09 SES 04.5 PS, General Poster Session
General Poster Session
The need to introduce an assessment system based on computers around the world has emerged by building the ICT environment in the knowledge and information society of the 21st century. Currently, it is being conducted with computer-based assessment such as the GMAT in the United States, CASEC in the Japan, ESPT and i-TEPS in the Korea. There are many cases of changing a paper-based assessment to computer-based assessment. Based on this contemporary flow, PISA (Programme for International Student Assessment) system was gradually changed. It was introduced the first computer-based assessment in some areas of PISA 2006. Also, it was conducted the computer-based assessment in the mathematics and reading in addition to the paper examination in PISA 2012.
Looking at the number of previous studies using the PISA data in Korea, it was mostly noted the results of paper-based assessment in terms of student achievement. Sohn, Kim, Park, and Park (2009) conducted to find out whether it is possible to explain the differences between countries in students’ science literacy using PISA 2006 data. It mentioned that students’ motivation and self-related belief variables are significant in Korea, Finland and Hong Kong-China. Park, Ha, and Park (2011) showed that reading experience with parents, high educational expenditure and mother’s high level of education were significant for Korea students in PISA 2009 data. They mentioned that female students were less the amount of ICT use than male students. Also, low-usage group of ICT represented the highest achievement and had the most positive attitude in reading. Park and Ha (2011) explored factors have influenced on reading literacy level of Korea students, and compare the differences in PISA 2000 and PISA 2009 data. The effect of gender, reading strategies, diversity of reading materials, the number of students per teacher and average level of education of students’ mother are significant in both data. But, the effect of parents’ cultural possessions is significant only in PISA 2009. Ku, Han, and Kim (2015) conducted a study to compare and analyze the effects of the educational context variables on gender difference in science achievement of Korea, Singapore, Japan and Finland using the PISA 2012 data. In this study, it was observed that the effect of homework time after school and attitude toward learning activity was significant in all four countries. Also, they mentioned that a good relation between the female students and teachers and an instruction to avoid disturbing the class atmosphere by male students were needed to raise science achievement in Korea based on the analysis results.
This study examines the characteristics of Korean students’ achievement in computer-based assessment of Mathematics and compares with Estonia students’ achievement to explore the direction of the education in schools. Estonia showed high achievement in the entire area of PISA 2012 and was known for its excellent IT education. This country was selected to examine the differences in characteristics between countries with different environment of education. At this time, the characteristics of male and female students’ achievement were separately searched focusing on the gender difference in both countries. In other words, the purpose of this study is to analyze the effects of educational context variables on male and female students’ computer-based assessment of Mathematics in Korea and Estonia and to draw implications for better mathematics education in schools.
Ku, J. O., Han, J. A, & Kim, S. S. (2015). Effects of educational context variables on gender difference in science achievement among top performing countries of PISA 2012. Korean Journal of Educational Evaluation, 28(5), 1381-1400. OECD (2014). PISA 2012 Technical Report. OECD Publishing. Park, H. J., & Ha, Y. J. (2011). Change in determinants of reading literacy level based on PISA databases. Korean Journal of Educational Evaluation, 24(4), 921-942. Park, H. J., Ha, Y. J., & Park, M. H. (2011). Application of the mixture modeling to the student characteristics and reading achievement according to the patterns of ICT use. Korean Journal of Educational Evaluation, 24(3), 733-754. Raudenbush, S. W., Bryk, A. S., Cheong, A. S., Fai, Y. F., Congdon, R. T., & du Toit, M. (2011). HLM 7: Hierarchical linear and nonlinear modeling. Lincolnwood, IL: Scientific Software International. Sohn, W. S., Kim, K. H., Park, C., & Park, H. H. (2009). A Comparison of Multi-level Models for Scientific Literacy across Korea, Finland and Hong Kong-China. Korean Journal of Educational Evaluation, 22(1), 129-149.
00. Central Events (Keynotes, EERA-Panel, EERJ Round Table, Invited Sessions)
Network 1. Continuing Professional Development: Learning for Individuals, Leaders, and Organisations
Network 2. Vocational Education and Training (VETNET)
Network 3. Curriculum Innovation
Network 4. Inclusive Education
Network 5. Children and Youth at Risk and Urban Education
Network 6. Open Learning: Media, Environments and Cultures
Network 7. Social Justice and Intercultural Education
Network 8. Research on Health Education
Network 9. Assessment, Evaluation, Testing and Measurement
Network 10. Teacher Education Research
Network 11. Educational Effectiveness and Quality Assurance
Network 12. LISnet - Library and Information Science Network
Network 13. Philosophy of Education
Network 14. Communities, Families and Schooling in Educational Research
Network 15. Research Partnerships in Education
Network 16. ICT in Education and Training
Network 17. Histories of Education
Network 18. Research in Sport Pedagogy
Network 19. Ethnography
Network 20. Research in Innovative Intercultural Learning Environments
Network 22. Research in Higher Education
Network 23. Policy Studies and Politics of Education
Network 24. Mathematics Education Research
Network 25. Research on Children's Rights in Education
Network 26. Educational Leadership
Network 27. Didactics – Learning and Teaching
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