Introduction. This study describes an action research project designed to improve reading

Introduction. Inability to self-regulate learning is likely to be an indication of internet/mobile phone use. When students have low self-regulation, this may negatively predict problematic smartphone use. Additionally, problematic smartphone use could be a predictor of academic procrastination. The aim of this study was to investigate the mediating role of self-regulated learning in the relationship between academic procrastination and problematic smartphone use among third year-middle school learning disabled students. Method. For the purpose of this study, quantitative survey research was employed. The independent variable is AP, PSU is the dependent variable and SRL is the moderating variable. 228 students from the four schools were selected. They were all in third year. They aged 14-15 years. Results. Self-regulated learning correlates negatively with academic procrastination, and smartphone addiction. On the other hand, self-regulated learning was found to be positively correlated with Problematic Smartphone Use. This study found that academic procrastination predicted negatively self-regulated learning. SLR predicted AP. Discussion and Conclusion. The results of this study raised our awareness of the mediating role of self-regulated learning in the relationship between academic procrastination and problematic smartphone use among third year-middle school learning disabled student.

This study aimed to investigate the combined effects of Self-Regulated Learning (SRL) and Academic Procrastination (AP) on Smartphone Addiction (SA). It also aimed at investigating the relative contribution of SRL and academic procrastination to SA among second year- middle school learning disabled students. Moreover, it sought to explore if there were correlations between and among SRL and AP on SA. Quantitative survey research was employed. 68 students from the four schools were selected. The results revealed that there were correlations between and among SRL, AP and SA. Both SRL and AP contributed to the prediction of SA. AP is a more potential predictor than SRL. The results raise our awareness of the negative impact of SA upon students as students who are supposed to be of no risk for SA could use high SRL strategies. Additionally, students who are used to using smartphone excessively are rarely able to attain high academic achievement, and may delay doing their assigned homework.

Introduction. It is believed that children with mild to borderline intellectual functioning are not successful in processing the information received from peers and other people in their surroundings during social interactions, which leads to challenging and aggressive behavior. The purpose of this study was to investigate the effect of social information processing (SIP) model intervention on reducing challenging behavior among children with mild to borderline intellectual functioning. Method. For the purpose of this study, a two-way repeated measures ANOVA, with pre-post and follow up test in two groups were employed. A total of 40 children in the age of 5-10 participated. Participants were 33 boys and 7 girls with a mean age of 8.32 (SD=3.14) and a mean IQ of 75.64 (SD=7.34). Results. Findings from this study revealed the effectiveness of social information processing (SIP) model intervention on reducing challenging behavior among children with mild to borderline intellectual functioning. Discussion and Conclusion. In conclusion, results from this study suggested that children with mild to borderline intellectual functioning utilized the Social Information Processing (SIP) Model and their challenging behaviors and prosocial behaviors (challenging behavior) could be reduced. Application and implications, limitations, future research were included.