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Record W1977971711 · doi:10.2202/1548-923x.1095

An Inventory of Nursing Education Research

2005· article· en· W1977971711 on OpenAlexaff
Olive Yonge, Marjorie Anderson, Joanne Profetto‐McGrath, Joanne Olson, D. Lynn Skillen, Jeanette Boman, Ann Ranson Ratusz, Arnette Anderson, Linda Slater, Rene Day

Bibliographic record

VenueInternational Journal of Nursing Education Scholarship · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSample (material)Relevance (law)Nursing researchResearch designNursingNurse educationMedical educationPsychologyMedicineSociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

PURPOSE: To describe nursing education research literature in terms of quality, content areas under investigation, geographic location of the research, research designs utilized, sample sizes, instruments used to collect data, and funding sources. DESIGN AND METHODS: Quantitative and qualitative research literature published between January 1991 and December 2000 were identified and classified using an author-generated Relevance Tool. FINDINGS: 1286 articles were accepted and entered into the inventory, and an additional 22 were retained as references as they were either literature reviews or meta-analyses. Not surprisingly, 90% of nursing education research was generated in North America and Europe, the industrialised parts of the world. Of the total number of articles accepted into the inventory, 61% were quantitative research based. The bulk of the research was conducted within the confines of a course or within a program, with more than half based in educational settings. Sample sizes of the research conducted were diverse, with a bare majority using a sample between 50 and 99 participants. More than half of the studies used questionnaires to obtain data. Surprising, 80% of the research represented in these articles was not funded. The number of publications of nursing education research generated yearly stabilised at approximately 120 per year. CONCLUSION: Research programs on teaching and learning environments and practice in nursing education need to be developed. Lobbying is needed to increase funding for this type of research at national and international levels.

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.766
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.507
GPT teacher head0.685
Teacher spread0.178 · 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 designOther design
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

Citations39
Published2005
Admission routes1
Has abstractyes

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