TutorTeach.ai

TutorTeach.ai is an innovative web-based application designed to enhance the learning experience of students by providing AI-generated educational content. The platform generates engaging video lessons, summarizes texts, creates assignment questions, and predicts student performance, ultimately helping users understand their strengths and weaknesses in various subjects.

Table of Contents

• Features
• How It Works
• Technologies Used
• Installation
• Usage
• Contributing
• License

Features

• AI-Generated Video Lessons: Generate informative videos based on user-selected topics using advanced AI technologies.
• Text Summarization: Summarize lengthy texts to help students grasp essential concepts quickly.
• Assignment Generation: Create custom assignment questions based on the summarized content to assess understanding.
• Performance Prediction: Analyze user responses to predict their strengths and weaknesses in the chosen topic.
• Feedback and Guidance: Provide personalized guidance and resources to help students improve in weaker areas.

How It Works

1. User Input: Students enter a topic they wish to learn about.
2. Video Generation: The model generates a relevant video using AI, allowing students to visualize the topic.
3. Text Summarization: Students can paste a transcript or relevant text, which is then summarized for easier understanding.
4. Question Generation: Based on the summary, the application generates assignment questions for self-assessment.
5. Performance Analysis: After students answer the questions, the system analyzes their responses, identifying strong and weak areas.
6. Personalized Recommendations: The application offers tailored resources and additional videos to help improve understanding in weaker sections.

Example Workflow

• A student enters "Machine Learning" as a topic.
• The application generates a video about machine learning principles.
• The student pastes the transcript of the video and receives a summarized version.
• The model generates a set of questions related to the summarized text.
• After answering the questions, the model evaluates their performance and suggests additional resources for improvement.

Technologies Used

• Frontend: HTML, CSS, JavaScript
• Backend: Flask (Python)
• AI Models: Hugging Face Transformers for text summarization and question generation
• Video Generation API: [Insert your video generation API details here]
• Database: [Specify if any database is used, e.g., SQLite, MongoDB]

Installation

To run the TutorTeach.ai application locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/JMadhan1/tutorteach.ai.git
   cd tutorteach.ai