handlers/session.rs - Learning Session Management

Requirements and Dataflow

  • Manages learning session lifecycle including creation, tracking, and completion
  • Handles task responses and scoring within active learning sessions
  • Integrates with adaptive learning algorithms for dynamic difficulty adjustment
  • Provides session replay functionality for analysis and review
  • Coordinates with learner profiles and topology configurations

High-level Purpose and Responsibilities

  • Session Lifecycle: Creation, tracking, completion, and archival of learning sessions
  • Task Management: Integration with core learning algorithms for task generation and adaptation
  • Response Processing: Recording and scoring of learner responses with feedback generation
  • Adaptive Learning: Real-time session adjustment based on learner performance
  • Data Collection: Comprehensive tracking of learning interactions for analytics
  • Replay System: Session reconstruction for analysis and educational review

Key Abstractions and Interfaces

  • Session creation with learner validation and topology configuration
  • Task response submission with scoring and adaptation triggers
  • Session completion with summary generation and performance metrics
  • Topology handling for different learning domains (alphabet, music, mathematics)
  • Integration with core learning algorithms through service layer abstraction

Data Transformations and Flow

  1. Session Creation: Learner validation → topology configuration → session initialization → database persistence
  2. Response Processing: Task response → scoring algorithm → adaptation trigger → database update
  3. Session Progress: Performance tracking → difficulty adjustment → next task generation → learner feedback
  4. Session Completion: Final scoring → summary generation → learner statistics update → session archival
  5. Replay Generation: Session reconstruction → response sequence → performance analytics → visualization data

Dependencies and Interactions

  • Learner Service: Learner profile management and permission validation
  • Core Learning Algorithms: Task generation, scoring, and adaptive difficulty adjustment
  • Database Layer: Session persistence, response tracking, and performance storage
  • Adaptation Service: Dynamic learning algorithm adjustment based on performance
  • Business Metrics: Learning effectiveness tracking and engagement analytics
  • Audit System: Session activity logging and learning interaction tracking

Architectural Patterns

  • Session State Management: Comprehensive session lifecycle with status tracking
  • Adaptive Learning Integration: Real-time algorithm adjustment based on performance data
  • Permission-Based Access: Learner ownership validation and access control
  • Data Persistence: Detailed session and response tracking for analytics
  • Service Layer Integration: Clean separation between handlers and core learning logic
  • Performance Analytics: Comprehensive metrics collection for learning effectiveness analysis