Much of the information required for these annual reports is available from a range of existing administrative data sources. These data will be extracted and collated into the report by the Menzies evaluation team.
Much of the community level data which will be compiled is publically available. Agreements have been established with the Department of Education and Training for school and system level data to be extracted from the Department of Education and Training data warehouse, the Student Assessment and Monitoring System and the Department of Education and Training Human Resources data (e.g. data on teacher and assistant teacher recruitment and retention). With the relevant departmental approvals, community level health data will be sourced from the Department of Health’s (Health Gains & Planning) and local community clinics (e.g. community rates of low birthweight, proportion of the community’s children 0-3 years who are anaemic, growth stunted or underweight).
Quantitative outcome measures include school attendance, National Assessment Program for Literacy and Numeracy results and other measures of school engagement and learning. Data from the Australian Early Development Index collected on all children’s first year at school in 2009, 2012, 2015 and 2018 will serve as community level indicators of outcomes for the evaluation of new early childhood programs being implemented through the SSBF program (e.g. Integrated Child and Family Centres being established in the SSBF ‘college’ sites).
It is well established that socio-demographic and health factors have a profound influence on a child’s education outcomes and that those factors operate at both a community and an individual level. For example both the overall quality of community housing and the conditions in a child’s home are significant predictors of a child’s health outcomes in remote Aboriginal communities (Bailie et al 2010). Socio-demographic factors are strong predictors of education outcomes in remote communities in WA, NT and Queensland (McKenzie et al 2010) and the patterns of influence are significantly different to the mainstream Australian context.
In view of this complex and poorly understood interplay of factors it is important that the monitoring system also collects data on socio-demographic variables known from other studies to play a significant role in determining student’s educational outcomes.
In parallel with this ‘top down’ evaluation we will be undertaking a ‘bottom up’ evaluation using the ‘Participatory Performance Story Reporting’ (Mayne 2004) and ‘Most Significant Change’ (Dart and Mayne 2003) methodologies.
Both qualitative and quantitative data will be collected in a brief (40 minute) household interview with the consenting carers of around 15 children enrolled in each of the ‘College’ schools. These carer interviews will be conducted by the Menzies team with the assistance of locally recruited interviewing staff/interpreters.
Other interview data will be collected from a random sample of the school’s teachers and assistant teachers.
Both the family and school staff interviews will gather information regarding community and school perceptions of the progress of the SSBF “college” model in improving school community collaboration and students’ engagement with school learning. The school’s Remote Learning Partnership Agreement and the community’s Local Implementation Plan informed many of the items in these questionnaires.
Details of the data can be found in attachment E “list of data fields”. It is important to note that many of the fields are optional: specific communities will choose to include them or not in order to reflect their particular local issues.