The simulation coaching concept - A step towards expertise
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
Background and objective: This paper presents a sub-study of an ongoing research and development project (August 1, 2017-December 31, 2019), whose aim has been to use simulation-based coaching to meet social and healthcare staff’s self-reported learning needs in 20 small and medium-sized enterprises in Finland. Two regional educational institutions are responsible for the management of the project. The study aim was to examine the development of self-rated professional competence and expertise of social and healthcare staff, following a simulation coaching project.Methods: An electronic questionnaire was used to collect information about participants’ self-rated expertise, first in November 2017 and again in May 2019 following the simulation-based coaching intervention. IBM SPSS for Windows 25 was used to analyse the data.Results: The respondents appreciated simulation coaching as an effective way of developing expertise and the continuous learning skills of professionals. In this project, coaching was considered to be especially suitable for theoretical and practical management of acute situations; for keeping up with change in society; for anticipating development needs, and for promoting the attractiveness and competitiveness of the company where they worked.Conclusions: The simulation coaching concept, which involves action-based and concrete ways of developing theoretical and practical competence, is well suited for social and healthcare professionals undertaking continuing education. Using the companies’ own facilities facilitates participation and application of new knowledge and skills.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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