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    June 15, 2024

    AI TUTOR - Education Learning Management System

    AI-driven language learning platform with personalized conversations

    AI TUTOR - Education Learning Management System

    The AI Tutor App was built to provide a personalized Language-speaking practice experience through real-time, AI-driven conversations. Its core goal was to help students improve spoken language skills using CEFR-aligned topics and feedback. With two learning modes — Chat Mode and Photo Mode — the app simulates a human tutor who guides users through structured conversations and only ends the session once all learning goals are met.

    Technology Used

    ReactNestJSTypeScriptAzure OpenAIAzure Speech ServicesWebSocketsAzure Blob Storage

    Key Features

    Chat Mode and Photo ModeCEFR-aligned learning pathsReal-time AI conversationsPersonalized feedbackProgress tracking

    The AI Tutor App represents a breakthrough in language learning technology, designed to provide students with an immersive, personalized speaking practice experience. Built on cutting-edge AI technology, the platform simulates natural conversations with a human tutor, adapting to each learner's proficiency level and learning style. The application features two distinct learning modes: Chat Mode for text-based conversations and Photo Mode for visual learning scenarios. Each session is carefully structured to ensure all learning objectives are met before completion, providing a comprehensive educational experience. The system integrates seamlessly with CEFR (Common European Framework of Reference for Languages) standards, ensuring that all content and assessments align with internationally recognized language proficiency levels. This makes the platform suitable for both individual learners and educational institutions seeking to enhance their language programs. Key technical achievements include real-time speech processing, adaptive learning algorithms, and a robust backend system capable of handling multiple concurrent users while maintaining conversation quality and educational effectiveness. The main challenge was designing a conversation flow that felt natural yet goal-oriented, capable of dynamically responding to user input and tracking CEFR progress. Real-time audio processing — including assessment, response generation, and TTS — needed to be efficient and seamless.

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