Development of methods for assessing the performance of teachers using of TUIT-LMS data

Abstract

The use of data mining methods is one of the current trends, which is widely used in finance, health, telecommunications, e-learning and others. Much of the research in the field of education is focused on the assessment of students' performance. But the impact of teachers on the quality of education is also significant. The traditional way to evaluate a teacher's performance is to conduct an assessment survey that takes into account the student's point of view. The article solves the problem of classification of teacher's activity using Generalized Linear Model, Deep Learning, Decision Tree, Random Forest methods based on the results of the survey and textual data based on the survey data conducted in the TUIT-LMS system and determines the reliability of the results.