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Record W2000603549 · doi:10.5430/jnep.v4n1p100

Course syllabi: Components and outcomes assessment

2013· article· en· W2000603549 on OpenAlexvenueno aff
Zane Robinson Wolf, Kathleen Czekanski, Patricia Dillon

Bibliographic record

VenueJournal of Nursing Education and Practice · 2013
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsSyllabusStandardizationAccreditationCurriculumContext (archaeology)Medical educationQuality (philosophy)Nurse educationNursingMedicinePsychologyPedagogyPolitical scienceGeography

Abstract

fetched live from OpenAlex

Course syllabi operate as basic structures of nursing curricula. They communicate and shape student and faculty respon- sibilities. Syllabi function to orient new faculty to the cultural norms of nursing programs, specify student learning outcomes, connect course outcomes to the program level, and provide evidence for accreditor organizations of curricular quality and achievement of standards. A committee on assessment and evaluation of a university’s nursing programs reviewed examples of syllabi and identified needed revisions. Members examined literature on syllabus construction and alignment with student learning outcomes along with faculty concerns about syllabi. Consequently, the nursing programs’ activities influenced a university’s review and standardization of syllabi in the context of nursing accreditation self-study and university regional accreditation standards.

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)0.009
metaresearch head score (Gemma)0.029
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.005

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 head0.181
GPT teacher head0.575
Teacher spread0.394 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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