Online Scholarly Discourse: Lessons Learned for Continuing and Nurse Educators
Bibliographic record
Abstract
This article describes a collaborative three-year research project that focused on nurses' experiences of a learning environment as they participated in an Internet-based cardiac nursing program. In addition to gathering data about the general appropriateness of the learning environment in a specialty content area, the study examined the environment's facilitation of online scholarly discourse about cardiac nursing. Scholarly discourse is characterized by evolution over time of communication by and among learners, inclusion of references to relevant nursing literature, and the practice of writing conventions appropriate to the discipline. Guided by professorial and other learner supports, it is the foundation of theory-guided, evidence-based practice for registered nurses. The data reflects the study's consideration of online scholarly discourse derived from the nurses' contributions to an online discussion forum. Research partners included Laurentian University's Centre for Continuing Education and School of Nursing, the Sudbury Regional Hospital (SRH), and the Office of Learning Technologies (OLT). The project was funded by the Office of Learning Technologies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".