The landscape of EdTech faces several challenges including lack of engagement, limited personalization, and insufficient human interaction, among others. To address these issues, Edufrent aims to revolutionize education by leveraging the power of AI to personalize learning, provide intelligent support, and create an adaptive educational environment.
- Lack of engagement
- Limited personalization
- Insufficient human interaction
- Technological barriers
- Lack of hands-on experience and self-discipline
- Limited feedback and assessment
- Overemphasis on content delivery
We aim to fill the gap in EdTech by introducing innovative solutions, including:
- Personalized learning experiences
- Intelligent virtual assistants
- Adaptive assessments
- Experiential learning opportunities
- Intelligent content generation
- Learning analytics
Edufrent incorporates the following key features:
- Personalized curriculum generator
- Intelligent virtual assistants
- Adaptive assessments
- Learning analytics and insights
- Interview and Viva voce preparation bot
Our project leverages:
- OpenAI's GPT-3.5 for implementing AI-powered solutions
- Streamlit for an interactive user interface
Future upgrades for Edufrent will include:
- File upload feature for generating questions from the content of the specific file uploaded
- Bionic reading for speed reading and ADHD support
- Collaboration features with friends
- Real-time audio support for confidence enhancement
Edufrent utilizes Generative AI and Streamlit to create an application that helps in personalized curriculum development and adaptive learning based on individual capabilities and preferences. It also features assessment and interview bots to provide feedback and identify areas for improvement.
- Create a new directory:
mkdir dir_name
- Create a virtual environment:
python3 -m venv venv
- Activate your virtual environment.
- Clone the GitHub repository:
git clone https://github.com/GaganaMD/Edufrent/
- Install dependencies using:
pip install -r requirements.txt
(ensure you are in the same directory asrequirements.txt
). - Create an environment file and add your OpenAI API token.
- Run
app.py
using Streamlit for the first set of features. - Run
app2.py
using Streamlit for the remaining features.