Teachfinity

Teachfinity is an e-learning platform that aims to improve upon existing Virtual Learning Environments (VLE) by making them more effective and engaging forthe students as well as less taxing on the faculty. In the midst of a pandemic, educational institutions of all levels have moved from classroom

Project Title

Teachfinity

Project Area of Specialization

Computer Science

Project Summary

Teachfinity is an e-learning platform that aims to improve upon existing Virtual Learning Environments (VLE) by making them more effective and engaging forthe students as well as less taxing on the faculty. In the midst of a pandemic, educational institutions of all levels have moved from classroom learning to online learning to minimise exposure to the COVID-19 virus. Due to this shift, quality of education has decreased immensely, our goal here then is to minimise that loss in quality while still protecting our loved ones from the virus.Teachfinity makes e-learning efficient for students of all categories may it bechildren at school level, or college, or even higher level students. It also providesfacilities not only to teachers at educational institutes but can also connect a simple home tutor to their students. By binding the supremacy of videos and visual sand attractive designs we can make e-learning effective yet fun for students of alllevels.

Project Objectives

Teachfinity provides and engaging and effective VLE for both teachers aswell as students. We think VLE could be improved by bringing the students andthe faculty closer to each other and that could be done through better communication. In a virtual environment it is certainly hard to communicate well but usingtechnologies such as NLP and Computer vision we think we can bring them closerand simulate a real class environment. By creating ways that would motivate thestudents to study harder, we can make online learning effective and fruitful.Interesting features like class participation that measure every students participation in class and also generates overall class mood motivate the students to participate during the class thus solving the lack of engagement problem duringonline classes. Similarly the quiz generator is available not only to save time for teachers but also helps students prepare for their tests. Plagiarism detector alsoeases the work for the teacher and encourages students to come up with their own answers. All these requirements make e-learning effective.

Project Implementation Method

One could describe our project as a VLE videoconferencing platform wherestudents can communicate with their teachers in real time and chat with each other.The platform will make sure the student stays put during their lecture and will no-tify the faculty of the overall mood of the class. It will also measure participationof the student in a class using NLP and speech recognition. Students can be restassured their classes are not clashing with each other as our time table algorithmwill make sure you will be notified if there ever is one.The faculty would be able to store all their files inside the ’class cabinet’, anNLP model would then read the files and suggest useful resources to the students.The project would be able to notify students and the faculty of any peer to peerplagiarism. Students can prepare for tests or exams on their own by using the Quizengine which will generate a quiz based on the notes you feed

Benefits of the Project

•Allows faculty to teach their students and see their progress in real time byvideo conferencing and chatting.

•Actively motivates the students to listen to the lecture and contribute to the4discussion.

•Quiz generation saves time and helps student prepare for the courses on theirown.

•Plagiarism detection motivates student to come up their own solutions with-out getting outside help.

•Class cabinet provides an in-built storage system where teachers can storetheir lecture materials and the students can then read it on their own accord.

•An NLP model using a webcrawler finds videos and articles from the internetthat might help understand the course material better by reading through thelecture notes stored in the Class cabinet.

•All-in-one platform so you do not have to waste time switching programs and apps.

•Prevents clashing of the students’ classes through the scheduler feature.

Technical Details of Final Deliverable

**Due to the limitation of the website, image upload of the system design is not possible**

The main system is built on top of MERN platform, the special features such as the NLP model will be available thorugh an external microservice built in Python. 

The video conference platform is built on top of the Jitsi platform on top of which we are making our own adjustments and additions such as the computer vision featues required to keep the students in check.

Final Deliverable of the Project

Software System

Core Industry

Education

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Quality Education

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com