期刊名称:Journal of Measurement and Evaluation in Education and Psychology
电子版ISSN:1309-6575
出版年度:2020
卷号:11
期号:3
页码:219-242
DOI:10.21031/epod.581379
语种:Turkish
出版社:EPODDER
摘要:The purpose of this study is to investigate the effects of access and usage of information and communication technologies (ICT) on Turkish students’ mathematics achievement implemented in PISA 2009 and PISA 2012. A correlational research model was used in this study. In this study,the data which were obtained from the PISA 2009 and PISA 2012 mathematics achievement tests and from the information and communications technologies familiarity questionnaire (ICTFQ) in Turkey were used. In this study,three student level variables and two school variables of ICTFQ which are common indexes both in PISA 2009 and PISA 2012 were selected to compare the effect of ICT variables on PISA mathematics achievement implemented in different years. Two-level Hierarchical Linear Modeling (HLM) analysis was performed in the analysis of the data. As a result,the student level variables had a small or a trivial effect on mathematics achievement. The effect size value of the ENTUSE variable was similar in the PISA 2009 and the PISA 2012 implementation,but the effect size value of the HOMSCH variable and the ICTHOME variable on mathematics achievement in PISA 2012 was lower than in PISA 2009. The ICTSCH and the USESCH variables at the school level had a large effect on mathematics achievement in two implementations of PISA 2009 and PISA 2012. The effect size value of the ICTSCH variable on mathematics achievement in PISA 2012 was higher than in PISA 2009. The effect size value of the ICTSCH variable,having a negative relationship with mathematics achievement in PISA 2012,was lower than in PISA 2009. In this study,the explained variance ratio of mathematics achievement by the school ICT variables level was greater than by the student ICT variables level.
关键词:Information and Communication Technologies (ICT);mathematics achievement;PISA 2009;PISA 2012;two-level hierarchical linear models