MétaCan
Menu
Back to cohort
Record W2611988902 · doi:10.17483/2368-6669.1088

Baccalaureate Program Evaluation, Preceptors, And Closing The Theory-Practice Gap: Is There A Connection?

2017· article· en· W2611988902 on OpenAlexaffvenue
Catherine Thibeault

Bibliographic record

VenueQuality Advancement in Nursing Education - Avancées en formation infirmière · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsTrent University
Fundersnot available
KeywordsPreceptorCurriculumMedical educationObjectivismCornerstoneCitizen journalismStakeholderNursingPedagogyNurse educationMedicinePsychologyEngineering ethicsPolitical scienceEngineeringPublic relations

Abstract

fetched live from OpenAlex

Curriculum evaluation and renewal is a cornerstone of nursing education. Systematic program evaluation in baccalaureate nursing education relies on feedback from a wide variety of stakeholders. Clinical preceptors represent an underutilized stakeholder group. Situated in both clinical practice and clinical education, preceptors have a unique and valuable perspective on the ability of the curriculum to prepare pre-licensure learners for professional practice. The author suggests that preceptor-stakeholders can be actively engaged in program evaluation: this kind of engagement relies on a paradigm shift from predominantly objectivist evaluation strategies to approaches that are more participatory and pluralistic. Readers will identify the significant role of clinical nursing preceptors as key stakeholders in BScN curriculum evaluation. Further, the author speculates that a pluralistic evaluation paradigm may help both nursing faculty and nurses in clinical practice understand the perspective of the other group, thus reducing the perceived theory-practice gap and creating more responsive baccalaureate nursing curricula.

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)0.018
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0020.006
Open science0.0010.000
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 head0.204
GPT teacher head0.573
Teacher spread0.369 · 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 designOther design
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

Citations6
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueQuality Advancement in Nursing Education - Avancées en formation infirmièreSame topicEvaluation and Performance AssessmentFrench-language works237,207