A novel hybrid method for better evaluation: Evaluating university instructors teaching performance by combining conventional content analysis with fuzzy rule based systems

Even though engineering and applied sciences deal with numerical data, they have successfully implemented fuzzy logic by using fuzzy rule based (FRB) systems by verbalizing data. On the other hand, social sciences such as sociology, education and physiology transform verbal type data into numerical values by using Likert type scale. Despite the fact that fuzzy set theory deals with verbal data very powerfully, social science fields in general have avoided to implement it to their verbal data up until now. One of the most active research areas in education field which generates verbal data is student evaluation of teaching (SET) questionnaires which are related to Total Quality Management applications in most of the competitive universities in the world. In this paper, we propose a novel hybrid method, which combines conventional content analysis (CCA) method and FRB systems and this new hybrid method is more suitable for the verbal data obtained from SET questionnaires. This novel CCA-FRB (conventional content analysis based fuzzy rule based systems) method uses a sample of 138 junior students from Gazi University in Turkey to implement the proposed method.