Multimodal Teaching and Learning Analytics for Classroom and Online Educational Settings

Abstract

Automatic analysis of teacher student interactions is an interesting research problem in social computing. Such interactions happen in both online and class room settings. While teaching effectiveness is the goal in both settings, the mechanism to achieve the same could differ in different settings. In order to characterize these interactions multimodal behavioral signals and language use need to be measured, and a model to predict effectiveness needs to be learnt. These would help characterize the teaching skill of the teacher and level of engagement of students. Also, there could be multiple styles of teaching which can be effective.