Predict the academic status of admitted applicants based on educational and admission data using data mining techniques
Education is one of the main issues in human society. The promotion of the educational level of society will stimulate its growth. Nowadays, due to increasing the amount of information stored in the databases, it has caused them to be more valuable as an asset. Data mining is one of the methods of extracting information from raw data. Data mining utilizes data analysis tools to discover valid patterns and relationships that have been unknown until now.Extracted knowledge helps institutions improve their teaching methods, learning process, and decision making. These improvements will ultimately lead to an increase in studentschr(chr('39')39chr('39')) performance and overall educational outcomes.This study aims to predict the educational status of students who intend to continue studying for a bachelorchr(chr('39')39chr('39'))s degree. Given that the Ministry of Science intends to eliminate the entrance test and on the other hand, this test serves as the main way to enter the university; Universities will face the problem, what are the criteria for selecting students?In this study, we try to provide a better choice of students using data mining techniques and tools, information received from students (register information) such as average, personal information, and comparison with graduate, Dropout and fired students.
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