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,…

Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational…

Education systems produce a large number of valuable data for all stakeholders. The processing of these educational data and making studies on the future of education based on the data reveal highly meaningful results. In this study, an insight was tried to be developed on the educational data collected from ninth-grade students by using data…

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…

The purpose of this article is to identify the order of significance of the variables that affect science and mathematics achievement in middle school students. For this aim, the study deals with the relationship between science and math in terms of different angles using the perspectives of multiple causes-single effect and of multiple…

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-…

The use of standardized test results to drive school administrator evaluations pervades education policymaking in more than 40 states. However, the results of state standardized tests are strongly influenced by non-school factors. The models of best fit (n = 18) from this correlational, explanatory, longitudinal study predicted accurately the…

School choice policies, such as charter schools and vouchers, are in part designed to induce competition between schools. While several studies have examined the impact of private school competition on public schools, few studies have explored school leaders' perceptions of private school competitors. This study examines the extent to which public…

How can illustrations motivate learners in multimedia learning? Which features make illustrations interesting? Beside the theoretical relevance of addressing these questions, these issues are practically relevant when instructional designers are to decide which features of illustrations can trigger situational interest irrespective of individual…

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…

Effective instruction is a critical predictor of student achievement. As students with exceptionalities such as emotional and behavioral disorders and learning disabilities, who typically struggle with academic achievement, spend increasing amounts of general education settings, the need for precise instructional behaviors becomes more imperative.…