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The Programme For International Student Assesment (PISA) is an international survey funded by the Organization of
Economic Cooperation and Development (OECD). PISA survey is conducted every three years since 2000, to measure and
evaluate the educational quality of students aged between 15 and 16. PISA survey is aimed to evaluate students'
achieveme...
Contexts in source publication
Context 1
... the data are hierarchical, structural equation modeling analysis is inadequate and multi-level structural equation modeling (MSEM) analysis is needed. Some of the literatures of MSEM on education studies is given in Table 1. In MSEM, both the between and within-group variancecovariance matrix are evaluated simultaneously. ...Context 2
... the data are hierarchical, structural equation modeling analysis is inadequate and multi-level structural equation modeling (MSEM) analysis is needed. Some of the literatures of MSEM on education studies is given in Table 1. In MSEM, both the between and within-group variancecovariance matrix are evaluated simultaneously. ...Similar publications
This presentation provides a comparison of the tax structures of Japan, Korea, Philippines,
Singapore, Indonesia, and selected Organisation for Economic Co operation and
Development, OECD, countries Through the comparison with also Malaysia, relevant
lessons on developed country fiscal systems are evaluated across the selected countries
with the co...
This chapter provides a comparison of Malaysia's tax structure with that of Japan, Korea, the Philippines, Singapore, Indonesia, and the Organisation for Economic Cooperation and Development (OECD) countries. Through the comparison, relevant lessons on tax policy that Malaysia could adopt for a more inclusive growth philosophy are provided. Using t...
Citations
International large-scale assessments have a key role in improving educational, economical, and political systems. By using the data of these assessments, countries can draw conclusions about the status of educational systems. Studies and reports generally tend to choose variables available in data set to model the relationships among the variables. In this study, we aimed to introduce a variable selection method to analyze large-scale assessments to be able to decide which variables might be included in modelling country data. We used the entire data set of Türkiye PISA 2015 through elastic net regression to decide which variables should be selected for further analysis. We also provided a summary of the available studies based on Türkiye PISA 2015 data and compared the results. Based on the series of analyses, this study revealed that test anxiety, environmental awareness, interest in broad topics in science, playing video games after school, mathematics literacy, reading literacy, and collaborative problem-solving skills were the explanatory variables contributed most to the degree of scientific literacy of students. This study has a potential to provide an example of shrinkage methods applied in educational context and offer another standpoint for providing a rationale to select which variables can be included.
