https://github.com/swish78/testline-student-analytics-recommendation-system-
A system analyzing quiz performance and providing personalized learning recommendations with insights.
https://github.com/swish78/testline-student-analytics-recommendation-system-
analysis llm python
Last synced: about 1 year ago
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A system analyzing quiz performance and providing personalized learning recommendations with insights.
- Host: GitHub
- URL: https://github.com/swish78/testline-student-analytics-recommendation-system-
- Owner: Swish78
- License: mit
- Created: 2025-01-24T10:17:42.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-26T17:48:15.000Z (over 1 year ago)
- Last Synced: 2025-04-16T01:50:18.055Z (over 1 year ago)
- Topics: analysis, llm, python
- Language: HTML
- Homepage:
- Size: 1.87 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Student Analytics and Recommendation System
A system designed to help students improve their learning by analyzing their quiz performances and providing personalized recommendations.
## Features
- Analyze quiz performance in real-time.
- Track progress over time.
- Identify strengths and weaknesses by topic.
- Provide personalized learning recommendations.
- Interactive dashboards for insights.
## Technology Stack
- **Frontend**: Dash & Plotly
- **Data Analysis**: NumPy, Pandas, Scikit-learn
- **Visualization**: Matplotlib, Seaborn
- **NLP Tools**: Stanza
## Setup Instructions
1. **Clone the Repository**:
```bash
git clone
cd
```
2. **Set Up a Virtual Environment**:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. **Install Required Packages**:
Either from `requirements.txt` (if available):
```bash
pip install -r requirements.txt
```
4. **Set Up the `.env` File**:
Create a `.env` file in the root directory of your project:
```
touch .env
```
Add your **GROQ API key** to the `.env` file in the following format:
```
GROQ_API_KEY=your_groq_api_key_here
```
5. **Run the Application**:
```bash
python main.py
```
5. **View the Dashboard**:
Open dashboard.html on your browser.
## Using the Conda Environment (Optional)
1. Create a Conda environment from the `environment.yml` file:
```bash
conda env create -f environment.yml
conda activate
```
2. Recreate the exact environment for cross-platform compatibility.
## Folder Structure
```
testline/
├── analytics/
│ ├── __init__.py
│ ├── quiz_analyzer.py
│ ├── performance_tracker.py
│ ├── llm_analyzer.py
│ ├── recommendation_engine.py
│ └── visualization.py
├── utils/
│ ├── __init__.py
│ ├── data_loader.py
│ └── config.py
├── models/
│ ├── __init__.py
│ └── schemas.py
├── tests/
│ ├── __init__.py
│ └── test_analytics.py
├── main.py
├── requirements.txt
└── README.md
```
Walk-through: https://testline-walkthrough.s3.us-east-1.amazonaws.com/Screen+Recording+2025-01-24+at+19.13.03.mov