Australian teachers' intent to leave teaching profession through logistic regression analysis
datasetposted on 14.02.2019 by Bo Cui
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Staff in Australia's Schools (SiAS) 2010 is the second national survey of approximately 17,000 teachers and school leaders funded by the Australian Government, conducted by the Australian Council for Educational Research (ACER); the first being conducted in 2006-07. It collected data on a wide range of teacher characteristics and workforce issues including: demographic items, professional learning, qualification, future career intention, and career path. One of the major purposes of this national survey was to provide relevant data to inform teachers staffing issues and teacher workforce planning. (McKenzie, Rowley, et al., 2011). The data is self-reported and data quality generally regarded as good. The first aim of this project was to use logistic regression to estimate Australian teachers' Intent to permanently leave teaching profession prior to retirement. Another aim was to identify the factors (or independent variables) that could most accurately predict teachers' intention to leave.