Description

How can teachers best connect with students? When teaching, you can't possibly evaluate how every student is finding your lesson quickly and easily. But with TeachWell, you can!

Using Attest's survey platform, we researched the user needs of teachers and lectures to work out what information they wanted from their lessons. 

Student responses to your lessons are shown real-time, and then displayed at the end of the lesson in a downloadable graph, so you can work out exactly where in the lesson students were most engaged or least engaged.

TeachWell:

Uses facial recognition to analyze and track student response to class material.

Uses Microsoft Azure Face technology to analyze facial expressions of students (anger, contempt, disgust, fear, happiness, sadness, surprise) and calculate the dominant emotion.
Generates real-time dynamic graphing of the overall emotion in class.
Generates downloadable report that displays how different emotions varied with time.
Also allows user to examine how each individual student responded to different materials.
Eliminates random personnel processing. Does not recognise faces that have not been trained on.

We used postman to get API calls to collect images detected by the Cisco Meraki camera, and then sends images to Microsoft Azure Face AI endpoint.
Using the Python client SDK provided by Microsoft to process image data - includes identification of dominant emotion, face recognition and tagging, looping snapshot processing every 15 seconds, generating moving average for class engagement.
Sent to front-end real time display developed with React.