StudyPilot AI

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  A personalized learning dashboard that brings study materials, AI tutoring, adaptive quizzes, and learning progress together in one place.

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  Upload textbooks, PDFs, lecture audio, slides, diagrams, and notes to build a unified knowledge base

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  Learning Resource Processing "Process and organize learning resources to make information easier to access and retrieve."

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  Knowledge Base "Create a searchable knowledge base from uploaded study materials for personalized learning."

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  Adaptive Quiz Interface "Generate personalized assessment questions to evaluate students' understanding of different topics."

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  Interactive Assessment "An interactive quiz experience that allows students to test their knowledge and practice concepts."

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  AI-Generated Questions "AI-generated questions help students evaluate their understanding through topic-focused assessments."

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  Knowledge Assessment "Generate adaptive diagnostic quizzes based on selected study materials and focus on weaker topics."

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  Quiz Results and Feedback "Review assessment results, identify incorrect answers, and receive revision recommendations.

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  Learning Progress Tracker "Track topic-wise performance, identify weak areas, and monitor learning progress through mastery analytics."

Inspiration

As students, we often struggle to manage information from different learning resources such as textbooks, PDF notes, presentation slides, and lecture transcripts. Finding relevant information, understanding difficult concepts, and identifying our weak areas can take a lot of time.

We wanted to build something that could make learning easier, smarter, and more personalized. This idea inspired us to develop StudyPilot AI, an AI-powered learning companion that brings study materials, personalized tutoring, and adaptive assessments together in one platform.

What it does

StudyPilot AI helps students learn more effectively through four major features:

Unified Knowledge Ingestion: Students can upload or provide their study materials, including PDFs, lecture transcripts, and notes, to create a unified knowledge base.

AI Tutor: Students can ask questions and receive AI-generated explanations grounded in their uploaded materials, along with relevant source citations.

Adaptive Quiz Generation: The platform generates quizzes to evaluate students' understanding and identify topics where they need improvement.

Mastery Tracking: Students can monitor their performance, understand their weak areas, and focus on topics that require more attention.

How we built it

We developed StudyPilot AI using modern web technologies and AI capabilities.

Technology Stack:

Frontend: React 18, Vite, and Lucide Icons

Backend: Node.js, Express.js, and Multer

AI Engine: Groq API with the openai/gpt-oss-120b model

Deployment: Render Cloud

We built the frontend to provide a simple and user-friendly experience, while the backend handles document uploads, processing, and communication with the AI engine.

Challenges we ran into

During development, we encountered several challenges:

Integrating different types of study materials into a unified learning workflow.

Making AI responses relevant to the uploaded content rather than relying only on general knowledge.

Providing useful source citations so students can verify the information.

Designing an adaptive quiz experience that helps students identify their learning gaps.

Connecting the frontend, backend, and AI services into a working application.

Solving these challenges helped us understand how to build and integrate AI-powered applications more effectively.

Accomplishments that we're proud of

We are proud to have transformed our idea into a working AI-powered learning platform that brings multiple study activities together in one place.

Some of our key accomplishments include:

Built a Unified Learning Platform: Successfully brought study materials, AI tutoring, quizzes, and performance tracking together in a single application.

Implemented Source-Grounded AI Tutoring: Developed an AI Tutor that provides answers based on uploaded study materials with relevant source citations.

Created Adaptive Assessments: Implemented quiz generation to help students evaluate their understanding and identify weaker topics.

Developed a User-Friendly Interface: Designed a simple and interactive dashboard to make the learning experience easier for students.

Successfully Deployed the Application: Made our project accessible through a live web application.

What we learned

Throughout this project, we gained practical experience in full-stack web development, API integration, working with large language models, document processing, and cloud deployment.

More importantly, we learned that building a useful AI product is not just about generating answers. It is about understanding users' problems and creating solutions that provide meaningful value.

What's next for StudyPilot AI

We see StudyPilot AI as more than just a hackathon project. Our vision is to turn it into a complete personalized learning ecosystem that helps students learn at their own pace.

In the future, we plan to:

Multimodal Learning Support: Expand support for different learning formats, including audio lectures, video content, images, and handwritten notes.

Smarter Personalization: Improve the AI system to understand each student's learning patterns, strengths, and weaknesses and recommend personalized study plans.

Advanced Adaptive Quizzes: Introduce difficulty levels that automatically adjust based on a student's performance and progress.

Progress Analytics: Build more detailed dashboards to track learning progress, topic-wise mastery, and improvement over time.

AI Study Planner: Add a smart study planner that recommends what to study next based on upcoming exams, available time, and weak topics.

Better Accessibility: Make the platform more accessible through mobile-friendly experiences and multilingual learning support.

Built With

• adaptive-learning
• ai-powered-education
• artificial-intelligence
• css
• education
• express.js
• generative-ai
• groq
• html
• javascript
• large-language-models-(llm)
• multer
• node.js
• personalized-learning
• react
• render
• rest-api
• vite