LinguistAI: Adaptive Vocabulary Mastery Platform

Traditional vocabulary learning applications rely on static repetition or fixed difficulty progression, failing to model individual mastery probability, forgetting curves, or learner-specific performance patterns. This results in inefficient practice cycles and superficial retention.

LinguistAI integrates Spaced Repetition Systems (SRS), Bayesian Knowledge Tracing (BKT), and adaptive difficulty modeling into a gamified, offline-first mobile architecture. Built with Clean Architecture and Domain-Driven Design principles, the system dynamically adjusts review timing, mastery thresholds, and challenge intensity based on real-time performance data. Learning analytics and forecasting modules transform raw interaction data into predictive insights.

LinguistAI demonstrates how adaptive modeling, gamification economies, and predictive analytics can be combined within a scalable mobile architecture. The platform achieves high query performance (<100ms), low crash rates (<0.1%), and production-level reliability while supporting personalized mastery modeling and long-term retention tracking.