ADAPTIVE LEARNING SYSTEM USING NEURAL ITERATIVE NETWORKS

This project presents an Adaptive Learning System designed to personalize the e-learning experience based onindividual student performance. The system follows a structured learning cycle where a student first watches aninstructional video on a chosen topic, followed by a short assessment of five randomized questions. If the studentfails to achieve a perfect score, the system automatically recommends another video on the same topic to reinforceunderstanding. This cycle repeats until the student achieves the required proficiency. A MySQL database tracksstudent progress, assessment results, and video attempts to ensure adaptive learning paths. The system is builtusing PHP, MySQL, HTML, and CSS, and can be integrated with existing Learning Management Systems (LMS)for broader accessibility. The intelligent feedback loop improves learning outcomes, knowledge retention, andstudent engagement by offering a flexible, student-centric approach to online education.