Session Information
09 SES 04 A, Utilizing International Assessment Data to Understand Variation in Cognitive and Non-cognitive Factors Across Europe and Beyond
Symposium
Contribution
Existing research recognizes the significant role of teaching quality in influencing students' academic (mathematics achievement) and affective outcomes (e.g., mathematics confidence) (Hattie, 2009). Teaching quality can both enhance or diminish the impact of student background characteristics on cognitive achievement (Fauth et al., 2014; Hattie, 2009). Observing, quantifying, and accurately measuring differences in teaching quality presents theoretical and methodological challenges, which could potentially introduce bias and affect study validity (Nilsen et al., 2016). This underscores the need for more empirical research on the relationships between teaching quality and learning outcomes, particularly among primary school students where such research is still limited. This study aims to provide empirical evidence by comparing the relations between student-perceived instructional quality and mathematics achievement and confidence, and examining differences between classrooms in four Nordic countries. The Nordic context is chosen due to the similarities in culture, school systems, and resources among these countries, making it a suitable setting for this comparative analysis (Kavli, 2018). Utilizing data from the 2019 Trends in Mathematics and Science Study (Mullis & Martin, 2017), the study involves 15,839 fourth graders from Denmark, Finland, Norway, and Sweden. It focuses on the relevance of student-perceived instructional quality (Kyriakides & Creemers, 2008) in relation to both cognitive and non-cognitive outcomes, as well as examining variations across classrooms. The concept of instructional quality in this research encompasses two main constructs: classroom management and instructional clarity. Classroom management involves teachers' structural-organizational activities to engage students in learning and establish a conducive learning environment, while instructional clarity pertains to the effectiveness of pedagogical techniques for clear instruction and support (Nilsen & Gustafsson, 2016). Employing Multilevel Confirmatory Factor Analysis (MCFA) and Multilevel Structural Equation Modeling (MSEM), the study examines the relationships between instructional quality and two outcome variables: mathematics confidence and mathematics achievement. Considering the cultural and educational similarities across the Nordic countries, alongside their varied results in international large-scale assessments, the study is guided by two research questions: 1. What are the relations between student-perceived instructional quality (classroom management and instructional clarity) and students’ mathematics confidence and achievement in the Nordic context? 2. What are the relations to student background factors? The results indicate a positive relationship between instructional clarity and mathematics confidence at the student level across all four countries. At the classroom level, mathematics confidence is positively related to instructional clarity. Student background factors demonstrate weaker correlations with mathematics confidence than with mathematics achievement.
References
Fauth, B., Decristan, J., Rieser, S., Klieme, E., & Büttner, G. (2014). Student ratings of teaching quality in primary school: Dimensions and prediction of student outcomes. Learning and instruction, 29, 1-9. https://doi.org/10.1016/j.learninstruc.2013.07.001 Hattie, J. (2009). Visible learning: a synthesis of over 800 meta-analyses relating to achievement. Routledge. Kavli, A.-B. (2018). TIMSS and PISA in the Nordic countries In N. C. o. Ministers (Ed.), Northern Lights on TIMSS and PISA 2018. Nordic Council of Ministers. https://www.norden.org/en/publication/northern-lights-timss-and-pisa-2018 Kyriakides, L., & Creemers, B. P. M. (2008). Using a multidimensional approach to measure the impact of classroom-level factors upon student achievement: a study testing the validity of the dynamic model. School Effectiveness and School Improvement, 19(2), 183-205. https://doi.org/10.1080/09243450802047873 Mullis, I. V. S., & Martin, M. O. E. (2017). TIMSS 2019 Assessment Frameworks Retrieved from Boston College, TIMSS & PIRLS International Study Center website: http://timssandpirls.bc.edu/timss2019/frameworks/ Nilsen, & Gustafsson (Eds.). (2016). Teacher Quality, instructional Quality and Student Outcomes: Relationships Across Countries, Cohorts and Time (Vol. 2). Springer Open. https://doi.org/10.1007/978-3-319-41252-8. Nilsen, T., Gustafsson, J.-E., & Blömeke, S. (2016). Conceptual Framework and Methodology of This Report. In T. Nilsen & J.-E. Gustafsson (Eds.), Teacher Quality, Instructional Quality and Student Outcomes: Relationships Across Countries, Cohorts and Time. Springer Open.
Search the ECER Programme
- Search for keywords and phrases in "Text Search"
- Restrict in which part of the abstracts to search in "Where to search"
- Search for authors and in the respective field.
- For planning your conference attendance you may want to use the conference app, which will be issued some weeks before the conference
- If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.