Document learner workbench pilot
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README.md
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README.md
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@ -140,6 +140,31 @@ For the fastest included example, use the MIT OCW Information and Entropy demo.
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- progress visualization
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- skill export
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## Learner Workbench Pilot
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Didactopus now also includes a learner-workbench pilot in the web UI.
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The current split is:
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- review workbench for candidate triage, synthesis, and promotion
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- learner workbench pilot for guided study and reflective revision
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The learner-workbench pilot currently uses the `Evidence Trail` sample pack and
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focuses on:
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- question framing
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- observation versus interpretation
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- source comparison
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- bibliography growth
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- revision under uncertainty
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The backend entrypoint for that pilot is `POST /api/learner-workbench/session`.
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The frontend pilot pack payload is [evidence-trail-pack.json](/home/netuser/bin/Didactopus/webui/public/packs/evidence-trail-pack.json), and the underlying pack lives in [domain-packs/evidence-trail](/home/netuser/bin/Didactopus/domain-packs/evidence-trail).
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This is still a pilot rather than the final learner UX. It is best understood as
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the first integrated learner-workbench path inside the main repository, not as a
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finished replacement for the existing learner-session demos.
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## `doclift` Bundle Ingestion
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When your source material starts as legacy office documents, the intended
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@ -87,7 +87,7 @@ Target features:
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### 5. Learner workbench UI
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Status: planned
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Status: pilot in progress
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Why important:
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@ -103,6 +103,23 @@ Target features:
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- evaluator feedback
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- recommended next step
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Current pilot state:
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- a backend learner-workbench path exists in `didactopus.learner_workbench`
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- the API exposes `POST /api/learner-workbench/session`
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- the web UI now has a launcher that separates review workbench from learner workbench
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- the first pilot pack exists at `domain-packs/evidence-trail/`
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- the frontend can load a static learner-pack payload from `webui/public/packs/evidence-trail-pack.json`
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- the current pilot explicitly emphasizes question framing, observation versus interpretation, uncertainty, and revision
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Next steps:
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- connect the learner-workbench pilot more directly to the standard learner-session backend
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- persist learner-workbench state instead of treating each step as a stateless interaction
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- ground the pilot more deeply in source fragments instead of mostly pack-level structure
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- decide which scientific-virtues framing belongs in the stable learner path versus remaining pilot-specific
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- document a simple local run path for using the learner workbench outside ad hoc development
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### 6. Adaptive diagnostics and practice refinement
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Status: planned
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@ -195,8 +212,9 @@ Examples:
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## Suggested Implementation Sequence
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1. Strengthen `didactopus.learner_session` into the standard session backend.
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2. Build a small model-benchmark harness around that backend.
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3. Add accessible learner HTML and text-first outputs.
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4. Add local TTS and STT support to the same session flow.
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5. Expand adaptive practice and diagnostics.
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6. Improve review, impact analysis, and incremental update support.
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2. Fold the learner-workbench pilot into that backend without losing its stronger study-state framing.
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3. Build a small model-benchmark harness around the unified learner backend.
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4. Add accessible learner HTML and text-first outputs.
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5. Add local TTS and STT support to the same session flow.
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6. Expand adaptive practice and diagnostics.
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7. Improve review, impact analysis, and incremental update support.
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