Unpacking Educational Inequality in the NT: Data Integration and Holistic Understanding

1. Unpacking educational inequality in the NT Professor Sven Silburn* & Steve Guthridge**, John McKenzie*, Lilly Li** & Shu Li** * Centre for Child Development and Education Menzies School of Health Research, Darwin, NT ** Health Gains Planning NT Department of Health, Darwin, NT

2. AIMHow can existing data be used to enable a more integrated understanding of educational inequality in the NT?

3. NAPLAN Year 3 Reading (2013) 48% of NT Indigenous students had NAPLAN scoresat or below the national minimum standard in 2013

4. Progress towards CtG targets:NAPLAN Year 3 reading at or above NMS Non-Indigenous (National) On track to meet the CtG Target by 2016 Indigenous (National) % at or above NMS By 2018 the % of NT Indigenous children above NMS will have doubled but this will still be far below the CTG target Indigenous (NT)

5. 1. How important is the current policy focus on attendance?

6. Students’ attendance history: Children born in the NT 1994-2004 (N=6,448) Non-Indigenous students Indigenous students % of expected attendance % of expected attendance

7. 2. How much does “Place” matter in shaping attendance and achievement?

8. Community socio-demographic differences:% adults speaking English by % with yr 10 ed. u n

9. Relative influence of community factors associated with remote school attendance Mean number of people per bedroom 0.49 % Adults with year 10 education 0.14 % Adults who speak English only 0.11 Mean weekly household income 0.09 Community remoteness (ARIA) 0.08 0.05 % Population who are Indigenous % Community SES (ICSEA) 0.03 % population aged < 15 years 0.01

10. 3. How do early childhood development outcomes shape subsequent school achievement?

11. Are AEDI outcomes associated with NAPLAN? Indigenous R2 linear =0.789 2012 NAPLAN Yr 3 Reading ( % < NMS) % of children with 2009 AEDI Total Score < 25th national %ile) Non-Indigenous R2 linear =0.032 2012 NAPLAN Yr 3 Reading ( % < NMS) % of children with 2009 AEDI Total Score < 25th national %ile)

12. Relative influence of remote community factors predictive of 2012 NAPLAN reading < NMS Mean weekly household income 0.45 Mean number of people per bedroom 0.20 % Adults with year 10 education 0.14 Mean school attendance 0.10 % Adults who speak English only 0.05 0.04 % AEDI vulnerable (2009) % population aged < 15 years 0.02

13. 4. Do early-life health and socio-demographic factors influence NAPLAN outcomes?

14. Individual child factors associated with Indigenous Yr 3 reading < NMS Multivariate logistic regression: Crude and adjusted risks for NAPLAN Yr 3 Reading below the National Minimum Standard (NMS) [NT Early Child Development Data-linkage Demonstration Study: Silburn, Lynch, Guthridge & McKenzie]

15. Relative importance of perinatal health and socio-demographic factors for Indigenous NAPLAN Yr 3 reading Population Attributable Risk % Population Attributable Risk is the reduction in incidence if the whole population were unexposed, comparing with actual exposure pattern.

16. 5. How can we derive a more “holistic” understanding of the key drivers of educational disadvantage?

17. De-identified linkage of selected data items from NT administrative datasets Datasets already linked Datasets to be linked

18. Summary • Addressing educational inequality in the NT requires recognition that: • School attendance really matters • Levels of remoteness vary considerably • Community characteristics have significant influence • Early-life health & socio-demographic factors also matter • Linking child, family, community & school data will assist in identifying key causal pathways and the best leverage points for improving outcomes