Attention, Emotion and Attendance Tracker with Question Generation System Using Deep Learning
Harsh Dodiya, Karan Gala, Rounak Jaiswal, Sheetal Chaudhari · 2021 2nd International Conference for Emerging Technology (INCET) · 2021
Learning requires attention, and attention trackers have the potential to be very useful tools for educators. The attention of students can be tracked through various techniques. The promising technologies and related studies on attention, attendance, emotion, and question generation are discussed in this paper. The proposed system tackles the predicament of obtaining the attention of students during online lectures. This system incorporates a camera to capture input image and an algorithm which detects facial features from the image. The expected output is an attention score, emotion report, attendance marking for students using face recognition, and another model for attention evaluation by conducting a test where questions will be generated from the text provided by the teacher. The accuracy attained for the question generator model is 76%. Emotions are determined by the model at 68% precision.