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Bülent Basaran – Education and Information Technologies, 2024
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…
Descriptors: Foreign Countries, International Assessment, Secondary School Students, Achievement Tests
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Simsek, Mertkan – International Journal of Technology in Education, 2022
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…
Descriptors: Predictor Variables, Mathematics Achievement, Achievement Tests, Foreign Countries
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dos Santos, Roberta Alvarenga; Paulista, Cássio Rangel; da Hora, Henrique Rego Monteiro – Technology, Knowledge and Learning, 2023
The demand for in-depth studies on educational data presupposes the application of technologies that allow data analysis of vast quantities, and subsequently, drawing relevant information and knowledge. The research objective herein is to employ data mining techniques on PISA databases to identify potential patterns that may explain the…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students
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Yalcin, Seher – International Journal of Progressive Education, 2018
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)…
Descriptors: Reading Achievement, Reading Skills, Classification, Information Technology