LearnMate AI

Inspiration

As students, we often find it difficult to study from lengthy textbooks, lecture slides, and video lectures. Even after reading a topic multiple times, we may still have doubts. General AI tools can explain concepts, but their answers are not always connected to our study materials and may include incorrect references.

This inspired us to build LearnMate AI for Track D: Personalized Tutoring & Adaptive Learning. Our goal was to create a study companion that helps students understand concepts more easily, find answers from their own learning materials, and improve through quizzes that adapt to their performance.

What it does

LearnMate AI brings learning materials and personalized tutoring together in one platform.

-Learning Dashboard:Displays learning progress, quiz scores, study streaks, and topics that need more attention. Knowledge Base: Supports learning materials such as PDF textbooks, lecture slides, notes, and transcripts. AI Tutor: Helps students understand concepts through explanations, examples, summaries, and source references. Adaptive Quizzes: Adjusts question difficulty according to student performance, helping learners strengthen their basics and progress to harder questions. Personalized Study Plan: Identifies weaker topics and recommends suitable revision activities based on quiz results. Learning Analytics: Helps students understand their progress through quiz scores and topic-wise performance.

We also included a sample Introduction to Artificial Intelligence course so users can explore the learning experience.

How we built it

We built the frontend using React, TypeScript, Vite, and Tailwind CSS. We used Lucide icons for the interface and charts to display learning progress.

For the knowledge base, we focused on extracting text from learning materials and preserving useful source information, such as document titles and page numbers. The tutor uses relevant content from these materials to support its answers and provide references.

We also implemented an adaptive quiz mechanism that changes question difficulty based on recent answers. Quiz results help estimate topic mastery and update study recommendations.

The application includes a demo mode that allows users to explore the main features without configuring an API key. Live AI tutoring through Google's Gemini API is an additional integration goal.

Challenges we ran into

One of our main challenges was connecting AI-generated answers to the original learning materials. We wanted students to check the sources behind an answer instead of relying entirely on the AI.

Another challenge was developing the adaptive quiz logic. We needed the difficulty to respond to correct and incorrect answers and use the results to recommend suitable revision activities.

We also wanted to make the application easy for hackathon judges to explore, even if they did not have their own learning materials or API keys available.

Accomplishments that we're proud of

We are proud to bring tutoring, learning materials, adaptive quizzes, and personalized study recommendations together in one application.

Instead of providing only a question-and-answer chatbot, LearnMate AI focuses on helping students identify their weak areas and understand what they should study next.

We are also proud of including a sample course that makes it easier for users and judges to explore the application's main learning features.

What we learned

Through this project, we learned how AI can be combined with educational content to support personalized learning. We explored document text extraction, retrieving relevant information, and displaying source references alongside answers.

We also learned how quiz performance can be used to adjust question difficulty and recommend topics for revision. This project helped us understand how frontend development, AI integration, and adaptive algorithms can work together to create a more useful learning experience.

What's next for LearnMate AI

In the future, we would like to add voice-based tutoring, improve support for lecture videos and handwritten notes, and integrate LearnMate AI with learning management systems such as Google Classroom and Canvas.

We also plan to improve the personalization system so that recommendations become more useful as students complete more quizzes and learning activities.