09 SES 12 A, Relations of Class Composition and Schools’ Time-policy to Students’ Competencies, Cognitions and Motivations in Lower Secondary Education
The allocation of students into schools and classes by achievement is a common practice worldwide (OECD, 2012, Table 2.2). However, there are clear differences both in the form of the selection of students into the different tracks and in when in student’ educational path the selection happens. In some OECD countries, students are tracked relatively early into schools or tracks with differing curricula (e.g., Austria, Belgium, Germany, the Netherlands) whereas in others (e.g., the Nordic countries, France, Poland, Japan), all students follow the same curriculum at least through compulsory education and in some, even longer (e.g., the United States) (Eurydice 2014; OECD 2012). While the first type of tracking represent open ability-based differentiation, also the latter can and often do include differentiation based on ability or other student characteristics. In them, differentiation is organised by allocating students into different schools or into different tracks or streams within schools. The latter may compass permanent grouping covering all subjects or be subjects-specific as in the advanced placement (AP) courses common to many American schools (Chmielewski, 2014). Ability-based tracking and streaming has been a hotly debated topic for a long time with arguments often resting on a perceived trade-off between equity and efficiency (Entwistle & Alexander, 1992; Hanushek & Woessman, 2006; OECD, 2012, 2013).
The central argument for tracking is that homogeneous classrooms permit a focused curriculum and appropriately paced instruction, leading to better learning for all (Duflo, Dupas, & Kremer, 2011; Loveless, 2009). Arguments for ungrouped classrooms centre on the concern that lower ability students will be disadvantaged by less ideal learning environments regarding teacher proficiency, curricular content, and peer effect (Duru-Bellat & Mingat, 2006; Entwistle & Alexander, 1992). Some, however, have found no evidence for the impact of ability grouping on student performance (Duflo, Dupas, & Kremer, 2011; Figlio & Page, 2002; Lefgren, 2004; Zimmer, 2003), interpreting this to mean that the positive effect of achievement-specific instruction of tracking overcomes the negative (or lacking positive) effect of the more able peers for students in the lower-achievement tracks.
Against this background, the present study focusses on between-class differences and their development in lower-secondary education in Finland, a country known for the high performance of its students and the small between-school differences in the OECD PISA studies (Programme for International Student Assessment). Undermining this, Finland stood out among the Nordic countries in the TIMSS 2011 study due to its considerably higher between-class differences at both grades 4 and 8 (Yang Hansen, Gustafson, & Rosén, 2014). To investigate this apparent challenge for educational equity in Finland further, the present study focusses on between-class differences and the role of class composition on the development of students’ cognitive competence and learning motivation through the three years of lower secondary education. The period can be seen as especially critical as it prepares students for the possibly most important choice regarding their future, the choice between the two tracks – academic and vocational – of the Finnish upper secondary education. In the study, class composition will be understood to be exemplified by the students’ cognitive competence, motivational attitudes, curricular attainment, SES, and class size.
Adey, P., Csapó, B., Demetriou, A., Hautamäki, J., & Shayer. M. (2007). Can we be intelligent about intelligence? Why education needs the concept of plastic general ability. Educational Research Review, 2, 75–97. Chmielewski, A. K. (2014). An international comparison of achievement inequality in within-and between-school tracking systems. American Journal of Education, 120(3), 293–324. Duflo, E., Dupas, P. & Kremer, M. 2011. Peer effects, teacher incentives, and the impact of tracking: Evidence from a randomized evaluation in Kenya. American Economic Review 101, 1739–1774.doi=10.1257/aer.101.5.1739. Duru-Bellat, M. & Mingat, A. 1998. Importance of Ability Grouping in French ”Collèges” and its Impact upon Pupils’ Academic Achievement. Educational Research and Evaluation, 4(4), 348–368. Entwistle, D., & Alexander, K. (1992). Summer setback: race, poverty, school composition and educational stratification in the United States. American Sociological Review, 57, 72–84. Eurydice (2014). The structure of the European education systems 2014/15: schematic diagrams. Eurydice – Facts and Figures. http://eacea.ec.europa.eu/education/eurydice/facts_and_figures_en.php#diagrams Figlio, D. N., & Page, M. E. 2002. School choice and the distributional effects of ability tracking: does separation increase inequality? Journal of Urban Economics, 51(3), 497-514. Gagné, F. & St Père, F. (2001). When IQ is controlled does motivation still predict achievement? Intelligence, 30, 71–100. Hanushek, E.A. & Woessman, L. 2006. Does Educational tracking affect performance and inequality? Differences-in-differences evidence across countries. The Economic Journal, 116 (March), C63–C76. Hautamäki, J. & Kupiainen, S. (2014) Learning to learn in Finland. Theory and policy, research and practice. In Ruth Deakin Crick, Cristina Stringher & Kai Ren (Eds.) Learning to Learn. International perspectives from theory and practice. Routledge. Lefgren, L. 2004. Educational peer effects and the Chicago public schools. Journal of Urban Economics, 56(2), 169-191. Loveless, T. 2009. Tracking and detracking: High achievers in Massachusetts middle schools. Thomas B. Fordham Institute. OECD (2012). Equity and Quality in Education. Supporting disadvantaged students and schools. Spinath, B., Spinath, F. M., Harlaar, N., & Plomin, R. (2006). Predicting school achievement from general cognitive ability self-perceived ability and intrinsic value. Intelligence, 34, 363–374. Zimmer, R. 2003. A new twist in the educational tracking debate. Economics of Education Review, 22(3), 307-315. Yang Hansen, K., Gustafsson, J.E., & Rosén, M. 2014. School performance differences and policy variations in Finland, Norway and Sweden. In Northern Lights on TIMSS and PIRLS. Differences and similarities in the Nordic countries. TemaNord 2014:528.
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