Abstract
The impact of globalisation along with the critical demands for economic and social development have given rise to competition in keeping up with both international and regional growth. This situation has accelerated the momentum to strengthen and improve the education system of many countries especially in the Asia Pacific Region.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Areepattamannil, S., & Kaur, B. (2013). Factors predicting achievement of immigrant and non-immigrant students: A multilevel analysis. International Journal of Science Mathematics Education, 11, 1183–1207.
Baker, D. P., & Jones, D. P. (1993). Creating gender equity: Cross-national gender stratification and mathematics performance. Social Educucation, 66(2), 91–103.
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191–215.
Bembenutty, H. (2011). The last word: An interview with Harris Cooper—Research, policies, tips, and current perspectives on homework. Journal of Advanced Academics, 22, 342–351.
Bryk, A. S., & Raudenbush, S. W. (1992). Hierarchical linear models in social and behavioural research: Applications and data analysis methods. Beverly Hills, CA: Sage Publication.
Carroll, J. B. (1963). A model of school learning. Teacher College Record, 64(8), 723–733.
Cooper, H., & Valentine, J. C. (2001). Using research to answer practical questions about homework. Educational Psychologist, 36(3), 143–153.
Cooper, H., Lindsay, J., Nye, B., & Greathouse, S. (1998). Relationships among attitudes about homework, amount of homework assigned and completed, and student performance. Journal of Educational Psychology, 90, 70–83.
Creemers, B. P. M. (1991). Review of effective teaching: Current research. School Effectiveness and School Improvement, 2(3), 256–260.
Creemers, B. P. M., & Scheerens, J. (1989). Developments in school effectiveness research. International Journal of Educational Research, 13(7), 685–825.
Eccles, J. S. (2005). Subjective task value and the Eccles et al. model of performance-related choices. In A. J. Elliot & C. S. Dweck (Eds.), Handbook of competence and motivation (pp. 105–121). New York, NY: Guilford Publications.
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53, 109–132.
Fontaine, R., Richardson, S., & Foong, Y. P. (2002). The tropical fish revisited: A Malaysian perspective. Cross Cultural Management, 9, 60–70.
Glewwe, P. W., Hanushek, E. A., Humpage, S. D., & Ravina, R. (2011). School resources and educational outcomes in developing countries: A review of the literature from 1990 to 2011. Retrieved from http://www.nber.org/papers/w17554
Hanushek, E. A., & Woessmann, L. (2008). The role of cognitive skills in economic development. Journal of Economic Literature, 46(3), 607–668.
Hsu, J. C. (2007). Comparing the relationships between mathematics achievement and student characteristics in Canada and Hong Kong through HLM (Unpublished master thesis). University of Victoria, VIC, British Columbia, Canada
Husén, T. (Ed.). (1967). International study of achievement in mathematics (Vol. 2). Stockholm: Almqvist and Wiksell.
Keeves, J. P., & Kotte, D. (1998). Sex differences and educational outcome. In T. N. Postlethwaite, B. R. Clark, G. Neave, & T. Husén (Eds.), Education: The complete encyclopaedia. UK: Pergamon.
Keeves, J. P., & Saha, L. J. (1998). Measurement of social background. In T. N. Postlethwaite, B. R. Clark, G. Neave, & T. Husen (Eds.), Education: the complete encyclopaedia. UK: Pergamon.
Kitsantas, A., Cheema, J., & Ware, H. W. (2011). Mathematics performance: The role of homework and self-efficacy belief. Journal of Advanced Academics, 22(2), 310–339.
Klein, K. J., & Kozlowski, S. W. (2000). From micro to meso: Critical steps in conceptualizing and conducting multilevel research. Organizational Research Methods, 3, 211–236.
Kreft, I., & de Leeuw, J.D. (1998). Introducing multilevel modelling. London: Sage Publications.
Kutnick, P., Ota, C., & Berdondini, L. (2008). Improving the effects of group working in classrooms with young school-aged children: Facilitating attainment, interaction and classroom activity. Learning and Instruction, 18, 83–95.
Lam, T. Y. P., & Lau, K. C. (2014). Examining factors affecting science performance of Hong Kong in PISA 2006 using hierarchical linear modelling. International Journal of Science Education, 36(15), 2463–2480. doi:10.1080/09500693.2013.879223
Ma, X. (2005). A longitudinal assessment of early acceleration of students in mathematics on growth in mathematics performance. Development Review, 25, 104–131.
McConney, A., & Perry, L. B. (2010). Science and mathematics achievement in Australia: The role of school socioeconomic composition in educational equity and effectiveness. International Journal of Science Mathematics Education, 8(3), 429–452.
Milford, T. (2010). An investigation of International Science Performance using the OECD’s PISA 2006 Dataset (Unpublished doctoral dissertation). University of Victoria, Victoria, British Columbia, Canada.
Ministry of Education, MOE. (2013). Malaysian education blueprint 2013–2025: Preschool to postsecondary education. Putrajaya: MOE.
Muthén, J. K., & Muthén, B. O. (2012). Mplus: Statistical analysis with latent variables: User’s guide. Long Angeles, CA: Muthén and Muthén
Nordin, A. R., Thien, L. M., & Darmawan, I-G. N. (2014). Relationship of student- and classroomlevel variables with TIMSS 2011 mathematics performance in Indonesia, Malaysia and Thailand. In S. L. Ong, E. J. Gonzalez., & S. S. Kanageswari (Eds.), TIMSS 2011: What can we learn together? (pp. 38–64). Penang: SEAMEO RECSAM.
