Learning Aid Generator - VARK

Team Name	Team members	Product version	Product document	Product demo	User guide	Source code	Developer guide
ThirdWheel	Anushka Ghei, Arvin Nooli, Anshul Ranjan, Ashlin Furtado, Ashwin Ragupathy	0.5	Product document	Product demo	User guide	Source code	Developer guide

Product Document

• Problem Statement

  According to a perception study, 82% of Indian schools reported that students having a short attention span was a prevalent problem. The present applications are somewhat erratic, hence a need for a more precise platform that offers options for training, growth, and education in addition to assisting people in understanding their specific learning styles to maximise the learning potential in students.

• Our Solution

  Everybody learns differently. Some students respond better to certain instructional methods than others.

  The VARK model effectively identifies and classifies people into four learning styles visual, auditory, reading/writing, and kinesthetic. Then, it generates personalised learning content that matches your results, from the concept fed to the system.

  

  Moving forward we even created a discord server customised especially according to the learning groups.

• Tech Stack

  • Python
  • Machine Learning
  • HTML, CSS, JS
  • VR- Unity

Product Demo

• Demo video : demo1 demo2
• Live application : click here

User Guide

• To launch the website click here
• The take test button on dashboard would take you to a self assessment which will help you recognise your learning type .
• On the basis of your learning type we have provided different features and ML algortithms to help students and learners excel.

Developer Guide

• Our solution is platform independent and is hosted on the github servers.
• To set it up we require to have python environment and other project dependencies installed.
• Make sure that you have Python 3 and pip installed.

1. Clone the repository

       $ git clone https://github.com/Anushkaghei/ThirdWheel-Challenge-4.git
       $ cd ThirdWheel-Challenge-4
   

2. Install the project dependencies

       $ pip install -r requirements.txt
   

You've now set up the project successfully. Run index.html on your favourite browser to see the results.