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MEJDS (2020) 10: 108 |
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Rasoli S, Ahmadian H, Jadidi H, Akbari M. The Effects of a Training Package Based on Self-Regulation Strategies, Academic Engagement, and Self-Handicapping on Procrastination in High School Students. MEJDS 2020; 10 :108-108
URL: http://jdisabilstud.org/article-1-1857-en.html
URL: http://jdisabilstud.org/article-1-1857-en.html
1- Department of psychology, Sanandaj branch, Islamic Azad University
Abstract: (1798 Views)
Background & Objectives: Procrastination has many different dimensions. Academic procrastination is among the most common problems at various levels of education, as a set of behavioral problems that numerous factors could reduce it. One of the most significant variables in explaining the cause of procrastination is self–regulation. The current study aimed to assess an educational package developed based on self–regulation strategies, academic engagement, and self–handicapping and explore its effect on high school students' procrastination.
Methods: This was a quasi–experimental study with a pretest–posttest and a control group design. The statistical population of the study consisted of all 10th– and 11th–grade students in Sardasht, Iran in the academic year of 2018–2019. Accordingly, 60 study subjects were randomly assigned in the experimental and control groups, each consisting of 30 individuals. The study participants were selected using a purposive sampling method. A designed training package based on self–regulation strategies, academic engagement, and self–handicapping was provided to the experimental group in ten 90–minute sessions. The required data were collected at pretest and posttest phases using the Tuckman Procrastination Scale (Tuckman, 1991). The scale’s reliability was established by a Cronbach's alpha coefficient of 0.86. Descriptive statistics indices, including mean and standard deviation, were used for the statistical analysis of the descriptive data. One–way Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA), Pearson’s correlation coefficient, and Independent Samples t–test were used for running inferential statistics evaluations.
Results: The obtained quantitative data revealed a significant difference between the control and experimental groups; thus, the provided training package presented a significant effect on the procrastination of investigated high school students (p<0.001). The results of Independent Samples t–test and one–way ANOVA suggested no significant relationship between age, household size, and economic status, and academic procrastination (p=0.624, p=0.784, p=0.802, respectively). The mean (SD) pretest scores of procrastination in the experimental and control groups were equal to 48.89(4.31) and 45.65(5.77), respectively. However, the posttest mean (SD) scores of the experimental and control groups were calculated as 27.89(3.50) and 44.68(6.10), respectively. These data indicate that compared to the controls, the procrastination scores of the students in the experimental group have changed after receiving the training.
Conclusion: Based on the current study findings, the presented training package based on self–regulation strategies, academic engagement, and self–handicapping could improve procrastination among the investigated high school students.
Methods: This was a quasi–experimental study with a pretest–posttest and a control group design. The statistical population of the study consisted of all 10th– and 11th–grade students in Sardasht, Iran in the academic year of 2018–2019. Accordingly, 60 study subjects were randomly assigned in the experimental and control groups, each consisting of 30 individuals. The study participants were selected using a purposive sampling method. A designed training package based on self–regulation strategies, academic engagement, and self–handicapping was provided to the experimental group in ten 90–minute sessions. The required data were collected at pretest and posttest phases using the Tuckman Procrastination Scale (Tuckman, 1991). The scale’s reliability was established by a Cronbach's alpha coefficient of 0.86. Descriptive statistics indices, including mean and standard deviation, were used for the statistical analysis of the descriptive data. One–way Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA), Pearson’s correlation coefficient, and Independent Samples t–test were used for running inferential statistics evaluations.
Results: The obtained quantitative data revealed a significant difference between the control and experimental groups; thus, the provided training package presented a significant effect on the procrastination of investigated high school students (p<0.001). The results of Independent Samples t–test and one–way ANOVA suggested no significant relationship between age, household size, and economic status, and academic procrastination (p=0.624, p=0.784, p=0.802, respectively). The mean (SD) pretest scores of procrastination in the experimental and control groups were equal to 48.89(4.31) and 45.65(5.77), respectively. However, the posttest mean (SD) scores of the experimental and control groups were calculated as 27.89(3.50) and 44.68(6.10), respectively. These data indicate that compared to the controls, the procrastination scores of the students in the experimental group have changed after receiving the training.
Conclusion: Based on the current study findings, the presented training package based on self–regulation strategies, academic engagement, and self–handicapping could improve procrastination among the investigated high school students.
Type of Study: Original Research Article |
Subject:
Psychology
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