Intelligent Techniques for Instructor Performance Evaluation

In this work, intelligent techniques of keyword spotting sub-system and text mining are used for instructor performance evaluation. The proposed system aims to convert instructor's speech (system inputs) to text, and then analyzes the text to extract related knowledge for instructor evaluation that depends on a set of criteria such as (example, communication, positive concepts, contents and jokes), finally provides advice to the instructor (system outputs). The proposed system uses Mel Frequency Cepstral Coefficient (MFCC), Euclidean Distance (ED) techniques to convert speech to text. Finally, this study proved the effectiveness of the proposed system also can improve reliability and efficiency of instructors¿ performance; provide the basis for performance improvement that will affect students¿ academic outcomes.