Using data t o drive instruction

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

8. MINIMUM STANDARD PROFILE for identifying students at risk in March: Gr 1 2111 Gr 2 3222 Gr 3 4333 Gr 4 5344 Gr 5 5454 Gr 6 6455

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.

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 ……….