Development and deployment of an advanced teaching satisfaction evaluation system

In a rapid changing education landscape, the assessment of teaching satisfaction plays a crucial role in improving educational quality. This paper elaborates the design and implementation of a data-driven teaching satisfaction evaluation system aiming at providing a comprehensive assessment of teaching quality by collecting and analyzing the student feedback data with machine learning algorithms. The system covers most of the real teaching scenarios from satisfaction surveys to data processing and from result analysis to report generation. By testing in a vocational training institution with more than 1,2500 students more than one academic year, the system proposed could effectively reflects student satisfaction level satisfaction improvement and provides valuable references for teaching improvements. Moreover, this research offers educational administrators an efficient tool for assessing teaching quality, which is of great significance for enhancing educational standards.