Abstract

Existing information on artificial intelligence (AI)-based facial emotion recognition (FER) is not easily comprehensible by those outside the field of computer science, requiring cross-disciplinary effort to determine a categorisation framework that facilitates exploration of the impact this technology has on users. Most proponents classify FER in terms of methodology, implementation and analysis; relatively few by its application in education; and none by its users. This paper is concerned primarily with users of FER for education, particularly teachers. It proposes a three-part classification of these teachers, by orientation, condition, and preference, based on theoretical traditions in educational psychology and philosophy, as well as on teacher surveys. It also compiles and organises the types of FER found in or inferred from the literature into technology and applications categories, as a prerequisite for structuring the proposed teacher-user category. This work has implications for the understanding of the relationship between teachers and FER among its proponents and critics, as well as for education practitioners.

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