Fuzzy Logic Based Expert System for Academic Staff Evaluation and Progress Monitoring

Abstract

Academic teaching performance is recognized as a top instrument in reducing student dropout. This paper proposes a fuzzy logic based expert system which helps the teachers perform their own evaluation of academic teaching and research activities, in order to match them to requirements for each study cycle (introductory, specialization, master). The developed expert system also offers a way of monitoring the progress of teachers’ performances and to provide additional explanations about which aspects still need improvement. The system was tested using artificial data. The results show the most appropriate teacher for every study cycle.