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Background and Rational
The Toronto District School Board (TDSB) is recognised as among the largest and most diverse in the world. Diversity in the TDSB presents opportunities as well as challenges to effective educational improvement and planning. TDSB’s population has high mobility: the majority of secondary school students live outside the neighbourhood of the school they attend. This allows for exploration of students’ post-secondary education (PSE) pathway from student, school and neighbourhood perspectives.
Many factors effect student achievement and PSE pathways that are in and out of the school doors. However in general, School Effectiveness Research has tended to focus on student achievement from the perspective of what a school offers students; without taking into account a student’s or school’s surrounding social context. This research study brings neighbourhoods, schools, and students simultaneously into the same model using advanced multilevel analytical techniques. One of the core hypotheses of this study is: the City of Toronto neighbourhoods differ in their effect on the schools and students within them.
Methods and Theoretical Framework
Multilevel exploration of associations between student, family, school, and neighbourhood characteristics on stratification and educational sorting of students towards PSE pathways will allow the merging of multiple theories of capital. For example “discussions of neighborhood disadvantages are often rooted in social disorganization theory…or epidemic theory, whereas explanations for the advantages of living in higher-status neighborhoods usually follow social capital theory…and the idea of concentrated wealth” (Pong and Hao, 2007, p. 208). Studying stratification and educational sorting of students’ towards PSE pathways will also allow examination of the current streaming, programs of choice, and Special Education Needs (SEN) practices in TDSB from social and structural equality perspectives.
In this study, Hierarchical Linear Modeling (HLM) is used to make predictions and to estimate the individual or interactive effects of certain student, school, family and neighborhood characteristics on stratification and educational sorting of students’ towards PSE pathways.
Data Sources and Results
The data source is TDSB Grade 12 students (N= 20,025) attending over the 2011-12 school year. Information from different sources (survey, administrative) was collected including applications to post-secondary institutions. Student residence was linked through ArcView 10.1 GIS to 140 City of Toronto neighbourhoods, approximately parallel to the 110 secondary schools in the TDSB. Preliminary descriptive analysis has shown a much stronger connection of PSE access to the neighbourhood where the student lives, compared to characteristics of the neigbhourhood where the school is attended. Secondly, the HLM will test these preliminary results.
References:
Pong, S.L., & Hao, L.X. (2007). Neighbourhood and School Factors in the School Performance of Immigrants’ Children. International Migration Review, 41(1), 206-241
Erhan Sinay, Toronto District School Board
Robert S. Brown, Toronto District School Board
Lisa Marie Newton, Toronto District School Board