nadereh sohrabi sheghefti

The International TIMSS exams, which include math and science exams, are held every four years to improve the performance of countries' education systems, the results of which are influenced by a variety of factors. The purpose of this study is to formulate a differential equation of successful and unsuccessful students based on school components in the TIMSS 2019 exam. The method of this research is correlational in the form of differential equation. The statistical population is all schools participating in the TIMSS 2019 exam. The sampling method is the same as the regular two-stage cluster sampling method that was performed in the TIMSS 2019 exam. The data collection tool in this study is the questions of the 2019 TIMSS International Examination Questionnaire for family, student, principal and teacher, which was published by the International Association for the Evaluation of Academic Achievement (IEA) in 2019. This test is valid because it is a global standard test and to calculate its reliability, Cronbach's alpha method was estimated on about 30 people in the study population and a coefficient of 0.85 was obtained, which indicates its reliability. Differential analysis method was used to analyze the data.The findings of this study showed that the characteristics of the school with a resolution of 0.711, about being a teacher with a resolution of 0.255, the school's emphasis on scientific success with a resolution of 0.247, the school atmosphere with a resolution of 0.227, readiness for school with a coefficient of 0.226, mathematical assessment with a coefficient of 0.199, about teaching with a coefficient of distinction of 0.180, school emphasis on academic success with a coefficient of distinction of 0.152, subjects of mathematics teaching with a coefficient of separation of 0.147 and the experience and education of the principal with a coefficient of separation of 0.145 have the greatest impact on the separation of successful students from unsuccessful students based on school components. The results of data analysis showed that the differential analysis equation is able to distinguish successful students from unsuccessful students based on school components.

The purpose of this study was to compare the effectiveness of Early intervention and Early intervention with family education on improving the academic ability of Slow-Learner.

The research method was experimental with pretest-posttest and follow-up with a control group. 30 late learners were considered as sample by purposive sampling method. They were randomly assigned to three groups (two experimental groups and one control group). The experimental groups were trained for 20 sessions of 90 minutes in one month. Data obtained from prerequisite reading, math and writing skills tests were analyzed using analysis of covariance.

The results showed that Early intervention and Early intervention along with family education had an effect on the components of academic ability (prerequisite skills of reading, writing and mathematics) and according to the Eta square, it can be said that 51% of the changes were due to the effect of interventions. The results of Tukey test also showed that Early intervention and Early intervention along with family education in the components of academic ability were significantly different from the control group. In addition, Early intervention with prerequisite reading skills along with family education has been more effective. But Early intervention and Early intervention along with family education did not differ in the effectiveness of math and writing skills.

The findings of this study generally confirmed the effectiveness of Early intervention and Early intervention along with family education on improving the academic ability of Slow-Learner.

The main aim of this research wasprediction of the aggression forteen girls and boys (17-18) at high schools in Shiraz based on emotion cognitive regulation (ECR) and resilience. The statistical sample contains 300 male and female students of second and third grades of high school in academic year 2016-2017 that were selected by multi-stage cluster sampling. For collecting data, aggression questionnaire, resiliency scale,and emotion cognitive regulation questionnaire were used. Pearson correlation coefficient and multiple regression analysiswas runto check the research hypothesizes. The results of multiple regression analysis showed that variables of emotion cognitive regulation and resiliency significantly predict the aggression among youth girls and boys. Also, the results of Pearson correlation coefficient showed a significant relationship between (ECR) and resiliency with aggression for high school students.