Our research aims to predict students' academic performance by considering the variables affecting academic performance in science courses using the deep learning method from machine learning algorithms and to determine the importance of independent variables affecting students' academic performance in science courses. 445 students from 5th, 6th,…

The purpose of the study is to analyze the affective traits that affect mathematics achievement through Structural Equation Modeling (SEM) as a traditional regression model and Multivariate Adaptive Regression Splines (MARS), as one of the data mining methods. Structural Equation Modeling, one of the regression-based methods, is quite popular for…

The purpose for this correlational, cross-sectional, explanatory was to explain the influence of the length of the school day on the total percentage of students who scored Proficient or Advanced Proficient (TPAP) on the New Jersey Ask (NJ ASK) in Language Arts and Mathematics in Grades 6-8 in for student populations with low, median, and high…

The purpose of this study was to examine the effectiveness of dropout predictors across time. Two state-level high school graduation panels were selected to begin with the seventh and ninth grades but end at the same time. The first panel (seventh grade) contained 29,554 students and used sixth grade predictors. The second panel (ninth grade)…

Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…

Class size reduction has been viewed as one school mechanism that can improve student achievement. Nonetheless, the literature has reported mixed findings about class size effects. We used 4th- and 8th-grade data from TIMSS 2003 and 2007 to examine the association between class size and mathematics achievement in public schools in Cyprus. We…

We examined the age of onset, over-time dynamics, and mechanisms underlying science achievement gaps in U.S. elementary and middle schools. To do so, we estimated multilevel growth models that included as predictors children's own general knowledge, reading and mathematics achievement, behavioral self-regulation, sociodemographics, other child-…

Applied early adolescent researchers often sample students (Level 1) from within classrooms (Level 2) that are nested within schools (Level 3), resulting in data that requires multilevel modeling analysis to avoid Type 1 errors. Although several articles have been published to assist researchers with analyzing sample data nested at two levels, few…

In this study, we analyse the predictive power of home and school environment-related factors for determining pupils' aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At the…

One of the educational reform methods sanctioned under No Child Left Behind legislation is the development of charter schools (King, 2007). While many studies have focused on comparing the student academic achievement rates of charter schools to traditional public schools, little empirical research exists comparing student academic achievement…