AI-Driven Smart Study Application

The rapid growth of digital education demands intelligent systems capable of delivering personalized learning experiences. Traditional study methods often fail to adapt to individual learning pace, leading to reduced engagement and inconsistent academic performance. This research proposes an AI-Driven Smart Study Application designed to enhance student productivity and academic outcomes through adaptive planning and intelligent recommendations. The system integrates personalized study scheduling, AI-based quiz generation, progress analytics, and cloud-backed note management within a mobile platform. A usercentred development methodology was adopted, including requirement collection, prototype development, iterative testing, and performance evaluation. The application utilizes Android technology with Firebase backend services and machine learning-based recommendation logic. The proposed system establishes a scalable and efficient framework for AI-supported personalized education.