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

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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.

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Technologies Used

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

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Project Structure

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

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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

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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.

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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

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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

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License

This project is created for educational and academic purposes.