Discriminating between students with high and low academic burnout based on their academic procrastination and loneliness


The aim of this study was to discriminate between students with high and low academic burnout based on their academic procrastination and loneliness. It was a causal-comparative research. The research population consisted of all students studying in Ahar public and private schools in the 2015-2016 academic years. The research sample consisted of 332 students who were selected based on Krejcie and Morgan table, and using cluster sampling method. Data were collected using procrastination assessment scale (Solomon & Rothblum, 1989), University of California Los Angeles loneliness scale (1980) and the Maslach burnout inventory-student survey (2002) and they were analyzed using software 16 SPSS and the statistical tool of discriminant analysis. The results of the discriminant analysis, led to a significant recognition function. According to this function, the component of preparing articles had the highest ability in discriminating between the groups.  Subsequent discriminative components included preparation for the exam, preparation for homework and the variable loneliness, respectively. Also, the results of the discriminant analysis showed that most students with low academic burnout were correctly discriminated from the other students with the highest percentage of detection (84/3%) and 80/2% of the two groups' students were properly reclassified according to the obtained function. The results of this reclassification indicated the ability of these variables in discriminating between students with different academic burnout levels. Therefore, in educational programs for the prevention and reduction of academic burnout among students, academic procrastination and loneliness needs special attention.

* MA in educational Psychology, Graduated from Āzarbāijān Shahid Madani University, arashshahbaziyan@yahoo.com
‌‌** (PhD), Āzarbāijān Shahid Madani University, (Corresponding Author), Mesrabadi@azaruniv.ac.ir
‌*‌*‌* (PhD), Āzarbāijān Shahid Madani UniversityFarid614@azaruniv.edu