Improving Teacher Performance using Data Mining

Abstract

This study examines the factors associated with the assessment of teacher's performance. To improve the teacher performance, good prediction of training course that will be obtained by teacher in one way to reach the highest level of quality in Teacher performance, but there is no certainty if there are accurately determine Teacher advantage and increase its efficiency through this session. In this case the real data is collected for teachers from the Ministry of Education and Higher Education in Gaza City. It contains data from the academic qualifications for teachers as well as their experience and courses. The data includes three years and questionnaire contains many questions about the course and length of service in the ministry. We propose a model to evaluate their performance through the use of techniques of data mining like association, classification rules (Decision Tree, Rule Induction, K-NN, Naïve Bayesian (Kernel)) to determine ways that can help them to better serve the educational process and hopefully improve their performance and thus reflect it on the performance of teachers in the classroom. In each tasks, we present the extracted knowledge and describe its importance in teacher performance domain.