A Multi-Agent Architecture for Peer-Help in a University Course*
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
I-Help is an integration of previously developed ARIES Lab tools for peer help to university teaching. In this paper we discuss an approach to distributing the centralised monolithic architecture of I-Help, by using a multi agent-architecture. The I-Help project I-Help is an integration of previously developed ARIES Lab tools for peer help to university teaching. One of its components, CPR provides a subject-oriented discussion forum and moderated FAQ-list supporting students with electronic help. Another component, PHelpS selects an appropriate peer helper who will support the student with direct peer help via an elaborate chat-environment. The selection of appropriate discussion forum, FAQ-article or human peer helper is based on modelling learner knowledge in the context of the concept / topic structure of the subject material. A full paper describing the I-Help Project will be presented at ITS'98 (Greer et al., 1998). In this paper we discuss an approach to distributing the ...
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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 | 0.000 | 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 | 0.000 |
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