Secondary Quantitative Analysis of Core Research Data (2004-2010): A Multilevel Study of Academic Achievement and 21st Century Competencies

Project Number
OER 20/14 CCY

Project Duration
January 2015 - September 2018


The Core Research Programme is a large-scale representative study of teaching, learning and cognitive assessment practices and student outcomes. Within this major project, survey and assessment data were collected across three subsidiary projects. Core 1 Panel 2 (2004) and Core 2 Panel 2 (2010) are two unique datasets that focus on how school, classroom and student level factors contribute to individual variation in student achievement and other key 21st century (21C) learning outcomes. Core 1 Panel 6 (2005-2008), on the other hand, is a longitudinal dataset that captures a broader range of affective, educational and psychosocial factors, many of which are increasingly recognised as productive 21C dispositions, and how these factors impact the academic and non-academic outcomes of students. Despite the richness of these datasets, however, existing research publications have been limited to cross-sectional analyses using data from individual datasets. The overall objective of this proposed study is to undertake secondary quantitative analyses of student achievement and 21C (non-academic) learning outcomes using existing datasets from the Core Research Programme. First, the proposed study will investigate the proportion of variation in student achievement data and background characteristics across Singapore classrooms and schools. Next, we will investigate and identify the extent to which the variability in student achievement is influenced by student, classroom and school level factors. Third, by linking two datasets, the proposed study will investigate the longitudinal impact of Primary Six students' psychosocial and educational characteristics on their Secondary Three academic achievement and 21C (non-academic)learning outcomes. The proposed study is important for a number of reasons. First, knowledge of the proportion of variance distributions provide important information for school effectiveness in terms of expected shifts in the proportion of variation that can be attributed to different levels of analysis. In broader terms, shifts in variation also provide important information that addresses issues of social and educational equity, given practical difficulties in assessing the direct impact of educational policies. Second, since relationships among different educational variables are often interactional in nature, modelling key contributions of student, class and school level effects separately and simultaneously provides important information about which variable matters most for explaining student achievement, controlling for all other variables considered. Third, observations of individual characteristics and the prospective academic achievement and 21C (non-academic) learning outcomes among the same students over time can provide more robust information about the nature of causal relationships, including control for confounding variables. Finally, findings from this research, in turn generated from advanced methodological approaches widely employed by school effectiveness and evaluation research are expected to provide new empirical insights into the unique strengths and structural gaps of the Singapore education system, so as to meaningfully inform policy and practice for better 21C teaching and learning outcomes.

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