Big Data: its collection, analysis and use

Seeing the need … implementing the response

But …

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

Range of data available

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

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

Dashboards Data  information Access Availability

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?’

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

Determine Expected Levels of Performance

Tracking student achievement and progress

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