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Record W2014025133 · doi:10.3928/01484834-20120427-03

Developing and Piloting an Online Graduate Nursing Course Focused on Experiential Learning of Qualitative Research Methods

2012· article· en· W2014025133 on OpenAlex

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

VenueJournal of Nursing Education · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicProblem and Project Based Learning
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsExperiential learningQualitative researchConstructivism (international relations)Nurse educationMedical educationPedagogyPsychologyNursingSociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

Despite the turmoil of a worldwide economic crisis, the health sector remains largely understaffed, and the nursing shortage represents a major issue that jeopardizes graduate nursing education. Access to education remains a challenge, particularly in rural and remote areas. This article reports the process of developing an asynchronous online qualitative research course. This online course was piloted among 16 interdisciplinary students. Participants agreed that experiential learning was useful to understand the intricacies of qualitative research. Within this constructivist approach, students were immersed in real-life experiences, which focused on the development of skills applicable to qualitative research. Based on the findings, we suggest that constructivism and the Four-Component Instructional Design (4C/ID) model (a four-part approach for fostering the development of complex skills) represent valuable ontological and pedagogical approaches that can be used in online courses. Triangulating these two approaches is also congruent with the student-centered philosophy that underpins nursing graduate programs.

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)0.016
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.434
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.614
GPT teacher head0.670
Teacher spread0.056 · 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