The qualitative learning experience of healthcare workers completing a hybrid workplace violence educational program
Bibliographic record
Abstract
Background: Hybrid educational methodologies which include online and classroom-based learning experiences increase learning. However, the course delivery preferences of learners need to be evaluated so that the design and delivery of future programs will maximize learning outcomes. The aim of this study was to describe how the delivery of a hybrid program contributes to learning outcomes. Methods: A qualitative descriptive design was used. Participants were recruited from two large emergency departments that completed a hybrid workplace violence educational program. Four focus group sessions were held with a convenience sample of 17 participants to discuss their learning experience with the hybrid educational program. Sessions were audiotaped and transcribed verbatim. Data were analyzed using a constant comparative analysis method. Results: Three themes emerged from the data. The first theme was "Implementation of the Intervention" and represented the opportunity for learning, the environment of learning, and the need for uniform training. The second theme was "Experience of the Intervention" and represented the conditions of learning, interdisciplinary learning, facilitated engagement, and realism of the learning content. The third theme was "Translation of the Intervention" which represented the transferability and retention of the program content. Conclusion: An active learning classroom-based component was perceived to yield greater knowledge attainment and retention than online learning for the participants in this study. Consideration of the learning styles and needs of learners should be taken into consideration when developing content for the online delivery or hybrid approach for educational programs.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".