Prediction of Academic Burnout Based on Academic Self-Efficacy among Lower Secondary School Students in Kavar City
محورهای موضوعی : Islamic EducationKamal Mohammadzadeh 1 , MohammadReza Keshtkar 2 , Fatemeh Khobyari 3
1 - PhD in Curriculum Planning, Marvdasht Azad University
2 - Master's student in Educational Sciences, Marvdasht branch, Islamic Azad University, Marvdasht, Iran.
3 - Master's student in Educational Sciences, Marvdasht branch, Islamic Azad University, Marvdasht, Iran.
کلید واژه: Academic Burnout, Academic Self-Efficacy, Students.,
چکیده مقاله :
Introduction: The aim of the present study was to predict academic burnout based on academic self-efficacy among lower secondary school students in Kavar City.
Research Methodology: This research is applied in terms of purpose, and descriptive-correlational in terms of nature and methodology. The statistical population included all lower secondary school students in Kavar, totaling 2,700 students. Using a multi-stage cluster sampling method, the researcher selected four schools from the lower secondary level, and from each school, two classes were randomly chosen—resulting in a total sample of 240 students. The data collection tools included two questionnaires: the Academic Self-Efficacy Questionnaire and the Academic Burnout Questionnaire. For data analysis, descriptive statistics (mean and standard deviation) and inferential statistics (stepwise regression and Pearson correlation coefficient) were used.
Finding: The findings indicated that students' academic self-efficacy is a significant predictor of academic burnout. Moreover, the dimensions of academic self-efficacy were also found to be significant predictors of students' academic burnout.
Introduction: The aim of the present study was to predict academic burnout based on academic self-efficacy among lower secondary school students in Kavar City.
Research Methodology: This research is applied in terms of purpose, and descriptive-correlational in terms of nature and methodology. The statistical population included all lower secondary school students in Kavar, totaling 2,700 students. Using a multi-stage cluster sampling method, the researcher selected four schools from the lower secondary level, and from each school, two classes were randomly chosen—resulting in a total sample of 240 students. The data collection tools included two questionnaires: the Academic Self-Efficacy Questionnaire and the Academic Burnout Questionnaire. For data analysis, descriptive statistics (mean and standard deviation) and inferential statistics (stepwise regression and Pearson correlation coefficient) were used.
Finding: The findings indicated that students' academic self-efficacy is a significant predictor of academic burnout. Moreover, the dimensions of academic self-efficacy were also found to be significant predictors of students' academic burnout.
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