Abstract
Teachers’ classroom behaviors and their effects on student learning have received significant attention from educators, because the quality of instruction is a critical factor closely tied to students’ learning experiences. Based on a theoretical model conceptualizing the quality of instruction, this study examined the characteristics of instructional quality represented by cognitive activation, student-oriented teacher behavior, class management, and learning support and investigated the relationships between instructional quality and students’ affective and cognitive outcomes. The PISA 2012 survey, administered to students in Korea and Singapore, was used to conduct a latent profile analysis and structural equation modeling. It was found that using more student-oriented instruction and less strategies of cognitive activation was positively associated with lower performance in math, while well-managed classroom and learning support were positively associated with higher performance. The level of instructional quality was generally higher for Singapore than Korea in every index at all achievement levels. Most affective characteristics and the math teachers’ instructional focus were positively associated with higher profiles of instructional quality. However, discrepant results were found between the two countries: Cognitive activation had positive effects on interest and self-concept in math as well as math performance for Korean students, whereas it only had a positive effect on math performance for Singaporean students. In contrast, student-oriented instruction had negative effects on interest in math as well as math performance in Korea, but a positive effect on interest in math in Singapore. The implications of each finding were discussed in detail.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Anderman, E. M., Eccles, J. S., Yoon, K. S., Roeser, R., Wigfield, A., & Blumenfeld, P. (2001). Learning to value mathematics and reading: Relations to mastery and performance-oriented instructional practices. Contemporary Educational Psychology, 26, 76–95.
Baumert, J., Kunter, M., Blum, W., Brunner, M., Voss, T., Jordan, A., et al. (2010). Teachers’ mathematical knowledge, cognitive activation in the classroom, and student progress. American Educational Research Journal, 47(1), 133–180.
Bolhuis, S. (2003). Towards process-oriented teaching for self-directed lifelong learning: A multidimensional perspective. Learning and Instruction, 13(3), 327–347.
Brookhart, S. M. (1997). A theoretical framework for the role of classroom assessment in motivating student effort and achievement. Applied Measurement in Education, 10, 161–180.
Brophy, J. E. (2000). Teaching: Educational practices series-1. Geneva: International Academy of Education/International Bureau of Education (IAE).
Brown, P. C., Roediger, H. L., III, & McDaniel, M. A. (2014). Make it stick: The science of successful learning. Cambridge: Harvard University Press.
Burns, D., & Darling-Hammond, L. (2014). Teaching around the world: What can TALIS tell us? Stanford, CA: Stanford Center for Opportunity Policy in Education.
Davis, W., & Carson, C. M. (2005). The interactive effects of goal orientation and feedback specificity on task performance. Human Performance, 18(4), 409–426.
Ellery, K. (2008). Assessment for learning: A case study using feedback effectively in an essay-style test. Assessment & Evaluation in Higher Education, 33(4), 421–429.
Fluckiger, J., Vigil, Y. T., Pasco, R., & Danielson, K. (2010). Formative feedback: Involving students as partners in assessment to enhance learning. College teaching, 58, 136–140.
Hanushek, E. A. (1997). Assessing the effects of school resources on student performance: An update. Educational Evaluation and Policy Analysis, 19, 141–164.
Harks, B., Rakoczy, K., Hattie, J., Besser, M., & Klieme, E. (2014). The effects of feedback on achievement, interest, and self-evaluation: The role of feedback’s perceived usefulness. Educational Psychology, 34(3), 269–290.
Hiebert, J., & Grouws, D. A. (2007). The effects of classroom mathematics teaching on students’ learning. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 371–404). Greenwich, CT: Information Age.
Kim, H. S., & Ham, E. H. (2014). What school characteristics affect Korean students’ non-cognitive outcomes in mathematics? Journal of Educational Evaluation, 27(5), 1311–1335.
Kingston, N., & Brooke, N. (2011). Formative assessment: A meta-analysis and a call for research. Educational Measurement: Issues and Practice, 30(4), 28–37.
