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Record W2518086660 · doi:10.1515/ijnes-2015-0053

Nursing Students’ Perceptions of Anecdotal Notes as Formative Feedback

2016· article· en· W2518086660 on OpenAlexaff
Margaret Ann Quance

Bibliographic record

VenueInternational Journal of Nursing Education Scholarship · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsMount Royal University
Fundersnot available
KeywordsFormative assessmentMedical educationNursingExtant taxonNurse educationQuality (philosophy)Transparency (behavior)MedicinePsychologyPedagogyComputer science

Abstract

fetched live from OpenAlex

Anecdotal notes are a method of providing formative feedback to nursing students following clinical experiences. The extant literature on anecdotal notes is written only from the educator perspective, focusing on rationale for and methods of production, rather than on evaluation of effectiveness. A retrospective descriptive study was carried out with a cohort of 283 third year baccalaureate nursing students to explore their perceptions of anecdotal notes as effective formative feedback. The majority of students valued verbal as well as anecdotal note feedback. They preferred to receive feedback before the next learning experience. Students found the quality of feedback varied by instructor. The anecdotal note process was found to meet identified formative feedback requirements as well as the nursing program's requirement for transparency of evaluation and due process. It is necessary to provide professional development to clinical nurse educators to assist them develop high quality formative feedback using anecdotal notes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.067
metaresearch head score (Gemma)0.226
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.067
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0670.226
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0030.005
Scholarly communication0.0070.004
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.066
GPT teacher head0.476
Teacher spread0.410 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2016
Admission routes1
Has abstractyes

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