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Multilingual STEM Teaching Assistant

Overview

Multilingual STEM Teaching Assistant is an AI-powered educational platform built using Streamlit and Groq API. It helps students and teachers learn STEM concepts through AI-generated explanations, quizzes, homework, lesson plans, and concept diagrams.

The application supports multiple languages including:

  • English
  • Tamil
  • Hindi
  • Japanese

Features

AI STEM Tutor

  • Explains STEM concepts in simple and detailed formats.
  • Supports Beginner, Intermediate, and Advanced difficulty levels.
  • Generates responses in the selected language.

Slides Generator

  • Creates educational slide content.
  • Generates structured slide titles and bullet points.

Homework Generator

  • Creates homework questions based on selected topics.
  • Supports different difficulty levels.

Quiz Generator

  • Generates quiz questions with answers.
  • Useful for self-assessment and classroom activities.

Lesson Planner

  • Creates complete lesson plans including:

    • Learning Objectives
    • Introduction
    • Teaching Content
    • Activities
    • Assessment
    • Summary

Concept Diagram Generator

  • Generates concept relationship diagrams using NetworkX and Matplotlib.

Student Progress Tracking

  • Stores recently learned topics.
  • Displays topic learning history.

Performance Prediction

  • Predicts student performance using a machine learning model.

Teacher Dashboard

  • Displays analytics on learned topics.
  • Provides visual insights using charts.

Technologies Used

  • Python
  • Streamlit
  • Groq API
  • Requests
  • Pandas
  • NumPy
  • Scikit-Learn
  • NetworkX
  • Matplotlib

Project Structure

Multilingual-STEM-Teaching-Assistant/
│
├── app.py
├── style.css
├── student_data.json
├── requirements.txt
├── .gitignore
└── README.md

Installation

Clone the repository:

git clone https://github.com/yourusername/multilingual-stem-teaching-assistant.git

Move into the project folder:

cd multilingual-stem-teaching-assistant

Install dependencies:

pip install -r requirements.txt

Create:

.streamlit/secrets.toml

Add your Groq API key:

GROQ_API_KEY="your_groq_api_key"

Run the application:

streamlit run app.py

Deployment

This project can be deployed using Streamlit Community Cloud.

  1. Push the project to GitHub.
  2. Open Streamlit Community Cloud.
  3. Create a new app.
  4. Select the repository.
  5. Set app.py as the main file.
  6. Add the Groq API key in Streamlit Secrets.
  7. Deploy the application.

Future Enhancements

  • Voice-based learning assistant
  • PDF export for notes and lesson plans
  • Student login system
  • Learning analytics dashboard
  • Interactive whiteboard
  • AI-generated study notes
  • Real-time classroom collaboration

Author

Daniel J

Bachelor of Engineering in Computer Science and Engineering

Loyola Institute of Technology, Chennai

LinkedIn: https://www.linkedin.com/in/daniel-j77

GitHub: https://github.com/daniel-j77

License

This project is created for educational and academic purposes.