Development of student achievement and motivation during lower secondary school – A multilevel pattern-centered analysis of student and classroom differences in Finland
The development of students’ motivation, learning and academic achievement may derive from the social context and group of peers students associate with for years.
Differences between schools are often acknowledged in the Programme for International Student Assessment (PISA) but at least in Finland, there has been much less research on within-school effects, although it is assumed that students’ academic achievements are to some degree affected particularly by their classmates. By using longitudinal, national large-scale educational assessment data, this presentation provides evidence on how Finnish students (N=5071) from different classrooms (N=435) develop distinct patterns regarding their math and literacy achievement and motivational orientation during lower secondary school. To investigate the classroom effect on students’ achievement and motivation patterns, we used multilevel latent profile analysis (MLPA). Students’ probability of having a certain achievement profile during lower secondary school was found to depend on the school class and some of the classes seemed to have a stronger effect on students’ test scores. The preliminary results on students’ achievement goal orientations seem to support the proposed classroom effect. The findings may reflect a combination of class placement practices as well as classroom and peer effect. Although the differences between Finnish schools in PISA have been one of the lowest in the OECD countries (OECD, 2001; 2007; 2016), the findings suggest that the ‘hidden tracking system’ created by classroom membership may create class-level quality differences in both the preconditions and the development of school engagement and learning.
Dr. Elina Ketonen is postdoctoral researcher in Educational Psychology and in Centre for Educational Assessment at the Faculty of Educational Sciences, University of Helsinki, Finland. Currently, Elina Ketonen is Visiting Postdoctoral Research Fellow at the Department of Education, University of Oxford. She has used both cross-sectional, longitudinal and experience sampling datasets in her research and a wide variety of statistical methods, such as variable- and person-oriented approaches, multilevel modelling and intraindividual analyses. Most recently, she has started to examine the biophysiological correlates of students’ self-reported experiences by combining biosignal data with experience sampling data.
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