Co-constructing Simulations with Learners: Roles, Responsibilities, and Impact
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
Co-constructed simulations were designed and piloted with senior occupational therapy master’s students in a neurorehabilitation practice module. The instructor served as the guide for the students through all phases of the case creation, simulation development, delivery, and debrief. The instructor facilitation promoted self-regulated learning (SRL) of knowledge and skill development through independent discovery and peer learning. This paper provides an evidence-informed co-construction simulation design with outlined stages, roles, and responsibilities for the instructor and learner. Thematic qualitative analysis of student feedback highlighted enhanced insight and SRL as a result of multiple role preparation, observation and interaction with peers, close interaction with the instructor, and the multi-stage debrief process. Recommended key features and critical interactions for a successful co-constructed design are also identified for the learner, instructor, and simulation. The co-construction simulation process and design elements are suitable for learners in any health-related field of study.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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