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Data Sheet 1_Assessing and monitoring clinical practice of undergraduate nursing students: a middle eastern context.pdf

2025· dataset· en· W6927078163 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDiphtheria, Corynebacterium, and Tetanus
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationClinical PracticeObjective structured clinical examinationNurse educationCurriculumNursing practiceQualitative researchNursing Outcomes Classification

Abstract

fetched live from OpenAlex

This paper presents an innovative Weekly Clinical Skills Progress (WCSP) tool to support the assessment of undergraduate nursing students in their clinical placements. The WCSP tool was implemented at the University of Calgary in Qatar (UCQ) Nursing Program in Spring 2024 to address inconsistencies in assessment documentation related to the absence of clearly defined proficiency levels in clinical courses. The UCQ clinical faculty trialed the newly developed WCSP tool on eighty-seven third-year nursing students enrolled in the clinical course Nursing Practice for High Acuity and Chronic Conditions. These students were divided into 11 groups, each consisting of six to seven members per instructor, and were placed in various medical-surgical clinical sites throughout Hamad Medical Corporation (HMC) in Qatar. During the course implementation and following, feedback from faculty, students and buddy nurses indicated the WCSP tool clarified the clinical goals, enabled consensus on clinical proficiency levels according to the course outline, and assessments were more consistent. Though the WCSP tool is still being refined, and more qualitative and quantitative research is needed, this paper contributes valuable preliminary results and recommendations that benefit nursing programs worldwide.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.096
GPT teacher head0.413
Teacher spread0.316 · 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 designNot applicable
Domainnot available
GenreDataset

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 routes1
Has abstractyes

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