This paper co-authored by Tim Maloney (CSDA co-director 2016-2019) outlines the use of predictive risk modelling tools to identify vulnerable students and understand factors that place these students at risk of non-completion and non-retention early in their university careers. Administrative data from the enrolment process is used to identify the factors contributing to these adverse outcomes.

Citation:
Jia, P., & Maloney, T. (2015). Using predictive modelling to identify students at risk of poor university outcomes. Higher Education, 70(1), 127-149.

This publication co-authored by Rhema Vaithianathan discusses the use of predictive risk models to target early and appropriate intervention to reduce child maltreatment and suggests potential issues that may arise from this approach to child protection.

Citation:
Dare, T., Vaithianathan, R., & De Haan, I. (2014). Addressing child maltreatment in New Zealand: is poverty reduction enough?. Educational Philosophy and Theory, 46(9), 989-994.