Recognizing student facial expressions: A web application

The project described in this paper investigates the idea of performing emotion analysis of a student population participating in active face-to-face classroom instruction. Machine learning algorithms are employed on live recordings collected by webcams that are installed in classrooms. The visualization application required to be remotely accessible by the lecturer so the application was engineered as a web application. The output, being a timeline of student emotions monitored throughout and in parallel with the lecture, serves to enable the lecturer and other interested parties to improve the delivery of education.