Personalized Learning Through Cognitive State Analysis: A Context-Aware AI Companion

ABSTRACT Personalized Learning through Cognitive State Analysis is an intelligent web-based learning system that monitors a learner’s attention level using real-time webcam analysis. The system detects facial presence and eye activity using OpenCV and Haar Cascade algorithms to determine whether the learner is attentive or distracted. Based on the detected cognitive state, the system dynamically adapts the learning content. If the learner is attentive, video-based learning continues. If the learner is distracted multiple times, the system recommends alternative learning modes such as text-based content or quizzes. The platform also provides a dashboard to analyze attentive time, distracted time, and overall performance. This system aims to improve learning efficiency, engagement, and personalization in digital education environments. Keywords: Personalized Learning, Cognitive State Analysis, Haar Cascade, OpenCV, Adaptive Learning, Attention Detection, E-learning.