We are a group of researchers working in the field of automated attention estimation of learners in online courses. Recent years have seen a major shift from classroom-based education to an online mode of education. The effectiveness of online classes depends on the attention level of students. Since attention significantly affects the teaching-learning process, online education requires an automated attention monitoring system working in parallel.

Many prior works exist that use eye gaze movements, body movements, and facial expressions to estimate engagement levels. It is an interesting idea to use head movements such as nodding and shaking to estimate the engagement level. In this survey, we want to check whether head movements alone can be used to estimate the engagement level of the students. This anonymous survey aims at understanding the implications of different head movements of learners/students during online classes.