Inspiration
Many students struggle to identify which topics they find difficult and how to improve their learning. We wanted to create a simple, beginner-friendly platform that helps students understand their learning progress and focus on the topics that need more practice.
What it does
LearnSmart is a proposed ML-powered personalized learning platform designed to help students practice quizzes, identify weak topics, track their progress, and receive study recommendations based on their performance.
How we plan to build it
The platform will use HTML, CSS, and JavaScript for the frontend, Python and Flask for the backend, and SQLite to store learning and quiz data. We plan to use Python and Scikit-learn to build a machine learning model that analyzes quiz performance and supports personalized learning recommendations.
Challenges
One of the main challenges is designing a useful recommendation system with limited student data. We aim to address this by starting with sample learning data, testing the model, and improving recommendations based on quiz results.
What we hope to learn
Through LearnSmart, we aim to gain practical experience in machine learning, web development, data analysis, and building technology that makes learning more accessible and engaging for beginners.
Future Scope
Future improvements may include adaptive quizzes, more learning subjects, personalized study plans, and deployment using suitable AWS services.
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