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Record W1989744356 · doi:10.2202/1548-923x.1263

The Power of Online Role-Play Simulations: Technology in Nursing Education

2007· article· en· W1989744356 on OpenAlexaff
Denise Nelson, Carol Blenkin

Bibliographic record

VenueInternational Journal of Nursing Education Scholarship · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsSaskatchewan Polytechnic
Fundersnot available
KeywordsNursingPower (physics)Nurse educationPublic healthMedicineMedical educationComputer sciencePsychologyPhysics

Abstract

fetched live from OpenAlex

The use and evaluation of an innovative Web-based technology and its suitability for promoting realism when interacting in clinical nursing situations are described. Also discussed are the development, implementation and evaluation of online role-play simulation. Student and faculty-centered insights are shared about the simulation and the technology supporting it. This Web-based learning experience validated literature review findings and offered new understanding about extended learning, projected realism, diversity, seriousness, non-verbal prompting, and evaluation. This simulation used the Fablusi platform in which students experienced the outcomes of their decisions and actions. This Web-based technology can be adapted for different student groups to enhance learning.

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)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.031
GPT teacher head0.463
Teacher spread0.432 · 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 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

Citations38
Published2007
Admission routes1
Has abstractyes

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