Experiments Module - Abstract Documentation
Purpose and Responsibility
Provides comprehensive experimental framework for conducting controlled learning research studies. Manages experimental design, participant assignment, condition randomization, data collection, and statistical analysis for rigorous research applications.
Key Data Structures and Relationships
Core Framework Components
- core: Main experimental framework with experiment management and execution
- ab_testing: A/B testing functionality for comparing learning conditions
- design: Experimental design patterns and statistical power analysis
- multi_session: Longitudinal study management across multiple sessions
Experimental Hierarchy
ExperimentFramework → Experiments → Conditions → Participants → Sessions → Trials
Main Data Flows and Transformations
Experiment Lifecycle
- Design Phase: Experimental design, power analysis, condition specification
- Setup Phase: Participant recruitment, randomization, condition assignment
- Execution Phase: Data collection, session management, real-time monitoring
- Analysis Phase: Statistical analysis, effect size calculation, report generation
Data Collection Pipeline
- Session Management: Multi-session studies with participant tracking
- Condition Control: Randomized assignment and counterbalancing
- Quality Assurance: Real-time data validation and integrity checks
- Export Integration: Research-ready data formats for analysis software
External Dependencies and Interfaces
- Statistical Framework: Integration with statistics module for analysis
- Learning System: Core learning models and adaptive algorithms
- Task Generation: Experimental task creation and difficulty calibration
- Data Export: Research-standard data formats and analysis scripts
Core Algorithms and Business Logic Abstractions
- Randomization: Condition assignment with counterbalancing and blocking
- Power Analysis: Sample size calculation and effect size estimation
- Multi-level Analysis: Hierarchical modeling for nested experimental designs
- Longitudinal Tracking: Participant progress across multiple sessions