1. Using data to drive instruction

2. Whole School & Classroom Data Analysis that will guide Mathematics directions
for 2018

3. Whole School & Classroom Data Analysis that will guide Mathematics directions for 2018
This powerpoint outlines a process for school and classroom data analysis for the MAI that when used in conjunction with NAPLAN data, PAT Maths data & teacher knowledge & observations of students will guide Mathematics directions for 2018 across the school and within classrooms. .

4. What do we do with Data as a school?
Identify trends within the school in relation to student achievement in numeracy aspects
Provides focuses for content in Professional Learning Team Meetings
Track individual student progress
Identification of children who maybe at risk; i.e. high or low attaining
Guides school participation in Diocesan Professional Development programs
Guides development of school-based Professional Development that maybe facilitated by outside presenters, CEO staff, coordinators or classroom teachers

5. What do classroom teachers do with data?
Construct Informed & Balanced Classroom Programs & Learning Experiences to meet the needs of student
Identify & cater for students who maybe deemed as at risk; i.e. high or low attaining
Update data through ongoing monitoring & assessment

6. Why do we collect data at the beginning of the year & in an ongoing nature?
To find out what my students know and can do.
To help me to know what to teach next.
To measure the effectiveness of my teaching.
To provide feedback to students on their learning.
To inform parents, other teachers, employers and interested others of academic progress.
Because my principal/school/community expects it (Doug Clarke)

7. A Process for Planning Instruction Based on Formative Data
Map students according to expected standards
Below – At – Above
Unpack the standards/expectations
“What do we want students to know or be able to do?”
What knowledge or skills do we as teachers need?
Deepen professional knowledge
Plan for and engage students in differentiated learning experiences
Assess student learning and teacher impact

8. MINIMUM STANDARD PROFILE for identifying students at risk in March:Gr Gr Gr Gr Gr Gr

9. Applying the process to MAI data
On the sheets provided classroom teachers will record the initials of students ABOVE or BELOW the minimum expected growth point
For the students above or below indicate beside their initial the GP they are at.
Create a whole school linear picture of the MAI data in each of the number domains initially.
For step 1 you can also include names of students AT if you want. The assumption is if the student is not written as being ABOVE or BELOW then they are AT.

10. The process continued…
4. In level teams follow up on the data discussion using the breakdown of growth point document as a guide of key place value learnings
5. What if I’m unsure of what to teach?
Key sources of professional support- colleagues, Origo Mathedology resource, Booker or Reys, CEOB etc.
6. As a team plan differentiated learning experiences to target these key understandings

11. Comparing with PATM
Compare the students who are ABOVE, BELOW or AT the expected MAI profile with October’s PATM results using the Diocesan Data Protocol.
What are the similarities between the 2 data sets?
What are the differences between the 2 data sets? Explore this in greater depth by delving into the areas students achieved success or were challenged in.

12. What about NAPLAN and A – E reporting?
Triangulate the data information with NAPLAN results across the school and for individual students using the data protocol.
How does this compare with A – E reporting?

13. Action Planning
By the ……..
I will have …….
So that ……….