AI for Personalized Education System
The AI-Based Personalized Education System is an intelligent platform developed to provide a customized learning experience for every student based on individual abilities, interests, performance and learning progress. In traditional education, students are generally provided with the same learning materials and teaching methods, even though each student has a different level of understanding and learning speed. This work uses Artificial Intelligence and Machine Learning techniques to analyze student data such as quiz scores, assessment results, learning activities and progress in order to identify strengths and weaknesses. Based on this analysis, the system can recommend suitable study materials, personalize learning paths, and adjust the difficulty of questions according to the student’s performance. It can also include an AI-based virtual tutor that helps students understand difficult topics by answering questions and providing simple explanations. The system provides continuous feedback and tracks student progress, helping both students and teachers understand learning improvements and areas that require more attention. Teachers can use the system to monitor individual student performance and provide additional support when needed. By combining personalized recommendations, adaptive assessments, progress tracking and AI-based assistance, the proposed system aims to make education more engaging, flexible and effective. Overall, this work demonstrates how Artificial Intelligence can be used to support student-centered learning and improve the quality of education by providing the right learning content to the right student at the right level.
Authors
- D. Praveen
- G. Sowjanya
- Babu Ch. Kiran
- Sai Lakshmi D. Venkata
- M. Sai Harsha
- P. Uday Kiran
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-11-10
- DOI
- https://doi.org/10.5281/zenodo.24104238
- Primary Topic
- Intelligent Tutoring Systems and Adaptive Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00