Methods based on machine learning have become increasingly popular in many areas as they allow models to be fitted in a highly-data driven fashion and often show comparable or even increased performance in comparison to classical methods. However, in the area of educational sciences, the application of machine learning is still quite uncommon.…

Normative studies are needed to obtain norms for comparing individuals with the reference population on relevant clinical or educational measures. Norms can be obtained in an efficient way by regressing the test score on relevant predictors, such as age and sex. When several measures are normed with the same sample, a multivariate regression-based…

The aim of the study is to analyze how classification performances change in accordance with sample size in logistic regression and CHAID analyses. The dataset used in this study was obtained by means of "Attentional Control Scale." The scale was applied to 1824 students and the analyses were done by randomly choosing the samples from…

Regression Tree Method is not yet a mainstream method in Education, despite of being a traditional approach in Machine Learning. We advocate that this method should become mainstream in Education, since, in our point of view, it is the most suitable method to analyse complex datasets, very common in Education. This is, for example, the case of…

The present study investigated the relationship between category extension and intension for 11 different semantic categories. It is often tacitly assumed that there is a (strong) extension-intension link. However, a recent study by Hampton and Passanisi (2016) examining the patterns of stable individual differences in concepts across participants…

The developments and changes that have accompanied the COVID-19 pandemic have affected the educational world and all sectors. Educational institutions around the world have implemented emergency and online educational practises to ensure continuity of education as opposed to the planned distance education activities that were implemented for…

When there are no personal consequences associated with test performance for examinees, rapid guessing (RG) is a concern and can differ between subgroups. To date, the impact of differential RG on item-level measurement invariance has received minimal attention. To that end, a simulation study was conducted to examine the robustness of the…

We perform two approaches of machine learning, logistic regressions and decision trees, to predict student dropout at the Karlsruhe Institute of Technology (KIT). The models are computed on the basis of examination data, i.e. data available at all universities without the need of specific collection. Therefore, we propose a methodical approach…

Purpose: In this study, Logistic Regression (LR), CHAID (Chi-squared Automatic Interaction Detection) analysis and data mining methods are used to investigate the variables that predict the mathematics success of the students. Research Methods: In this study, a quantitative research design was employed during the data collection and the analysis…

Educational data mining (EDM) has been a rapidly growing research field over the last decade and enabled researchers to discover patterns and trends in education with more sophisticated methods. EDM offers promising solutions to complex educational problems. Given the rapid increase in the availability of big data in education and software…

Large-scale surveys typically exhibit data structures characterized by rich mutual dependencies between surveyed variables and individual-specific skip patterns. Despite high efforts in fieldwork and questionnaire design, missing values inevitably occur. One approach for handling missing values is to provide multiply imputed data sets, thus…

A recursive partitioning model approach in the form of classification and regression trees (CART) was used with 2012 PISA data for five countries (Canada, Finland, Germany, Singapore-China, and the Unites States). The objective of the study was to determine demographic and educational variables that differentiated between low SES student that were…

People participate in vocational education and training (VET) for a variety of reasons and at different stages of their life. Some undertake VET to gain the vocational skills necessary to enter the labour market for the first time, while others enter in order to upgrade existing skills, learn new ones, or simply for personal interest. Successful…

Purpose: The purpose of this study was to analyze tracking and stability of motor coordination in children from age 6 years to ages 9 and 13 years. Method: Data were from the Copenhagen School Child Intervention Study. Motor coordination (MC) was measured using the körperkoordinationstest für Kinder (KTK) test. The crude performance score on every…

Educational policies have increasingly promoted parental involvement as a mechanism for improving student outcomes. Few jurisdictions have provided funding for this priority. In Ontario, Canada, the province's Parents Reaching Out Grants program allows parents to apply for funding for a parental involvement initiative that addresses a local…