Application of Facial Emotion Recognition in Teaching-Learning Process for Quality Assessment and Enhancement

The existing literatures based on AI-facial emotion recognition (FER) presents a challenge for non-specialists, necessitating a collaborative inter-disciplinary effort to establish a comprehensive framework that enhances comprehension of this new technology and its implications for the end-users.Prevailing categorizations principally revolve around methodological, implementation, and analytical aspects, along with limited attention to its educational applications as well as user-centric perspectives.This current study primarily focuses on potential educators who prefer to work upon FER tools.It introduces a threefold classification of these educators, based upon their orientation, context, and preferences, drawing from established taxonomies of affective educational objectives and relevant theoretical foundations.Also, this research systematically gathers and categorizes the various FER solutions documented in the literature.This work holds significance for advancing the comprehension of the interplay between educators and FER technology among proponents, critics, and end-users.