https://github.com/jisnap/personalized-student-recommendations
A Python-based solution to analyze quiz performance and provide students with personalized recommendations to improve their preparation.
https://github.com/jisnap/personalized-student-recommendations
Last synced: 11 months ago
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A Python-based solution to analyze quiz performance and provide students with personalized recommendations to improve their preparation.
- Host: GitHub
- URL: https://github.com/jisnap/personalized-student-recommendations
- Owner: JisnaP
- License: mit
- Created: 2025-01-25T07:55:54.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-26T13:57:55.000Z (over 1 year ago)
- Last Synced: 2025-02-26T08:37:40.524Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 573 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Personalized-student-Recommendations
A Python-based solution to analyze quiz performance and provide students with personalized recommendations to improve their preparation.
# Overview
This Flask-based application generates personalized recommendations for students based on their quiz performance. The app fetches data from a JSON API, preprocesses it, trains a recommendation model, and provides improvement suggestions for students.
# Features
Fetches quiz performance data from an external JSON API.
Processes and structures data into a Pandas DataFrame.
Trains a machine learning model to generate personalized recommendations.
Provides suggestions to students for improving their performance.
RESTful API to interact with the recommendation engine.
# Requirements
Python 3.8 or higher
Flask
Pandas
Scikit-learn
Requests
Anaconda (optional, for managing environments)
#Installation
Clone this repository:
```python
git clone https://github.com/your-username/student-recommendations-app.git
cd student-recommendations-app
```
Create and activate a virtual environment (optional but recommended):
```python
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
Install the required dependencies:
```python
pip install -r requirements.txt
```
File Structure
```markdown
.
├── app.py # Main Flask application
├── Data/
│ ├── datapreprocessing.py # Helper functions for data processing
│ ├── fetched_data.json # Sample JSON data file
│ ├── student_performance.csv # Processed data
├── src/
│ ├── recommendation.py # Recommendation model logic
├── templates/
│ ├── index.html # HTML template for the app
├── static/
│ ├── styles.css # Static CSS files (optional)
├── README.md # This file
├── requirements.txt # Dependencies
```
Usage
Start the Flask application:
```python
python app.py
```
Open your browser and navigate to: http://127.0.0.1:8080/