Klieme, E. (2013). The role of large-scale assessments in research on educational effectiveness and school development. In M. von Davier, E. Gonzalez, I. Kirsch, & K. Yamamoto (Eds.), The role of international large-scale assessments: Perspectives from technology, economy, and educational research (pp. 115–147). Berlin: Springer.
Klieme, E., Pauli, C., & Reusser, K. (2009). The Pythagoras study: Investigating effects of teaching and learning in Swiss and German mathematics classrooms. In T. Janik & T. Seidel (Eds.), The power of video studies in investigating teaching and learning in the classroom (pp. 137–160). Münster: Waxmann.
Ku, J., Kim, S., Rim, H., Park, H., & Han, J. (2015). Comparative analysis on the achievement characteristics and effects of educational contextual variables in high ranking countries of PISA 2012 results. Research report (RRE 2015-6-1), Korea Institute for Curriculum and Evaluation.
Lipowsky, F., Rakoczy, K., Pauli, C., Drollinger-Vetter, B., Klieme, E., & Reusser, K. (2009). Quality of geometry instruction and its short-term impact on students’ understanding of the Pythagorean Theorem. Learning and Instruction, 19(6), 527–537.
Muthen, L. K., & Muthen, B. (2012). 1998–2012. Mplus user’s guide (7th ed.). Los Angeles, CA: Muthen & Muthen. https://www.statmodel.com/download/usersguide/Mplus%20user%20guide%20Ver_7_r6_web.pdf.
OECD (2009). Creating effective teaching and learning environments: First results from TALIS. Paris: OECD Publishing.
OECD. (2013). PISA 2012 assessment and analytical framework: Mathematics, reading, science, problem solving and financial literacy. Paris: OECD Publishing. doi:10.1787/9789264190511-en.
Scheerens, J., & Bosker, R. J. (1997). The foundations of educational effectiveness. Oxford: Pergamon.
Seidel, T., Rimmele, R., & Prenzel, M. (2005). Clarity and coherence of lesson goals as a scaffold for student learning. Learning and Instruction, 15, 539–556.
Seidel, T., & Shavelson, R. J. (2007). Teaching effectiveness research in the past decade: The role of theory and research design in disentangling meta-analysis results. Review of Educational Research, 77(4), 454–499.
Sohn, W., Shin, Y., & Bae, J. (2014). Effects of teachers’ classroom assessment practices on student math confidence, enjoyment and achievement: Comparative analysis of TIMSS 2011 data of Korea, Singapore and Finland. Journal of Educational Evaluation, 27(5), 1337–1359.
Stefanou, C. R., Perencevich, K., DiCintio, M., & Turner, J. C. (2004). Supporting autonomy in the classroom: Ways teachers encourage student decision making and ownership. Educational Psychologist, 39(2), 97–110.
Turner, J. C., Meyer, D. K., Cox, K. E., Logan, C., DiCinto, M., & Thomas, C. T. (1998). Creating contexts for involvement in mathematics. Journal of Educational Psychology, 90(4), 730–745.
Vieluf, S., Lee, J., & Kyllonen, P. (2009). The predictive power of variables from the PISA 2003 Student Questionnaire. Paper presented at the QEG Meeting, Offenbach, Germany, 19–21 October.
Wang, M. C., Haertel, G. D., & Walberg, H. J. (1993). Toward a knowledge base for school learning. Review of Educational Research, 63(3), 249–294.
Yair, G. (2000). Reforming motivation: How the structure of instruction affects students’ learning experiences. British Educational Research Journal, 26(2), 191–210.
Author information
Authors and Affiliations
Corresponding author
Additional information
This paper was supported by Konkuk University in 2014.
Appendix
Appendix
A full SEM model of instructional quality and student outcomes
Rights and permissions
About this article
Cite this article
Yi, H.S., Lee, Y. A latent profile analysis and structural equation modeling of the instructional quality of mathematics classrooms based on the PISA 2012 results of Korea and Singapore. Asia Pacific Educ. Rev. 18, 23–39 (2017). https://doi.org/10.1007/s12564-016-9455-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12564-016-9455-4