Evaluating the quality of teaching in higher education institutes using clustering approach and set pair analysis

Teaching Quality Evaluation is an important process in all higher education institutes and is carried out after each semester. However, it is not fully reliable as students don´t always fill the form with no bias whatsoever. The problem is too complex to be solved using present evaluation system. So, the main purpose of this paper is to show how to use machine learning techniques so that the system can identify the nongenuine responses and an effective evaluation model will be set up using set-pair analysis. Efforts are made to remove the vagueness in the results obtained. By forming clusters and applying fuzzy techniques, the results are analyzed and the implementation will be shown to demonstrate the efficiency of the proposed techniques.