جستجوی مقالات مرتبط با کلیدواژه "multilevel analysis" در نشریات گروه "علوم تربیتی"

The main goal of this paper is to present a multi-level model for analyzing the scores of the national entrance exam to universities and higher education institutions.Based on its objective, this research is an applied and a descriptive research for analyzing and explaining the factors influencing the total score of the candidates participating in the university entrance exam. We used data of the 2019 year exam which include information on socio-economic status of the candidates' including educational, health, cultural and economic variables at individual level as well as at the level of counties and provinces of the country and We used the HLM software to stimate the multilevel models.The estimation of the three-level model showed that 94.6% of the changes in the total test score were due to the differences in the individual and family characteristics of the candidates. 3.6% of the changes in the total score were related to the educational, health and cultural factors of the city and 1.8% to the economic participation rate of the province. Cosidering that 5.4% of the changes in the total score are related to the geographical location, it can be acknowledged that the difference in the total score of the candidates is not only rooted in their socio-economic status, but the simultaneous effect of this situation with the level of prosperity of the cities from the perspective of educational, health, economic and cultural factors also contributes to the intensification of the difference in the total score.

The purpose of this study is to enumerate a set of factors that affect students' participation in scientific olympiads. Turning to the above goal, the theoretical framework of the problem was explored at the micro and messo levels and their interaction with each other was examined.

In this research, survey method and questionnaire were used. The statistical technique used in this method was diagnostic analysis. In order to calculate the validity of the questionnaire tool, face validity was used and to calculate its reliability, Cronbach's alpha was used. The sample selection method was purposeful and in order to compare between the two sets of cases (participants and non-participants) the homogeneity statistical population was selected and 384 samples were studied based on the scientific method of sampling.

This study, which sought to obtain a function to determine the importance of each independent variable in distinguishing groups from each other, was able to identify significant differences between the two groups and, based on the distinction made in the independent variables, predict that Participants in the Olympiad are different from non-participants in independent variables.The results showed that the variables of school educational quality, parents' economic and social status, school olympiad atmosphere, student evaluation system, his ability and ability as well as parents' encouragement were able to predict students' membership in two groups of participants / non-participants

According to the obtained results, it can be said that the experimental findings are a kind of indicative of the theoretical framework of the research. In other words, several factors affect the participation / non-participation of students in this scientific competition at the micro and intermediate levels. Factors that start with the quality of the actors and include school and family support at the institutional level

The purpose of this study was to determine the impact of students' competencies and organizational climate on their academic achievement using a multilevel approach. In this analysis, students’ competencies and the organizational climate were analyzed at the first and second levels, respectively. Given the purpose of study, this was an applied research that was categorized among descriptive correlational research in terms of data collection method. The research population was consisted of students (N = 13000) and faculty members as Heads of different academic departments (N = 57) at Shahid Bahonar University of Kerman. The research sample included 1140 students and 57 faculty members who were selected and analyzed using stratified random sampling method. The data collection tools included three questionnaires, including Interpersonal Competencies Questionnaire, Systemic and Applied Competencies (Ismaili, Mahani, et al., 2016) and Organizational Climate Questionnaire (Halpin and Kraft, 2000). Students’ total grade point averages were also evaluated for their overall academic achievement. The fluctuation range of Cranbach’s Alpha Coefficient for each of the four scales was between 0.55 and 0.84. The results indicated that academic climate at the second level affected the impact of students' competencies on their academic achievement at the first level.

This study aimed to investigate the factors affecting the academic achievement of students at both school and student levels. Therefore, 600 high school students from 20 schools completed student efficacy scale of Jinks and Morgan's (1999) and personal achievement goal orientation and school goal structure scales of Midgley et al. (2000). Also, the school teachers answered teacher's sense of efficacy scale developed by Tschannen- Moran and Hoy (2004). The results of multilevel analysis revealed that at the student level, there is a positive and significant relationship between academic self-efficacy, mastery goal orientation, performance-approach goal orientation, amount of study time and academic achievement. This relationship was negative and significant for the performance-avoidance goal orientation. Girls were found to have higher academic achievement as compared to boys. At the school level, school type and mastery goal structure had a positive and significant relationship with students’ academic achievement. No significant relationship was found among performance-approach, performance-avoidance goal structure, teacher’s collective self-efficacy and academic achievement of students. The level-1 predictors accounted for 49% of the student-level variance and the level-2 predictors accounted for 79% of the school-level variance.

The purpose of this study was to examine graduate studies private rate of return in Iran by using multilevel models. Using latest statistics, applying a multilevel analysis and Mincer earnings function, the effect of university graduate education on employed earnings was investigated. In multilevel analysis method used, major groups activities are considered as second level units. Meanwhile, by measuring the average years of individuals’ unemployment after completing education and adjusting the years after graduation, the estimates of the years of work experience considered to be closer to reality. The most important results of the study showed that the data have a hierarchical structure. In addition, graduate studies have a positive impact on job earnings and the rate of the impact for each additional year of education is 12.3% - a rate that exceeds the opportunity cost of education in developing countries (10%). The study also indicated that the effect of work experience on earnings is 2.6%. This goes beyond the other incentives to enter graduate studies. This result showed the individual's economic justification. Employees earnings with graduate degrees in urban areas was 21.4% more than the same group in rural areas, justifying the migration of labor force with graduate degrees to urban areas. Lastly, the return of each additional year of graduate studies is more than the return of each additional year of higher education

Validity of the multilevel analyses with a focus on differences in learning theories (with both classis approach toward measurement and new approach toward measurement (IRT)) by means of various data has recently been studied. This study is aimed at determining the level of impact of schools on the scores gained by students involved in advanced TIMSS’s 2008 test. In order to achieve the chief goal of the study, the researchers adopted the data relating to administration of advanced TIMSS’s 2008 physics test, which assesses the course of teaching advanced physics to the high school seniors (pre-university students). The population and sample group of this study comprise the pre-university candidates of mathematics and physics taking advanced TIMSS physics test administered in the academic year 2007-2008. The sample size of Iranian students involved in this measurement equaled 2556 subjects. Results of the analyses generally suggest that firstly multilevel IRT (MLIRT) analyses are more powerful than multilevel true scores (MLTS) analyses in clarifying school differences. Secondly, the level of difference in the schools involved in advanced TIMSS math test reflected in intraclass correlation (ICC) is high in MLIRT analyses. Discussion and First, considering measurement error of each item in analyses within Bayesian framework and by means of Gibbs sampling can remarkably improve the power of multilevel analyses and lead to a significant rise in the ratio of the explicated variance. Second, there is too much educational difference and discrimination among schools which is largely due to school-level variables (such as those relating to teacher or school-related variables).