59 lines
1.7 KiB
Markdown
59 lines
1.7 KiB
Markdown
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# Phase 3 Plan: Learner Memory
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**Status:** Ready for execution
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**Phase Goal:** Convert graded answer evidence into structured learner memory.
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## Requirements Covered
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- MEM-01: System stores learner profile with role, stack, timeline, and
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preferences.
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- MEM-02: System stores concept mastery states with evidence.
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- MEM-03: System stores recurring misconceptions with supporting answers.
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- MEM-04: System stores intervention history and review schedule.
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- MEM-05: Temporary session context does not become durable memory without
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evidence.
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## Tasks
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### 1. Add learner memory package
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- Create `internal/learnermemory`.
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- Define profile, concept mastery, misconception, intervention, review schedule,
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and snapshot types.
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- Add in-memory store with clear interface.
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### 2. Add memory extraction workflow output
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- Extend `workflows.StubRunner.ExtractLearningMemory` to return evidenced
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memory update candidates from a graded answer.
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- Ensure candidates without evidence are not applied.
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### 3. Wire diagnostic answers to memory
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- Inject learner memory service into interview service.
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- After grading an answer, extract and apply memory updates.
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- Keep diagnostic session records and learner memory records separate.
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### 4. Add memory read endpoint
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- Add `GET /api/v1/learners/{userID}/memory`.
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- Return learner profile, mastery, misconceptions, interventions, and review
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schedule.
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### 5. Add tests and verification
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- Test memory applies only evidenced updates.
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- Test diagnostic answer submission updates learner memory.
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- Test memory HTTP read endpoint.
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- Run Go tests, OpenSpec validation, and line-count check.
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## Out of Scope
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- Persistent database.
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- Memory ranking/decay.
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- Progression readiness map.
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- Frontend UI.
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---
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*Plan created: 2026-04-26*
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