Inspiration

The project was inspired by the lack of a consolidated platform to aid learners in revising and learning specific topics quickly and efficiently. Traditional lecture-based learning often falls short when students need to revisit specific points, making lengthy sessions cumbersome for revision. Additionally, there’s a growing demand for solutions that allow users to focus on particular topics without sifting through hours of content. This project aims to provide a platform optimized for quick revision, making it a convenient tool for learners who value precision and speed.

What it does

Our platform enhances learning by combining accessibility, engagement, and efficiency through key features. The key features implemented successfully include an AI Chatbot for answering user queries using a generative AI model, a Summary Generator for quick topic revisions, a Quiz Module to reinforce learning through interactive assessments, Timestamps to help users navigate and locate specific sections easily, and a Translation Feature to enhance inclusivity through multilingual support.

How we built it

We followed a modular approach, where the project was broken into distinct components. Each module addressed a specific aspect of the platform, such as user interface, backend integration, AI model functionality, and caching mechanisms. Following the software development life cycle (SDLC), we began with requirement analysis to understand user needs, then moved to design, where we kept the learner’s convenience at the forefront. The implementation phase involved iterative development, where individual modules were tested and integrated step by step.

Challenges we ran into

One of the primary challenges was finding the right large language model (LLM) that aligned with our use case. Limited access to free tokens made the evaluation process resource-intensive, as we had to try multiple models to identify the best fit. Additionally, ensuring that these models worked cohesively with the platform's architecture added complexity. Balancing performance optimization and integration with limited resources was a challenging yet rewarding aspect of the project.

Accomplishments that we're proud of

We’re proud of successfully integrating generative AI to power an intelligent chatbot and implementing key features like summaries, quizzes, timestamps, and multilingual translation. Overcoming challenges such as optimizing response times with caching and selecting the right AI tools were major milestones. Most importantly, we created a user-friendly platform that addresses real-world learning challenges and delivers a meaningful impact.

What we learned

Through this project, we learnt about the connectivity between front-end and back-end components and how they integrate seamlessly with generative AI models via APIs. The importance of caching became evident as it significantly reduced response times, even when handling large language models. We also learned to carefully evaluate and select APIs based on specific use cases, optimizing the efficiency and functionality of the application. Overall, we gained good experience in the technical and functional aspects of building a full stack web application.

What's next for EduAId

Voice Input: Enable users to interact with the chatbot or search topics using voice commands. Text-to-Voice Output: Provide text-to-voice functionality for summaries and answers to aid users with disabilities. Notes on Video Timestamps: Allow users to add and save notes linked to specific timestamps for easy navigation. Chat History Storage: Save user chat interactions for future reference and topic revisits. Study Playlist: Let users curate study playlists with videos, tags, and personalized annotations.

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