Empowerment and Leadership Development in an Online Story-Based Learning Community
Bibliographic record
Abstract
The problem was that there is a shortage of nurses who possess the leadership practices required to fill current and impending nursing leadership vacancies. Hospital-based nurse educators are in a prime position to foster a leadership mindset within nurses, and seek out potential nurse leaders; however, nurse educators first need to develop their own leadership practices and feel empowered to take on the role of mentoring future nurse leaders. The goal was to develop an online learning community where hospital-based nurse educators could develop their own nursing leadership practices through storytelling within an environment that included the elements of teaching presence, cognitive presence, and social presence. The online learning community would be considered an empowering environment, and nurse educators would improve their own feelings of empowerment. A wiki was used as the computer-user interface for the online learning community, and was designed based on the principles of human-computer interaction, learning theory, and instructional design. The wiki was separated into two learning communities, namely, the facilitated community and the self-organizing community. Some of the wiki pages were viewable by both communities, some were community specific, and other pages were private and viewable only to the nurse educator and the facilitator. The researcher/facilitator was the leader of the facilitated community, while self-organizing community members were responsible for leading their own community. The facilitator intervened in the self-organizing community when necessary, mostly to address technical issues. Through direct instruction via narrated presentations available to both communities, and leadership stories written and posted by the community members themselves, nurse educators learned about exemplary practices of leadership. Nurse educators in both communities significantly increased their own perceived leadership practices and perceived levels of empowerment. Educators in both learning communities identified that their communities included the elements of teaching, cognitive, and social presence. There were no differences between the communities, except on the teaching presence subscale of direct instruction, where the facilitated community was rated significantly higher. Given increases in empowerment levels, it was determined that both online learning communities could be considered empowering environments.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".