New_Micro_Learning/docs/event-taxonomy.md

Event Taxonomy

Events use dot-separated past-tense names and versioned payload schemas. Every tenant event includes organization context set by the server, actor context where relevant, occurred time, correlation ID, and causation ID.

Authoring

• course.draft_created
• course.version_published
• taxonomy.mapping_created
• taxonomy.mapping_confirmed

Learning

• course.opened
• course.completed
• lesson.started
• lesson.progressed
• lesson.completed
• block.viewed, block.interacted, and block.completed
• video.started, video.progressed (25/50/75 milestone), and video.completed
• video.replayed, video.skipped, and video.exited
• assessment.started and assessment.completed
• question.answered
• comment.created, bookmark.created, and note.created

The ingestion allow-list is EventTaxonomy::learning() and its current schema version is 1. The server owns organization and learner identity. Clients may supply only a stable event UUID, assignment/content identifiers, occurred time, optional session/correlation/causation identifiers, a bounded payload, and allow-listed device context (platform, formFactor, online, appVersion). Video telemetry reports media position/duration and discrete milestones; it never sends a derived learner score.

Intelligence

• assessment.evidence_created
• skill.evidence_recorded
• capability.recalculation_requested
• capability.score_updated
• capability.snapshot_created
• coverage.metric_updated
• skill_gap.detected

Raw events carry stable IDs, not copied taxonomy trees, and are immutable after ingestion. Consumers claim an event using (learning_event_id, processor, processor_version), so retries and late/offline delivery cannot duplicate projections. Derived daily metrics, risks, insights, and attention records stay in separate tables and can be rebuilt from raw events.