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Record W4412578426 · doi:10.17483/d4g46t54

Pedagogical Approaches and Teaching Strategies Used in Nursing Education to Teach Academic Writing: A Scoping Review

2025· review· en· W4412578426 on OpenAlexaffvenueabout
Rose McCloskey, Patricia Morris, Lisa Keeping‐Burke, Ali McGill, Alex Goudreau, Holly Knight, Sarah Buckley, Dave Mazerolle, Courtney M.C. Jones

Bibliographic record

VenueQuality Advancement in Nursing Education - Avancées en formation infirmière · 2025
Typereview
Languageen
FieldArts and Humanities
TopicAcademic Writing and Publishing
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPsychologyNurse educationMathematics educationPedagogyMedical educationMedicine

Abstract

fetched live from OpenAlex

Academic writing is considered an essential skill in post-secondary education in general and in nursing specifically (Mitchell et al., 2020). The importance of writing for future nurses is reflected in the Canadian Association of Schools of Nursing (CASN) National Nursing Education Framework’s standards. This national consensus-based framework outlines the expectations of undergraduate nursing programs and graduates according to the six domains of knowledge, research skills and critical inquiry, nursing practice, communication and collaboration, professionalism, and leadership (CASN, 2022). Academic writing is embedded in each of these domains, as it provides students with a venue to share factual knowledge, demonstrate critical thinking, and make important connections between theory and practice (Naber & Wyatt, 2014). A scoping review of research on the pedagogical approaches and teaching strategies used to teach academic writing in nursing education yielded 12 studies. Findings show a range of approaches with varying degrees of success. Further research is needed on how best to guide and assess students’ writing.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.659
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.002
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 head0.229
GPT teacher head0.505
Teacher spread0.276 · 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.

Study designOther design
Domainnot available
GenreReview

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
Published2025
Admission routes3
Has abstractyes

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