Avancées en formation infirmière · 2015
Typearticle
Language
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsNipissing University
Fundersnot available
KeywordsGeneral partnershipExperiential learningApprenticeshipBachelorNarrativeNurse educationCognitive apprenticeshipReflective practiceAdult education

Abstract

fetched live from OpenAlex

In the program described in this paper, innovation in nursing education is presented as a response to specific tensions between academic and practice environments in the nursing field. As a unique partnership between a university in northern Ontario and three health care delivery organizations in a large urban environment, the Scholar Practitioner Program (SPP) is an accelerated two-year post degree leading to a Bachelor of Science in Nursing. Using narrative inquiry and cognitive apprentice pedagogies, SPP partners developed an experiential program in which students act as inquirers and co-creators as opposed to receivers of knowledge. Students are also immersed in practice settings throughout the program, supported by clinically based faculty, and connected, at all points, by communication and learning technologies. The benefits, challenges, and opportunities associated with this program from inception to the time of writing are presented for the reader's consideration. The purpose of this reflection on the SPP journey as it includes faculty, students, administrators, and other partners is to inspire others interested in advancing nursing education in Canada.

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)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.005
Scholarly communication0.0070.003
Open science0.0030.015
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.123
GPT teacher head0.492
Teacher spread0.368 · 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 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

Citations0
Published2015
Admission routes3
Has abstractyes

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