ABSTRACT
Following the COVID-19 pandemic, as the user-base of online synchronous communication systems skyrocketed, the shortcomings of synchronous online learning systems became more visible. Any attempt to overcome these shortcomings should be considered worthwhile due to the magnitude of potential impact. Improving the quality and addressing the shortcomings of online education is more important than ever. The goal of this multidisciplinary study that lies in the intersection of the fields of Education Science and Computer Science is to address a number of challenges of online education by incorporating AI. This study focuses on developing methods and means to ethically collect and use non-verbal cues of participants of online classrooms to assist teachers, students, and course coordinators by providing real-time and after-the-fact feedback of the students’ learning-centered affective states. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).