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Record W2410958719 · doi:10.3928/01484834-20070201-11

NursingQuest: Supporting an Analysis of Nursing Issues

2007· article· en· W2410958719 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Nursing Education · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsWebQuestAppealContext (archaeology)Nurse educatorProcess (computing)Computer scienceMedical educationKnowledge managementNurse educationPsychologyPedagogyMedicinePolitical science

Abstract

fetched live from OpenAlex

With the development and use of new strategies, practices, applications, and resources in technology, the teaching and learning context is shifting. Nurse educators are challenged to create instructional strategies that appeal to the newer generation of students and have the potential to enhance learning. Effective learning programs for these students require new digital communication skills, new pedagogies, and new practices. Nursing students should not be seeking the right answer as much as they should be seeking appropriate information and then developing approaches to issues or resolutions for problems. The focus of the teaching and learning context is shifting from the individual to the group, with the purpose of constructing new knowledge from available information. This article discusses the value of WebQuest activities as inquiry-oriented strategies and the process of adapting the WebQuest format for the development of a strategy called NursingQuest.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.787
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.091
GPT teacher head0.527
Teacher spread0.436 · 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