Six Lessons for School Effectiveness – Analytics journey in a Catholic school system School systems globally have now embarked on leveraging data to improve school effectiveness. At the Catholic Education system in Western Sydney (Australia), an analytics strategy has been successfully implemented in all its primary and secondary schools which has energised the schools in the use of real time data through visualisations and dashboards on school and student performance, system performance, community and culture, resourcing and even regulatory areas. The presentation will share insights and highlights from this analytics journey.

1. Analytics for school system
effectiveness
Six Lens Framework
Raju Varanasi
Chief Information Officer

2. Presentation Outline
1. About School Systems
2. Context for Analytics Strategy
3. Walk-through of Dashboards
4. Ten insights for School system effectiveness

3. Digital Transformation in Education – Has the fuse been lit !
Education is one of the most regulated industries
(understandably - to protect children)
Education is sector with so much societal
promise – providing opportunity, reducing
inequality, improving equity, enhancing social
mobility.
Digitalisation of business processes, automating
workflows and democratising the access to
dashboards and visualisations can make a big
difference.
Analytics is a powerful lever for this social
change.

4. Western Sydney – catholic school system of 80 schools
Geo-spatial knowledge of
your community and
students is valuable.
Provides deeper
knowledge of your
catchment possibilities and
enrolment trends.
Easier to identify
community growth vs
school enrolment growth.

5. 2015
(Faces SIS)
2014
(Faces LD)
2016
(Enterprise
Systems)
Online charts
& graphs
2013
(EYA)
Pre-2012
(eSchool) Basic charts & graphs –
generated manuallyText based
reports
School systems – move from cottage to Enterprise
User generated
reports & exports Real time data &
dynamic self-service
dashboards

6. Schools are enabled by an Enterprise Ecosystem

7. Schools can self-serve when data is easier to use
Spreadsheets are limiting Visualisations are empowering

8. Six Lens Framework - Analytics & Insights

9. Data has no one home - dynamic blend, hypothesis driven
Data Sources Data Sets Dashboards
Data Blending
School
A-E Reports (Secondary)
Attendance
Student Welfare
School-based PL
Visualisations
External
HSC
RLA
QCS
NAPLAN
PAT-R & PAT-M
EYA
HSC
PAT-R
PAT-M
QCS
RLA
NAPLAN
Attendance
Enrolment
A-E Grades
Student & Staff
Demographics
Student Welfare
Professional Learning
Awards & Activities
Enterprise Systems
Faces (SIS & LD)
Professional Learning
CA:PS, ConnX
Service Desk

10. Shifts in data mindset – for school effectiveness journeys
Type
Shift in Data Mindset
from to
Emphasis Store Flow
Stakeholders Leadership All staff, parents
Unit of analysis Aggregate, homogeneity Granular, heterogeneity
Event Past Current
Mode Static Dynamic, real time
Form Reports Visualisations
Focus What happened? What’s happening?

11. Stakeholders and Analytical focus

12. Attendance – unexplained absence tells us more !

13. Similar attendance levels but different absence patterns

14. Poor attendance does mean poor schooling outcomes

15. School catchment analysis and community perceptions

16. Compare school based assessment to standardised tests scores

17. Correlations -Reading & Numeracy, Reading & Writing

18. Similar socioeconomic index – different scoresAv.NaplanScore
SES index

19. Teacher Development – School profile

20. Feeder Primary schools to two Secondary schools ( Year 7 entry)
Feeder
Primary
schools
Secondary School 1 Secondary school 2

21. Low score, Low gain quadrant students – the real challengeGain
Score

22. School improvement - monitoring intervention success granularly

23. Dashboard on dashboards – Users, Events, Views

24. School improvement - examples from analytics
Mapping student post codes to geo locate students around schools (published)
Associating school semester reports and NAPLAN results (published)
Correlating NAPLAN results in L7, N7, L9 and N9 with HSC bands (completed)
Finding patterns in partial or full student absences (published)
Analysing fee behaviour from chronic absenteeism (not yet)
Profiling VET successes to inform career guidance (not yet)
Predicting at-risk students from attendance, demographics and performance data (not yet)
Preparing trends in STEM provision across CEDP schools (commenced)

25. 10 Analytical Insights for School improvement
1. Policy formulation High needs and low needs schools
2. Enrolment growth Community growth and enrolment trends
3. School attendance Unexplained absence vs explained absence
4. School performance HSC and NAPLAN analysis
5. Student performance Learning gain and growth
6. Resource usage Staffing levels, staff leave
7. Professional learning Participation and Impacts of courses
8. Intervention programs Reading Recovery, EMU analysis
9. Principals’ Review Goals vs achievement
10. Personalised learning Students with high needs

26. Summary – multiple lenses, self service mindset to analytics
Attendance
analysis
Enrolment
analysis
NAPLAN
analysis
Catchment
analysis
Professional
Learning Analysis
Staff leave
analysis
Intervention
analysis

27. Thank you
Raju Varanasi, CIO
rvaranasi@parra.catholic.edu.au