Abstract:

The main goal of this study is to analyze the effects of different aspects of family background such as family income, parental education, parental job, the number of family members, and the socioeconomic status of parents on educational performance of applicants in Wide Entrance Examination (WEE): university admission system in Iran.

The Iranian university and college admission system involves prospective students listing up to one hundred majors in order of their preferences in the application. Admission at universities is offered to the applicants based on both their preferences and their entrance examination results.
This research deals with specific WEE data created and collected over 10 years by NOET (National Organization of Educational Testing). In order to investigate the effects of family background factors and other related variables on educational performance (entrance examination grades) we apply various statistical methods and data mining algorithms such as ANN (Artificial Neural Network), C&RT (Classification and Regression Tree), and regression analysis. We do so as we consider the complete data set which consists of roughly six million WEE applicants' information from three different main testing groups (mathematics and physics, empirical sciences, and human sciences).

The results of this analysis show that parental education, parental job and the socioeconomic status of family have a large effect on entrance examination grades and as a result on university and college acceptance. Meanwhile, the number of family members and age of applicants have a negative effect. Moreover, the proportion of acceptance in universities for the high social class families is more than the proportion of candidates in the other categories. In other words, applicants who come from higher social classes have a significantly better chance of getting admission at a university.

Results of this study provide a better understanding of the factors that could have significant impact on the applicant’s admission, and as a result on the higher education achievement. Such insights can assist those responsible in making decisions about conditions and quotas applied for future exams..

Keywords:

Socioeconomic Status, Family Background, Educational Performance, Total Grades, Nationwide Exam, Data Mining Techniques.