OECD. (2004). Learning for tomorrow’s world-First results from PISA 2003. Paris: OECD.
OECD. (2007). PISA 2006: Science competencies for tomorrow’s world (Executive summary). Paris: OECD.
OECD. (2012). Education at a glance 2012. Paris: OECD.
OECD. (2013). PISA 2012 results: Ready to learn: Students’ engagement, drive and self- beliefs (Vol. 3). Paris: OECD publishing. doi:10.1787/9789264201170-en
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage.
Raudenbush, S. W., Bryk, A., Cheong, Y. F., & Congdon, R. (2008). HLM: Hierarchical linear and nonlinear modelling (Version: 6.06) [Computer software]. Lincolnwood, IL: Scientific Software International, Inc.
Ross, S. P. (2008). Motivation correlates of academic performance: Exploring how motivation influences academic performance in the PISA 2003 data (Unpublished doctoral dissertation). University of Victoria. Victoria, British Columbia, Canada.
Scheerens, J. (1992). Effective schooling, research, theory and practice. London: Cassell.
Scheerens, J. (2002). School self-evaluation: Origins, definition, approaches, methods and implementation. In D. Nevo (Ed.), School-based evaluation: An international perspective (pp. 35–73). Oxford: Elsevier Science.
Sharp, C., Keys, W., & Benefield, P. (2001). Homework: A review of recent research. Slough: National Foundation for Educational Research.
Shin, J., Lee, H., & Kim, Y. (2009). Student and school factors affecting mathematics performance: International comparison between Korea, Japan and the USA. School Psychology International, 30(5), 520–537.
Skaalvik, E. M., & Skaalvik, S. (2004). Self-concept and self-efficacy: A test of the internal/external frame of reference model and predictions of subsequent motivation and performance. Psychological Reports, 95, 1187–1202.
Smith, I. D. (2003). Home and coaching. In J. P. Keeves & R. Watanabe (Eds.), The international handbook of educational research in the Asian-Pacific region (pp. 755–766). Dordrecht, The Netherlands: Kluwer Press.
Stevens, T., Olivarez, A., Jr., & Hamman, D. (2006). The role of cognition, motivation, and emotion in explaining the mathematics performance gap between Hispanic and White students. Hispanic Journal of Behavioral Sciences, 28, 161–186.
Stigler, J. W., & Perry, M. (1988). Cross cultural studies of mathematics teaching and learning: Recent findings and new directions. In D. A. Gouws & T. J. Cooney (Eds.), Perspective on research on effective mathematics teaching (pp. 194–223). Reston, VA: National Council of Teachers of Mathematics.
Stringfield, S. C., & Slavin, R. E. (1992). A hierarchical longitudinal model for elementary school effects. In B. P. M. Creemers & G. J. Reezigt (Eds.), Evaluation of educational effectiveness (pp. 35–39). Groningen: ICO.
Tate, W. F. (1997). Race-ethnicity, SES, gender, and language proficiency trends in mathematics performance: An update. Journal of Research in Mathematics Education, 28(6), 652–679.
Thien, L. M., Darmawan, I. G. N., & Ong, M. Y. (2015). Affective characteristics and mathematics performance in Indonesia, Malaysia, and Thailand: What can PISA 2012 data tell us? Large-scale Assessments in Education, 3(1), 1–16. doi:10.1186/s40536-015-0013-z
Thorndike, E. L. (1906). The principles of teaching: Based on psychology. New York, NY: A.G. Seiler.
Townsend, T., & Cheng, Y. C. (2000). Educational change and development in the Asia-Pacific region: Challenge for the future. Netherlands: Swets & Zeitlinger.
Trautwein, U., Köller, O., Schmitz, B., & Baumert, J. (2002). Do homework assignments enhance performance? A multilevel analysis in 7th-grade mathematics. Contemporary Educational Psychology, 27, 26–50.
Treiman, D. J. (1977). Occupational prestige in comparative perspective. New York, NY: Academic Press.
Walberg, H. J. (1984). Improving the productivity of America’s school. Educational Leadership, 41, 19–30.
Willms, J. D., & Smith, T. M. (2005). A manual for conducting analyses with data from TIMSS and PISA. Montreal, Canada: United Nations Educational, Scientific, and Cultural Organization Institute for Statistics (UIS).
Wu, M. (2005). The role of plausible values in large-scale surveys. Studies in Educational Evaluation, 31, 114–128.
Zhu, Y., & Leung, F. K. S. (2012). Homework and mathematics performance in Hong Kong: Evidence from the TIMSS 2003. International Journal of Science and Mathematics Education, 10, 907–925.
Zimmerman, B. J., & Kitsantas, A. (2005). Students’ perceived responsibility and completion of homework: The role of self-regulatory beliefs and processes. Contemporary Educational Psychology, 30, 397–417.
Zimmerman, B. J., & Schunk, D. H. (Eds.). (2011). Handbook of self-regulation of learning and performance. New York, NY: Routledge.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Sense Publishers
About this chapter
Cite this chapter
Thien, L.M., Darmawan, I.G.N. (2016). Factors Associated with Malaysian Mathematics Performance in PISA 2012. In: Thien, L.M., Razak, N.A., Keeves, J.P., Darmawan, I.G.N. (eds) What Can PISA 2012 Data Tell Us?. SensePublishers, Rotterdam. https://doi.org/10.1007/978-94-6300-468-8_6
Download citation
DOI: https://doi.org/10.1007/978-94-6300-468-8_6
Publisher Name: SensePublishers, Rotterdam
Online ISBN: 978-94-6300-468-8
eBook Packages: EducationEducation (R0)