Advancing Virtual Simulation in Education: Administrators' Experiences
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.
Bibliographic record
Abstract
BackgroundHigher education healthcare administrators are under increasing pressure to find quality clinical placements and there is a critical need to look beyond traditional ways of preparing students for practice. Virtual simulation is a rapidly emerging tool for learning within healthcare education. Administrators are just starting to learn how to manage its integration into curricula.MethodsEleven healthcare administrators from seven institutions of higher education, colleges and universities were interviewed in this qualitative study to understand their needs, challenges, and recommendations regarding virtual simulation integration. These administrators were testing and integrating virtual simulations provided through the Virtu-WIL program, a pan-Canadian, work-integrated learning experience that developed and tested health care virtual simulations.ResultsFour themes were derived from the data: Driving forces, Impact of VS on learning process and outcomes, Collaboration and Coordination, and Sustainability. In addition, administrators recommended several different strategies to support the implementation of virtual simulation. These included faculty support, collaboration between schools and institutions and sustainability initiatives.ConclusionAdministrators are integral to successful VS adoption; therefore, they need to effectively manage its integration in the curriculum.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it