مطالب

The purpose of the present study was to model the structural relationships of job stressors and teachers' autonomy support with mediation of emotional exhaustion. This research was descriptive of the correlation type by the method of structural equations. The statistical population included all the teachers of first and second grade of secondary schools in Noor’s and Chamestan’s public schools in the academic year of 2019-2020, that based on Cochran’s formula and stratified random sampling method, 240 people were selected. The tools of this research were the job stressor factors questionnaire of Otero-Lopez et al. (2006), the teacher as social context questionnaire Welborn et al. (1992) and the teachers’ burnout inventory of Maslach et al. (1996). All analyzes were done by structural equation modeling method. The findings indicated that the structural relationship model of job stressors and teachers' autonomy support with the mediation of emotional exhaustion in teachers of first and second grade of secondary schools has favorable fit and significance. In this research, all the direct and indirect paths that lead to the prediction of teachers' autonomy support have been significant. The research’s results indicate that job stressors have a direct and indirect effect, through emotional exhaustion, on teachers' autonomy support and also emotional exhaustion directly affects autonomy support. Addressing these variables can be effective in solving the problems of teachers' autonomy support and increasing it.

Given that academic procrastination originates from various factors, two of the most important factors in this field are cyberspace addiction and executive functions. Therefore, this research aims to model structural equations for predicting academic procrastination based on cyberspace addiction and executive functions. The research method is a descriptive-correlation type of structural equation modeling. The statistical population of this research includes 8150 female first-secondary school students in the city of Kerman in the academic year 2022-2023; according to Morgan's table, 384 people have been selected as a sample using stratified random sampling. Widyanto and McMorran's (2004) cyberspace dependence, Brief's (2000) executive functions, and Solomon and Rothbloom's (1984) academic procrastination questionnaires were used to collect data. Data analysis was done with SPSS25 and AMOS24 software, and descriptive and inferential statistics such as mean, standard deviation, and structural equation modeling were used. The research results showed that the model for predicting academic procrastination based on dependence on cyberspace and executive functions has an acceptable fit. There is a significant relationship between cyberspace addiction, executive functions, and academic procrastination (p<0.05), so cyberspace addiction and executive functions simultaneously explain 0.70 of the variance of academic procrastination. Therefore, it can be concluded that the high dependence on cyberspace and spending much time aimlessly in this space cause students to procrastinate in doing their homework and to suffer from a kind of procrastination in academic subjects. Also, defects in executive functions aggravate the academic procrastination of students.