Previous researchers have identified socioeconomic status as a significant predictor of achievement/literacy. However, it is important to recognize that the influence of socioeconomic status on literacy may vary at different levels of socioeconomic status. Thus, this study analyzes the relationship between socioeconomic status and literacy scores…

The research aims to determine the factors affecting PISA 2018 reading skills using the Random Forest and MARS methods and to compare their prediction abilities. This study used the information from 5713 students, 2838 (49.7%) male and 2875 (50.3%) female, in the PISA 2018 Turkey. The analysis shows the MARS method performed better than the Random…

This study seeks to compare fixed and mixed effects models for the purposes of predictive classification in the presence of multilevel data. The first part of the study utilizes a Monte Carlo simulation to compare fixed and mixed effects logistic regression and random forests. An applied examination of the prediction of student retention in the…

Background: Their ubiquity is particularly notable as video games become increasingly intertwined with the technological revolution. Despite this prominence, gender disparities in adolescent video gaming remain under-explored. Objectives: This research aims to determine the frequency classes of video game playing based on gender, analyse the…

The education system strives to help students from low-income families achieve academic success. Academic resilience is related to not only individuals but also classrooms and schools. This study aimed to construct a comprehensive resilience model in science domains that presents the image of resilient students and describes the mechanisms by…

Filipino students ranked last in reading proficiency among all countries/territories in the PISA 2018, with only 19% meeting the minimum (Level 2) standard. It is imperative to understand the range of factors that contribute to low reading proficiency, specifically variables that can be the target of interventions to help students with poor…

This study aims to classify student profiles based on the type and frequency of Information and Communication Technologies (ICT) usage. Each profile exhibits homogeneous characteristics and heterogeneous characteristics compared to other groups. Additionally, the study investigates whether covariates at the school and student levels create…

Considering the large volume of PISA data, it is expected that data mining will often be assisted in making PISA data more meaningful. Studies show that different dimensions of ICT may reveal different relationships for mathematics achievement. The purpose of this article is to evaluate the success of the decision tree classification algorithms in…

In the digital era, traditional communication has undergone a drastic transformation into computer-mediated communication (CMC), which can be classified into synchronous CMC (SCMC) and asynchronous CMC (ASCMC). This study compared the effects of extracurricular CMC among students about schoolwork on students' digital reading achievement between…

Classical conceptualisations of self-regulated learning typically ignore the role of teaching strategies in real-world classrooms. Therefore, the present exploratory study aimed to examine the different clusters of perceived teaching strategies and students' metacognitive knowledge and experiences, and motivation. The data came from 6365 (49.63%…

Response process data have the potential to provide a rich description of test-takers' thinking processes. However, retrieving insights from these data presents a challenge for educational assessments and educational data mining as they are complex and not well annotated. The present study addresses this challenge by developing a computational…

The purpose of this research was to determine classification accuracy of the factors affecting the success of students' reading skills based on PISA 2018 data by using Artificial Neural Networks, Decision Trees, K-Nearest Neighbor, and Naive Bayes data mining classification methods and to examine the general characteristics of success groups. In…

This study problematizes the global educational governance of OECD PISA and its statistical data as a governing technology in contemporary discourses of education reforms. The study examines principles that order the discourses and practices of the international comparative assessment. The effort of analysing the impact of an education reform…

Academic resilience refers to students' capacity to perform highly despite a disadvantaged background. Although most studies using international large-scale assessment (ILSA) data defined academic resilience with two criteria, student background and achievement, their conceptualizations and operationalizations varied substantially. In a systematic…

The purpose of this study was to examine the use of a misspecified calibration model and its impact on proficiency classification. Monte Carlo simulation methods were employed to compare competing models when the true structure of the data is known (i.e., testlet conditions). The conditions used in the design (e.g., number of items, testlet to…