Abstract:
The present study aimed to examine the effective factors in the rank of national entrance exam of the candidates in state universities and higher education institutes in Iran in the form of a multilevel analysis. Therefore, the data of 5000 candidates was gathered randomly from five experimental groups in the national examination of 2017. The HLM7.30 software was used for multilevel data analysis. The results revealed that among the provinces, there were significant differences in the average national ranks of the candidates in Math, Humanity, Art, and English experimental groups. However, there was not any significant difference in the Science group. In the Math group, the average scores of the third year of high school, the total average of diploma, the entrance quota, and gender determined 58.44 percent of the whole variance of the national rank at level one. In the Humanity group, the average scores of the third year of high school, the total average of diploma, and gender explained 49.22 percent. In the Art group, the total average of the third year of high school, the entrance quota and gender were 15.8 percent; and finally in the English group, the average scores of the third year of high school, the total average of diploma, the entrance quota, and gender were wholly 31.45 percent. There was not any relationship between the age of the candidates as well as the time interval between their graduation and the entrance exam with their national rank. In the Humanity group, only in the local districts and among the other groups, in poles and local districts, the national rank of the candidates was different. In the Science group, only the third year high school’s average scores of the candidates could predict the national rank.
Machine summary:
Abstract The present study aimed to examine the effective factors in the rank of national entrance exam of the candidates in state universities and higher education institutes in Iran in the form of a multilevel analysis.
Keywords: Educational background, Entrance quota, Local province, Multilevel analysis, The national entrance exam Introduction Almost in all countries, students need to pass through different filters in order to enter universities; such filters vary according to country’s educational system or type of authority or the independence of each country (Helms, 2008).
The studies performed in this respect (Bahrami Mokhtari, 2005; Bozorgi, 2000; Dashti, 2008; Noqani, 2007; Noorbakhsh Haeri, 2011; Roudbari, 2005; Sajjadi, Karamdoost, Dorrani, Salehi Moghaddam-zadeh, 2017; Sobhaninezhad, Shahhoseini, Hashemi Khodabandeh, 2013; Tabatabaieyazdi, 2006) show that 48 | P a g e Iranian Journal of Learning and Memory 2018, 1(3) the successful performance on the exam depends both on personal characteristics and contextual features of the candidates.
In order to answer, “what is the relationship between individual level predictors (gender, age, entrance quota, the average scores of the third year of high school, the total average of diploma and the gap between the graduation and exam time) and the national rank?”, the random intercept model with first level predictors was run.
Since the within and between group variance was not significant for Science group, the multiple regression was used in order to predict the national rank of the candidates based on variables like the total average, average scores of the third year of high school, age, and graduation year which is shown in Table 5 and 6.