Systems used in Turkey to place students from primary education to high schools have showed constant changes in time. In 2013, Turkish Ministry of Education heralded the process of transition to secondary education with a new system, however it has recently been abolished without fully investigating the impacts it created. Therefore, this study aimed to analyze the student, parent, and school related factors affecting 8^th grade students’ academic achievement in transition exams in state secondary schools during 2015-2016 school year in Eskişehir, and the relationships of these factors by using hierarchical linear modeling in a casual comparative type of research.

The study aimed to answer the following research questions:

1-    Does the school effectiveness vary according to the socioeconomic status of the neighborhoods in which schools are located?

2-    Is there a significant difference among schools in terms of students’ Transition Exam scores?

3-    Does the school effectiveness variable in Level 2 predict Transition Exam scores?

4-    Do the student and parent related variables in Level 1 predict Transition Exam scores?

5-    Are the Level 1 variables related with school effectiveness?

6-    Does the school socioeconomic status variable in Level 2 predict Transition Exam scores?

7-    Are the Level 1 variables related with school socioeconomic status?

Out of 49 state secondary schools in the two districts (Odunpazarı and Tepebaşı) of Eskişehir city, schools were stratified based on the socioeconomic status of the neighborhoods they are located in as low (Low SES), average (Average SES), and high (High SES). In order to determine these strata, current values listed in the document prepared by Odunpazarı Municipality and named as “Current Values of the Minimum Land Properties and Building Plots to be Used in 2010” was taken into consideration. Based on the values in the document, mean values of the neighborhoods were calculated by computing the current values of each street in Odunpazarı and Tepebaşı Districts. After these calculations it was seen that the neighborhoods having 300 ₺ or over current values are High SES, neighborhoods having 150-299 ₺ current values are Average SES, and neighborhoods having 150 ₺ or below current values are Low SES neighborhoods. To show the clear picture of the situation, 3 schools from High SES and 3 schools from Low SES neighborhoods were randomly selected. From these schools, 667 students and their parents as well as 211 school leaders and teachers participated in the study. Data were collected by means of three instruments developed by the researcher. School Effectiveness Scale was used to determine the factors reflecting school effectiveness through the eyes of teachers and administrators. Secondly, Student Questionnaire filled by 8th grade students in selected schools consisted of items that mention about personal variables which might have an influence on the difference of exam scores. Third instrument to collect data for the study, Parent Questionnaire, was used to determine the parental factors that might have an effect on scores. Psychometric qualities of each instrument were calculated prior to the actual study and pilot studies were conducted. Hierarchical Linear Model was preferred for analysis since the data were collected from different strata and as the data set reflected a nested and hierarchical structure

The results showed that schools located in high SES neighborhoods were more effective. The first HLM analysis indicated that 37% of the variation in the exam scores resulted from schools (and 63% from student and parent related Level 1 variables). School effectiveness was responsible for the 85 % of variation in scores in Level 2, and the variables included in Level 1 explained the variance up to 84 %. In the second HLM analysis it was found that school socioeconomic status created a 76 % variation in scores. Although cross interactions in both analyses were significant, the percentage of their explained variance was rather low. The findings of this study could be compared with the outcomes of previous systems or the new systems which will be launched in the future in order to determine the strengths and weaknesses of each and to make reasonable steps to improve educational decisions in terms of inclusion or exclusion of students.

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