“The most important thing that the teachers can do while they are meeting online with the students is to connect with them emotionally” ~Ruxandra Mercea

Learning research indicates that people learn better in the presence of some emotional connection—to the content or to other people. Creating this emotional connection is particularly challenging in the online classroom, where most communication is asynchronous and lacks many of the emotional cues of the face-to-face environment. Teachers with autism can need special aid to recognize the emotions of their students. Similarly, students with autism and expressive introversion need aid to express themselves to the teachers in online classes. Also, women in STEM can be promoted by supporting our girls at the right time when they need help and clarity in these domains to grasp in-depth knowledge straight from elementary-level education.

This is a website empowered by Computer Vision based Sentiment Analysis to help assess the emotions and psychology of a child, especially when they attempt to solve challenging problems or try to understand advanced concepts. Based on the emotions of the child, if they show signs of under-confidence, irritation or anger, we provide systematic help by detailed analysis over a period of time set by the teacher and sending the detailed report of the student study session to the teacher. This helps the teacher understand the areas where the student was feeling uncomfortable in understanding and using the drill-down reports of the student study sessions the teachers can ensure that the student's learning rate does not fall down.

The front end of the web application is built with HTML, CSS and Javascript. The emotion recognition is built using ml5.js face API to do real-time face detection through a webcam. I implement detection rectangle, face landmarks, and displaying emotion estimation. The detailed data analysis report is sent to the teacher on a timely basis(as decided by the teacher) via SMS which is implemented using Twilio SMS API using PHP.

1. NLP based Sentiment Analysis
2. Graphical Data Visualisation dashboard for teachers of the student emotions per study session

You'll be making your own copy of the "TeachersHelpGirlsJoinSTEM website starter" repository so you have your own project to customize. A "fork" is a copy of a repository. So select "Fork" atop the github/somya-15/TeachersHelpGirlsJoinSTE.

Once you've found a home for your forked repository, it's yours. You're the owner, so you're ready to publish, if you wish.

Install in your local development environment If you want to manage your website in a local web development environment, you'll be using PHP as well.

Once you've found a home for your forked repository, clone it.

If you installed git you can clone the code to your machine, or download a ZIP of all the files directly.

Download the ZIP from this location, or run the following git command to clone the files to your machine:

git clone https://github.com/somya-15/TeachersHelpGirlsJoinSTEM.git

• Once the files are on your machine, open the Quiz-master folder in Visual Studio Code.

• With the files open in Visual Studio Code, press the Go Live button at the bottom of the window to launch the files with Live Server.

The following tools help make easier to work with sample code.

• git: A tool for managing source code
• Visual Studio Code: A source code editor
• Live Server: A simple web server utility for Visual Studio Code

demo link- https://youtu.be/50_ZxcMAOaQ