Reflections on the role of faculty in distance learning and changing pedagogies.
Bibliographic record
Abstract
The increasing number of nursing faculty teaching in distance education programs represents a paradigm shift that has implications for faculty role and changing pedagogies. This descriptive study investigated experiences of nursing faculty teaching web-based courses. Participants were drawn from eight nursing schools in the United States and Canada. Nineteen faculty discussed perceptions of teaching online in small-group teleconference interviews. Major categories identified were: faculty role issues, redesigning/rethinking courses, handling communications, developing partnerships, managing time, and dealing with technology. The core category was: redesigning pedagogies and rethinking faculty role for online teaching. Dimensional analysis was used to develop a matrix telling the story of the experience within the perspectives of antecedent conditions, context, strategies, and consequences. Results indicated that support systems, technology partnerships, and policies should be in place before redesign. The context of redesign was evident in moving from "on stage" to a virtual environment. Strategies used to redesign courses included collaboration, rethinking communications, and faculty development. Consequences had positive and negative outcomes with respect to their impact on faculty role, teaching approaches, and student/faculty relationships.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".