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Record W2891437611 · doi:10.5430/jnep.v9n1p32

Nursing students’ learning experiences in clinical placements or simulation–A qualitative study

2018· article· en· W2891437611 on OpenAlexvenueno aff
Kirsten Nielsen, Annelise Norlyk, Jette Henriksen

Bibliographic record

VenueJournal of Nursing Education and Practice · 2018
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsNursingQualitative researchPsychologyMedical educationMedicineSociology

Abstract

fetched live from OpenAlex

This paper reports on a qualitative study whose aim was to investigate nursing students' learning experiences in two arenas. It is common practice all first-year nursing students to practise in a skills lab. In this study, students practised in either clinical settings or a skills lab. In the design, a phenomenological-hermeneutic approach was used. The setting was Course 2, a ten-week course including either two weeks on clinical placements or two weeks in a skills lab. The participants were six first-year students. Data were generated by participant observations and interviews and were interpreted according to Ricoeur’s theory of interpretation. The findings indicated that students learned nursing skills in both arenas. However, on clinical placements, students and preceptors began nursing the patients after 20 minutes and students subsequently reflected on practice. In the skills lab, preceptors guided the students for up to an hour before they were ready to begin performing nursing. Students with previous nursing experience and activist learning style preferred to learn on clinical placements. Students with other learning styles – even one student with previous nursing experience – seemed to prefer learning in the lab, where they felt safe, as there was no risk of harm to patients. The conclusion was that, rather than all first-year students practising in the lab, it could be valuable to consider the students’ prior experience and preferred learning style in discussions of where to begin the learning trajectory in the nursing programme.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.368
GPT teacher head0.681
Teacher spread0.313 · 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 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

Citations13
Published2018
Admission routes1
Has abstractyes

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