EXAMINING THE FACTORS AFFECTING THE ACHIEVEMENT ORIENTATIONS OF UNIVERSITY STUDENTS WITH LOGISTIC REGRESSION ANALYSIS

Fazilet Taşdemir

Abstract


In this study, it is aimed to examine the variables that affect the achievement orientation of university students with logistic regression analysis. Gender, age, education program of university students, academic grade point average, order of preference for university entrance, mother's education level and father's education level constitute the independent variables with demographic content. Enjoying learning new information and working in a job in daily life, the desire to prove their current abilities, the desire to be better than their peers in education and business life, academic ideal and physical disability are other independent variables in the research. The “2x2 Achievement Orientations Scale Revised Form” developed by Elliot and Murayama (2008) and adapted into Turkish by Arslan and Akın (2014) was used to determine students' achievement orientations. The population of the research consists of undergraduate students of Recep Tayyip Erdogan University. The sample of the study consists of 155 students determined by the purposive sampling method. In the study, logistic regression analysis was used to determine the variables that predict the success orientation of university students. As a result of the analysis, it was seen that university students' mother’s education level and the desire to prove their current skills were the predictors. It has been determined that the desire to be better than their peers in educational life and the high academic achievement averages are other predictive variables that affect success orientation. It was concluded that other variables (age, gender, preference, father education, enjoying learning new information, having an academic ideal, working in a job in daily life, physical disability) did not make a significant difference on the predicted variable.

 

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achievement orientation, skill, desire, mother's education level, academic achievement, logistic regression analysis

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DOI: http://dx.doi.org/10.46827/ejes.v9i7.4367

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