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HackOff 3.0-Team Push That Code

Knewton Ed - Smart AI-Digital Based Solutions for Education Analysing

Abstract

The impact of pandemic COVID-19 is observed in every sector around the world. The education sectors of India as well as world are badly affected by this. It has enforced the world wide lock down creating very bad effect on the students’ life. Around 32 crore learners stopped to move schools/colleges and all educational activities halted in India. The outbreak of COVID-19 has taught us that change is inevitable. It has worked as a catalyst for the educational institutions to grow and opt for platforms with technologies, which have not been used before. The education sector has been fighting to survive the crises with a different approach and digitising the challenges to wash away the threat of the pandemic.

The Problem

The COVID-19 pandemic has had a number of consequences in different Sectors, one of which was the Education Sector.

Unfortunately,Due to lack of physical interaction within school premisis , students and teachers had tried to adopt certain ways to address their concerns in virtual way.Whether it was traditional way of dealing with exams by faculties or students , or how students interacted with their teachers regarding their doubts , aspirations ,concerns , Virtual Distance is something which has been a major problem in this sector and not that effective as compared to physical and remote way!

The Solution

Keeping all the conerns in our mind , we have tried to develop a smart AI Based digital Platform Using Machine Learning /AI and Web based skills to make a secure web application , which aims to analyze the user's information,it can be a Faculty or Student. Using Appropriate Tech Stack , this app tries to analyse and solve the problem of online assignment upload, to check plagiarism of the assignments sent by the students, the teacher can check if any student had copied the assignments or not through our ML model, to give a short summary and finding the main key points in the assignment so that it could save time for the teacher and student counselling where student can predict a career or predict dropout rate using our ml model.

Tech Stack:

Machine Learning /AI Based Tech Stack :
  1. Natural Language Processing
  2. NLTK
  3. CountVectoriser
  4. Tfidf Transformer
  5. Gensim
  6. Spacy
  7. Scikit-Learn
  8. XgBoosting
  9. Decision Trees
  10. Pytessearct-OCR Engine
  11. OpenCV
Frontend Tech Stack :
  1. Html and CSS
  2. ReactJS
Backend Tech Stack :
  1. NodeJS
  2. ExpressJS which is a NodeJS Framework
  3. Flask which is a Python Framework
Database Tech Stack:
  1. MongoDB

Features:

  1. Pdf Optical Character Recognition based text Extraction [OCR]- Using Pytesseract and Opencv and Pdf-plumber libray, Text Can be extracted by the pdf documents.
  2. Summarizer and keyword extraction- Analyses Pdf 's Text and returns summary and main points and keywords of student's answer sheet.
  3. Plagirism Detection - Using Natural Language Processing Techniques and cosine similarity , our app can identify whether two students uploaded documents content have been plagirised or not .
  4. Auto Evaluate - Using Narural Language Processing Techiniques , this app can automatically evaluate a student's answer sheet and can evaluate it against original answer ky provided by faculty and can calculate marks easily.
  5. Student Dropout- Using Machine Learning , our app can easily predict whether a particualr student is on verge of getting arrears or dropouts.This can help him to connect with suitable faculties who mught help them to prepare for the fortcoming exams accordingly.This way , Faculty can help them remotely address their concerns and doubts
  6. Student Counsel- Using Machine Learning , our app can easily help a student identify which type of a job role would be suitable for him , based on inputs as in skills and experience received by user.This way , Faculty can help them remotely address their concerns and doubts reagrding their future aspects and can help them to train and prepare in suitable manner.
  7. Fully Secured - Uses a Autheticated Login Backend For Teachers and Students Separately to keep track of their respective data.
  8. Stores All the Previous Logs- Marks , Reports in Database and can be easily retrieved using this App (PyMongo).


Demo :


Challenges we ran into:

1.To create reliable api using Nodejs
2.To Store and retrive data from database
3.To manage and display various datas across users
4.Creating a reliable ml model
5.Finding Proper Datasets
6.Hosting Ml models
7.Creating a Great UI Exp

CONCLUSION:-

This can help to increase and strengthen interaction and communication between faculty and student more efficiecntly and can help to deliver and tackle complex solutions more easily !

Contributors

Harsh Shaw

Harsh Shaw

Harsh Sharma

Harsh Sharma

Rishabh Abhani

Rishabh Abhani

Sulaksh Sharma

Sulaksh Sharma

Preetam Sarkar

Preetam Sarkar

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This repo is for hackoff 3.0

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  • JavaScript 45.7%
  • Python 37.0%
  • CSS 9.6%
  • HTML 7.7%