1. Big Data: its collection, analysis and use

2. Seeing the need … implementing the response

3. But …

4. The bottom line … improving student learning
The guiding principles …
Analysing results  informing understanding  forming decisions
Reporting performance  diagnosing learning
Data-informed, not data-driven
ALWAYS ask questions of the data
Impact on MY classroom practices
Data for learning and to support learning
The bottom line … improving student learning

5. Range of data available

6. Promote common understandings What do we need to ensure?
Need for, scope of, change
Discern needs
Change behaviours
Build capacity
Data literacy
Data-informed learning
Whole-school improvement
Developing ‘big data’
Develop infrastructure
Systemic approach
Data warehousing/datamart

7. The key System driver: CE Intranet
SharePoint environment
Single sign-on through Active Directory
Permissions determined by role

12. Dashboards
Data  information
Access
Availability

13. Ask questions of the data
‘What are the data showing us?’
‘What are our concerns about student learning?’
Identify areas of need
‘Are there common concerns throughout the school?’
Using ‘big data’
Respond
‘What do we want to achieve?
How do we translate evidence into action?’
Review
‘Have we achieved our goals/ targets?’
‘What’s the next step?’

14. QUESTION
Why is there a noticeable difference between Sem 1 and Sem 2?

17. Determine Expected Levels of Performance

18. Tracking student achievement and progress

22. Infrastructure Intent The ability to … A culture of … Access Analyse
Report
Use
valuing data
data  evidence
evidence  action
data-informed decision-making