Collaborative Online Multimedia Problem-Based Learning Simulations (COMPS)
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
This chapter describes the development, implementation and evaluation of a Collaborative Online Multimedia Problem-based Learning Simulation (COMPS) instructional model designed to help students and practitioners in the health professions develop clinical reasoning and diagnostic skills. Both students and instructors are searching for effective learning platforms and pedagogical models that enable them to collaborate, study, and work at a distance. In order to address this need, COMPS was developed to support a case-based tutorial model where learners can work together online to solve authentic problems no matter where they are located. The model aims to bring together the strongest features of simulations, namely engagement and immersiveness, with one of the strongest features of face-to-face learning—social interaction. The COMPS model combines these strengths to create a new learning system for health education and examines how students learn in this online environment. This chapter also discusses the next steps in our research and development, investigating the use of a COMPS model on a dedicated platform.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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