[Türkçe] How Our Analytics Lake Tracks Learning Outcomes (Not Just Clicks)

# How Our Analytics Lake Tracks Learning Outcomes (Not Just Clicks) [Turkish content] ## How Our Analytics Lake Tracks Learning Outcomes (Not Just Clicks) Unlike most EdTech apps that track clicks and time-on-screen, Alphazed's analytics lake tracks actual learning outcomes: pronunciation accuracy improvement over time, concept mastery transitions (beginner → intermediate → advanced), spaced repetition effectiveness (are review sessions reducing forgetting?), and Bloom's Taxonomy level progression. This data drives curriculum improvements and proves to parents that their children are genuinely learning, not just playing. ### Three-Tier Analytics Architecture **Tier 1: Mobile Events** (Real-time from app) When a child completes an exercise, the app sends an event: ```json { "event_type": "attempt_complete", "concept_id": "letter_ba", "exercise_type": "select", "accuracy_score": 0.89, "attempt_number": 3, "session_id": "session_abc123", "timestamp": "2026-03-28T14:35:22Z", "is_correct": true, "response_time_ms": 2400 } ``` **Tier 2: Backend Enrichment** (Context added server-side) Backend augments with user properties: ```json { "...event...", "user_id": "user_456", "age_group": "5-7", "persona": "intermediate", "days_since_signup": 34, "total_practice_minutes": 487, "app_name": "amal", "device_type": "Android", "country": "US" } ``` **Tier 3: Analytics Lake** (Asynchronous, SQL-queryable) ``` Backend sends enriched event → SQS queue (fire-and-forget) ↓ (doesn't wait for analytics) ↓ (user experience unaffected