The evaluation method of college teachers’ morality considering intelligent emotion recognition and data mining algorithm

Abstract

ABSTRACT The core of teaching consists of four basic values: dignity, truthfulness, fairness, responsibility & freedom. All teaching is founded on ethics – whether it be the teacher-student relationship, pluralism, or a teacher’s relationship with their work. This article combines intelligent emotion detection technology and a data mining algorithm to develop a model for evaluating college professors’ morals to discover an effective way to do so. This study examines the moral hazard game model of concealed behaviors of instructors with overconfidence in four risk preference combinations based on fair fundamental assumptions and comparisons with rational teachers with the same risk preference. In addition, this research formulates the ideal incentive contract for each circumstance. It creates a model of the assessment system of college professors’ morality in conjunction with their real teaching environment. In addition, the simulation model is used to assess the influence of the assessment system on the morality of college instructors. The experimental investigation indicates that the assessment technique of college professors’ morality presented in this work, taking intelligent emotion detection and data mining algorithm into account, has some influence. The model and data mining algorithm are applied to evaluate college teachers’ morality, the method effect is statistically evaluated, and the results showing the superiority of the proposed method are obtained.