MétaCan
Menu
Back to cohort

Evaluating the Effectiveness of a Clinical Tracking System for Undergraduate Nursing Students

2013· article· en· W4243852801 on OpenAlex
Vincent Salyers, Lorraine Carter, Clara D. Antoniazzi, Susan L. Johnson

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

VenueNursing Education Perspectives · 2013
Typearticle
Languageen
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsTracking (education)Medical educationDocumentationMedicineNursingPsychologyComputer sciencePedagogy

Abstract

fetched live from OpenAlex

Aim. This study evaluated one commercially available clinical tracking system to determine its appropriateness for use within a school of nursing. Background. Collecting documentation during undergraduate clinical experiences (e.g., type of patient care experience, diagnosis, skills completed, competencies met) is a challenging undertaking for students and faculty. Little research has been conducted to evaluate the effectiveness of clinical tracking systems. Method. A convenience sample of students and faculty completed an end-of-course survey that measured their satisfaction with the clinical tracking system. Results. Statistically significant (p < .05) differences were found between students and faculty in several areas: utility, technical issues, capacity to identify regulatory body achieved competencies, and usefulness of records generated. There was also a statistically significant (p < .01) difference in overall satisfaction, with faculty much more satisfied with the system than students. Conclusion. The clinical tracking system was found by faculty and students to be user friendly. Faculty overall were more satisfied with the system than students.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.086
GPT teacher head0.523
Teacher spread0.437 · 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