Abstract

Fulfilling the demands of industry 4.0, teachers are required to improve the quality of their profession. A quality profession will not be achieved if the teacher does not have a qualified and prosperous person. By utilizing technological developments, teachers can monitor and diagnose self-wellbeing conditions on an ongoing basis. The encounter of educational science, this psychological trait with Artificial Intelligence, is called Positive Education. One form of it is self-diagnostic that can diagnose psychological conditions to produce optimal quality. Teacher wellbeing can be defined as a condition of teacher emotional and cognitive evaluation of their life, which is related to happiness, peace, fulfilment, and life satisfaction. This study aims to develop a research instrument, namely teacher wellbeing that optimizes the quality of teacher's work life for face recognition-based applications. The research method used is the Neuroresearch method to instrument calibration. The result of the research is an evaluation of teacher wellbeing instrument that optimizes the quality of teacher's work life for face recognition-based applications. Teacher wellbeing can be defined as a condition of teacher emotional and cognitive evaluation of their life, which is related to happiness, peace, fulfilment, and life satisfaction. So that the teacher wellbeing instrument is built by three dimensions, namely cognitive, emotional and behaviour. This study contributes to the literature on facial recognition applications, especially regarding teacher wellbeing.