International Journal of Knowledge Processing Studies

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Fifth Generation University Data-Based Model in Islamic Azad University

Document Type : Original Research Manuscripts

Authors

1 PhD student in Public administration,comparative management and development Qaemshahr Branch,Islamic Azad University, Qaemshahr,Iran

2 Assistant Professor, Assistant Professor ,Department of Managemen, Qaemshahr Branch,Islamic Azad University, Qaemshahr,Iran

3 Assistant Professor, Assistant Professor Department of Industrial Engineering, Qaemshahr Branch, Islamic Azad university, Qaemshahr, Iran

4 Department of Management,Dehaghan Branch,Islamic Azad University ,Dehaghan, Iran

Abstract

This research aims to develop a data-based model for fifth-generation universities. Creating a data-driven model in a university environment is essential in education. The primary mission of higher education is to address the specific educational needs of individuals, as well as the needs of society and its economic development. The study was conducted in both qualitative and quantitative sections. The grounded theory is conducted based on the perspectives of the chancellors of Islamic Azad University. 21 people were selected using snowball sampling techniques. In the following, a six-category model is provided. Analysis was done using NVIVO software. The statistical population in the quantitative section consisted of all professors from Islamic Azad University nationwide. A sample size of 381 professors was selected using the Cochran sampling formula. The research tool was a questionnaire created by the researcher. Then, using the model presented and the suggested pattern fit, the performance of the model is predicted based on the K-Mean method in Weka and RapidMiner software. According to the results, the proposed model was approved by experts. The analysis of structural equations was also confirmed. According to the Waode algorithm model, the highest accuracy was 81%.

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References
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International Journal of Knowledge Processing Studies
Volume 4, Issue 1
December 2023
Pages 79-90
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History
  • Receive Date: 15 March 2023
  • Revise Date: 28 March 2023
  • Accept Date: 27 June 2023
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