Code Learn

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Authors: Nandhini G S, Abitha M, Kavya G, Haarhish V S, Jaya Surya S; Lumin Yagal S
Cited by: 0

Abstract

CodeLearn is an intelligent and adaptive e-learning platform designed to transform how students and professionals acquire knowledge through personalized, data-driven instruction. The platform provides a comprehensive library of courses, quizzes, and learning materials across domains such as programming, data science, and web development. By modeling each learner’s pace, performance, and interests, CodeLearn delivers a tailored learning experience that supports continuous engagement and improved outcomes. The system is built on a modern technological stack, featuring a React.js–based frontend and a Python backend implemented using Flask or Django. To optimize content delivery, CodeLearn employs a hybrid recommendation engine that integrates Collaborative Filtering, Content-Based Filtering, and Deep Q-Learning. These machine learning techniques enable the platform to recommend the most relevant lessons and activities for each user, adapting dynamically as their learning behavior evolves. Secure user authentication and role-based access control ensure that learners receive personalized dashboards, while administrators can efficiently manage course content, monitor learner progress, and oversee system operations. Adaptive quizzes and real-time analytics further enhance personalization by evaluating individual performance and adjusting difficulty levels to match the learner’s evolving proficiency

Fields of Study & Subjects

Intelligent Tutoring Systems and Adaptive Learning Online Learning and Analytics Recommender Systems and Techniques

Publication details

Journal / source
Iconic Research and Engineering Journals
Volume
9
Issue
7
Publication date
12 January 2026
Language
EN