Principal investigator
John Anderson, University of Victoria
Research Assistant
Shelley Ross, University of Victoria
Focus
The basic thrust of the section of the research is to investigate relationships and patterns associated with student performance in mathematics, science and reading, and student, school, home and community characteristics. Datasets from provincial, national and international assessment programs will be the central information sources for this work in statistical modeling:

BC Foundational Skills Assessment (FSA)

PanCanadian School Achievement Indicators Program (SAIP)

Programme of International Student Assessment (PISA)

The International Mathematics & Science Studies (TIMSS)
The first step after acquisition is the entry, ordering and management of these large and complex datasets in a secure yet accessible manner. The major work will consist of analysis and modeling of these data – this work will be based upon multilevel modeling using the program Hierarchical Linear Modeling (HLM6).
Rationale
The relationships between school system traits and the outcomes of schooling are of basic interest and significance to the educational research and policy community since they help to better understand school performance and functioning. Likewise better understandings of the relationships between different facets of literacy is of significance. Although general measures of language arts, mathematics and science performance offer limited insight into the potential symbiosis of literacies from these domains, more finegrained indicators that could be extracted from itemlevel data – such as measures of reading informational text, mathematics communications, data representation and interpretation, information technologies and contemporary science literacy – could enhance the observed patterns of relationships given the stronger correlations between these measures.
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NODE 2 
Classroombased Studies of Teaching, Assessment, & Technology Applications 


