This study examined teachers' digital tool use through latent class analysis (LCA) and identified predictors that separated the emergent subgroups of teachers. Data from the PISA 2018 teacher questionnaire were employed to analyze the teachers' digital tool behaviors in ICT (Information and Communications Technology) strong countries: Germany,…

This scoping literature review examines the relationship between ICT and performance scores in mathematics and science for students around the world included in the PISA assessment. In this review we examined 25 publications and showed that the relationship between ICT and academic achievement is not consistent. The different types of ICT revealed…

This research aims to find how the infrastructure of digital devices within the school and teachers' capacity using digital devices affect student achievement defined as PISA 2018 reading, math, and science scores. The ex post facto co-relational causal research design was employed. The data were obtained from the school questionnaire administered…

Mathematical literacy is becoming increasingly important and needs to be developed. However, various factors can affect students with different mathematical literacy patterns. This study aims to investigate the effects of students' backgrounds, attitudes toward mathematics, and information and communication technology (ICT) familiarity on the…

Recently, the use of information and communications technology (ICT) at school has been extensively increased in Finland. This study investigated whether the use of ICT at school is linked to students 'learning outcomes in Finland. We used the Finnish PISA 2015 data (N=5037). Cognitive learning outcomes (i.e. science, mathematics, reading,…

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…

Using panel data from the last five PISA cycles and data on various institutional variables, the role of ICT resources, parents' occupation, school characteristics and institutions in student attainment was explored. The data were collected from 2.5 million students in 94 countries/economies representing more than 140 million students worldwide.…

This study aims to investigate how Turkish students' involvement in information and communication technologies (ICT) predicts their math and science performance in the 2018 Programme for International Student Assessment (PISA) test. The research also tests demographic variables including socioeconomic status (SES) and gender as covariates. The…

In large-scale international assessments such as the Programme for International Student Assessment (PISA), the Trends in International Mathematics and Science Study (TIMSS), or the Progress in International Reading Study (PISA), research has struggled to find positive associations between the frequency of educational technology use in schools and…

This study investigated whether there are significant differences between reading achievements of 15-year-old students and starting age for preschool and socioeconomic factors according to the results from the PISA 2015 and 2018. The quantitative results show that there is a clear and statistically significant difference between reading test…

Previous research on the relationship between students' home and school Information and Communication Technology (ICT) resources and academic performance has shown ambiguous results. The availability of ICT resources at school has been found to be unrelated or negatively related to academic performance, whereas the availability of ICT resources at…

Large-scale international studies offer researchers a rich source of data to examine the relationship among variables. Machine learning embodies a range of flexible statistical procedures to identify key indicators of a response variable among a collection of hundreds or even thousands of potential predictor variables. Among these, penalized…

This study aimed to determine the affective and socioeconomic variables significantly predicting achievement level of low- and high-achieving students. The data of 1323 low-achieving and 2022 high-achieving Turkish students participated in the PISA 2015 were used in the study. The data were analyzed by using binary logistic regression. The…

The main drive for this study is to look into potential predictors of educational achievement using OECD's original Pisa 2018 dataset. This paper explores (i) access to ICT, (ii) physical characteristics of learning environment at school, (iii) quality of teaching staff and educational material, (iv) student characteristics and learning climate,…

In this study, it is aimed to distinguish the reading skills of students participating in PISA 2015 application into multi-level latent classes at the student and country level. Furthermore, it is aimed to examine how the clusters emerged at country-level is predicted by variables as students have the information and communication technology (ICT)…