Designing and Implementing the Higher Education Development Fuzzy Expert System in Iran


Authors

Shahin Homayoun Arya - Shahid Beheshti University, Tehran, Iran, Faculty of Education and Psychology. Mahmood Abolghasemi - Shahid Beheshti University, Tehran, Iran, Faculty of Education and Psychology. Ali Mohammad Ahmadvand - Imam Hossein University, Tehran, Iran, Faculty of Engineering. Ebrahim Salehi Omran - Mazandaran University, Babolsar, Iran, Faculty of Humanity and Social Science.


Abstract

Due to the fact that the quantitative development in higher education requires, on one hand, macro investments and challenges in order to provide new resources and making capacity, and on the other hand requires setting goals and long qualitative activities so that it shall not lead to reverse results; therefore, this matter should be conducted by programming and paying comprehensive attention to different aspects and indexes and this matter has caused educational and providential programming in the higher education future development to become inevitable. The goal of this paper is to design a fuzzy expert system for the quantitative development of higher education in Iran. Seeing as how the issuance of required licenses are conducted intensively at the Ministry of Sciences, Researches and Technology; therefore, this system is able to help as a decision- making- aid to the higher managers of this Ministry in making decisions regarding the quantitative development of higher education with regard to many elements such as: the structural space of the university, the number of faculty members, the University characteristics and facilities by considering the upper hand documents of higher education development. Designing this program consists of six steps. At the first step, the registered criteria are excavated on the basis of analyzing the content of the upper hand documents and distributing questionnaires among the higher education expert. At the second step, the ranges of alterations of lexical items are determined and at the third step they are changed to fuzzy amounts. At the fourth step, the fuzzy lexical base is compiled using the opinions of the experts and in the fifth step the syllogism engine of the programming system is executed and at the final step defuzzification is conducted. Eventually, the programmed system is assessed by the system output examination method and is accredited by case study. The concluded results are implementing and assessing the corroborated system of the accuracy of performance of the programmed system.


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