It is common to find mixed-format data results from the use of both multiple-choice (MC) and constructed-response (CR) questions on assessments. Dealing with these mixed response types involves understanding what the assessment is measuring, and the use of suitable measurement models to estimate latent abilities. Past research in educational…

This study aims to conduct a comparative study of Bagging and Boosting algorithms among ensemble methods and to compare the classification performance of TreeNet and Random Forest methods using these algorithms on the data extracted from ABIDE application in education. The main factor in choosing them for analyses is that they are Ensemble methods…

Despite the increasing interest in data science education in the world, its teaching is not included in the curricula (junior secondary) and there is little information about it. Google Trends is discussed as a tool and database in school data science. Also, in different subjects, students were able to create and interpret graphs using this tool.…

The ability to interpret and compare data distributions is an important educational goal. Inherent in the statistical concept of distribution is the need to focus not only on individual data points or small groups of data points (so-called local view), but to perceive a distribution as a whole, allowing to recognize global features such as center,…

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 pervasiveness of racism in the U.S. and its negative relations with key development outcomes has led researchers to uncover mediators, of which this article argues efficacy should be considered. Self-efficacy, one's belief in their capability to accomplish a task or goal, can be measured in multiple domains of functioning and contexts to…

Energy is a central concept across the sciences and an important goal of science education is to support all students so that they develop a full understanding of the energy concept. However, given the abstract and complex nature of the energy concept, only a few students develop an understanding so that they can use energy ideas to make sense of…

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…

The importance of family background in determining a student's academic achievement has long been acknowledged by researchers. Nonetheless, the effect of schooling on this relationship has also been widely investigated. Some studies have shown that family background plays a far stronger role while the effect of schooling is minimal; others have…

This research focuses on how designing, implementing, and evaluating didactic strategies and activities based on scaffolding with visualization and the use of graphic organizers guide the process of reading comprehension in an eighth-grade public school course placed at A1 level. The research methodology was framed as action research with a…

Educational Data Mining (EDM) is an important tool in the field of classification of educational data that helps researchers and education planners analyse and model available educational data for specific needs such as developing educational strategies. Trends International Mathematics and Science Study (TIMSS) which is a notable study in…

A common criticisms of school choice programs is that, instead of improving student achievement, they would increase school segregation. Parents may use different criteria to choose a school, such as proximity, school quality, or the school's ethnic/racial composition. As a result, the system would be segregated based on the parent's preferences.…

This study is the first to empirically examine how school districts allocate resources in response to capital investment revenue from statewide penny sales taxes (called SAVE funds), and whether SAVE funds affect student outputs (i.e., educational achievement). We found evidence that school districts do not use SAVE funds to increase capital…

Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…

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…