Let's Study

AI for Accessible Education

Comment 1

About the Project

Inspiration

Education should be accessible, personalized, and engaging for everyone. Traditional approaches often overlook individual learning styles, causing frustration and disengagement. Inspired by the potential of AI-driven adaptability, we created Let’s Study—an adaptive learning platform that tailors course content based on the RAISEC personality test and user performance, making learning more efficient, interactive, and enjoyable.

What It Does

Let’s Study is an AI-powered platform that:

  • Personalizes courses using RAISEC personality traits.
  • Generates custom lesson plans, quizzes, and assessments aligned with each learner’s style.
  • Adapts course structure dynamically based on real-time performance data.
  • Tracks progress and offers actionable feedback to guide improvement.
  • Collects user feedback for continual refinement and personalization.

By focusing on individual learning paths, Let’s Study ensures an inclusive and effective educational experience for all users.

How We Built It

  • Frontend: Created with React.js and TailwindCSS for a responsive and intuitive user interface.
  • Backend: Developed using GoLang, handling user data, course personalization, and real-time assessments.
  • Database: Managed with MongoDB to store user progress, RAISEC results, and adaptive course content.
  • AI Integration:
    • Model: Meta-Llama-3.1-8B-bnb-4bit, locally hosted and fine-tuned.
    • Datasets: LectureBank and Open University Learning Analytics Dataset (OULAD) to enrich the model with educational context and learning analytics.
    • Dynamic Course Adaptation: Feedback loops update the lesson path in real time.
  • Authentication: Implemented via Google OAuth to streamline user onboarding.
  • Deployment & CI/CD: Hosted on Vercel with continuous deployment from GitHub.

Challenges We Ran Into

  1. Fine-Tuning AI for Personalization: Balancing the precision of course recommendations with the performance constraints of a locally hosted model.
  2. Adaptive Learning Logic: Designing an adaptive flow that remains user-friendly while adjusting content in real time.
  3. Scalability: Ensuring the platform can handle multiple users simultaneously without compromising the learning experience.

Accomplishments That We’re Proud Of

  • Successful Integration of Personality Traits into the AI model to enhance user engagement and retention.
  • Real-Time Adaptive Learning: Building a platform that continuously evolves with the learner’s progress and feedback.
  • Robust Prototype: A functional system demonstrating how AI can make education more accessible and personalized.

What We Learned

  • Power of AI-Driven Personalization: We saw significant improvements in user engagement when learning paths are tailored.
  • Complexity of Adaptive Systems: Managing dynamic content and maintaining simplicity for end-users requires careful design.
  • Importance of Continuous Feedback: Regular user feedback loops greatly enhance personalization and system accuracy.

What’s Next for Let’s Study

  • Expanded AI-Based Recommendations: Incorporate more sophisticated algorithms to refine course suggestions.
  • Gamification: Implement badges, leaderboards, and reward systems to motivate and engage learners.
  • Mobile App Development: Provide on-the-go access to adaptive learning materials and further boost accessibility.

Through Let’s Study, we envision a future where AI-driven adaptive learning makes education truly accessible, ensuring every learner’s needs are recognized and met.

Built With

Share this project:

Updates