Simulating Face to Face Collaboration for Interactive Learning Systems
Bibliographic record
Abstract
Abstract: The use of Problem-Based Learning (PBL) in medical education and other educational settings has escalated. PBL's strength in learning is mostly due to its collaborative and open-ended problem solving approach. Traditional PBL was designed to be used in live team environments rather than in an online setting. We describe research that allows for web-based PBL via geographically distributed physical locations that emphasize PBL's collaboration and open brainstorming approach using interactive web, gaming and simulation techniques. We describe Interactive Face Animation- Comprehensive Environment (iFACE) which allows for expressive voice based character agents along with Collaborative Online Multimedia Problem-based Simulation Software (COMPS) which integrates iFace within a customizable web-based collaboration system. COMPS creates an XML-based multimedia communication medium that is effective for group based case presentations, discussions and other PBL activities. We also discuss our medical school prototype that allows for brainstorming sessions, remote instructors and simulated patients. Figure 1: Instructor remotely delivering web based collaborative content in COMPS while controlling the expressive iFACE face agent via speaking through his computer microphone in real-time.
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.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".