Personalized AI Tutor: An Intelligent Adaptive Learning System for Early Education
Year: 2026
Type: conference-paper
Abstract: This research presents a Personalized AI Tutor system designed for adaptive learning in early education. The proposed system utilizes artificial intelligence, machine learning, and learning analytics techniques to create a personalized educational environment for students. The platform continuously analyzes student performance, learning patterns, topic completion status, assessment scores, and interaction behavior in order to dynamically recommend suitable educational content and learning materials. Based on the understanding level of each learner, the system intelligently adjusts recommendations and learning paths to improve educational effectiveness and student engagement. The developed AI Tutor integrates adaptive assessments, intelligent recommendation systems, performance analytics, and progress tracking mechanisms to provide customized learning experiences for students. The project aims to enhance personalized education, improve accessibility to digital learning resources, and support student-centric adaptive learning methodologies. This research contributes toward the development of intelligent tutoring systems capable of supporting modern digital education platforms through AI-driven personalization and adaptive educational technologies. Project Demo:https://personalized-ai-tutor.netlify.app
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7161691687
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