Hierarchical Clustering to Identify Emotional Human Behavior in Online Classes: The Teacher’s Point of View

Abstract

Teacher and student emotions are a fundamental basis in the development of the teaching-learning process. In this paper, we aim to verify whether it is possible for the emotions that are registered on a teacher’s face to constitute emotional vectors and therefore be grouped hierarchically in order to obtain the teacher’s emotional behavior during a virtual class. The experimental process demonstrated that it is possible to obtain an emotional funnel whose result is reflected in a valid hierarchical cluster to identify the set of emotions of a teacher when dealing with a specific topic or in the course of a time window. The work is in progress, but the conclusions it offers are valid enough to be proposed as a basis for recommendations in the teaching-learning process. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.