Socratic Bot
Unlock the World of Algorithms with AI-Powered Socratic Tutoring This project offers an interactive AI-driven Socratic assistant designed to guide students through the complexities of data structure.
Created on 2nd October 2024
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Socratic Bot
Unlock the World of Algorithms with AI-Powered Socratic Tutoring This project offers an interactive AI-driven Socratic assistant designed to guide students through the complexities of data structure.
Describe your project
In-Scope:
This project provides an interactive AI-driven tutoring system focused on teaching data structures and sorting algorithms. The solution includes a user-friendly chat interface where students can engage in Socratic dialogue with an AI assistant. The AI generates insightful questions, prompts critical thinking, and provides tailored feedback on user inputs
Out of Scope:
The current solution does not cover all aspects of computer science or programming languages beyond data structures and sorting algorithms. Advanced topics such as machine learning, databases, or system design are not included. Additionally, while the AI assistant aims to enhance understanding, it does not replace formal education or provide certification. The system also does not support real-time coding exercises or integrated development environments (IDEs) for hands-on coding practice.
Future Opportunities:
There are several opportunities for enhancing this solution, including expanding the curriculum to cover additional topics in computer science and algorithms. Integrating gamification elements, such as quizzes or challenges, could further engage users and reinforce learning. Future iterations could incorporate adaptive learning technologies, allowing the AI to personalize content based on individual user performance. Additionally, creating a mobile application could enhance accessibility, reaching a broader audience and providing learning on-the-go.
Challenges we ran into
- AI Response Consistency
Challenge: Initially, the AI responses were not consistently staying on topic. The assistant would sometimes drift away from discussing sorting algorithms, reducing the educational value.
Solution: We refined our prompt engineering by adding a specific instruction to always redirect the conversation back to sorting. - Dark Mode Implementation
Challenge: Implementing a seamless dark mode that worked well with both the cover page and chat interface proved tricky. We needed to ensure all elements were legible and visually appealing in both light and dark modes.
Solution: We leveraged CSS variables and media queries to create a dynamic theming system. By using prefers-color-scheme: dark, we were able to automatically switch between light and dark modes based on the user's system preferences. We carefully selected a color palette that works well in both modes, ensuring contrast ratios meet accessibility standards. - User Input Validation:
We encountered issues with invalid user inputs causing unexpected behavior in the chat interface. This led to a poor user experience, as errors would crash the application. To mitigate this, we implemented rigorous input validation and error handling mechanisms. We introduced clear user feedback for common errors, ensuring that users were guided to provide appropriate input and could recover gracefully from mistakes.
4.Typewriter Effect Performance:
Implementing a typewriter effect for AI responses added a layer of complexity. Initially, it caused performance issues and lag in rendering messages, especially for longer responses. We resolved this by optimizing the text rendering logic, ensuring that only one character was processed at a time without blocking the main thread. This improved the responsiveness of the chat interface while maintaining an engaging user experience.
Tracks Applied (1)
5. Problem statement shared by Blume Ventures
Technologies used