Meeting+Notes+17th+February

Data Group – Report from Warrnambool Meeting Thursday 17th February

‘Sometimes the questions are complicated and the answers are simple” Dr Seuss.

__Purposes for Data__ (Why the big focus? / why collect it ?)

o Inform and guide teaching and consequently planning o Targeting and allocation of resources (physical / staffing / PD foci) o Track and reflect on student progress o Differentiate teaching to level of understanding o Accountability (class / school / network / region / state / national / international) o Reflection and feedback at all levels o Observe and reflect on trends

Ultimately – ** // __to improve student outcomes__ // **

__Purpose of assessment?__

o Provides feedback on teaching o Feedback is a powerful tool for students o Authentic feedback – positive and negative – real and in context of the student o Allows teachers to set goals for the students. (Teacher goals are most effective as teachers have the understanding of learning and the continuum)

__Funding__ o Australia’s funding system is one of the few in the world where independent (non government) schools are funded as much (and more) than the government schools. o Fact 1 – Students from independent schools do ** // achieve // ** marginally higher on school exit examinations o Fact 2 – The percentage of students ** // enrolling // ** at university is marginally in favour of independent school leavers over government school leavers o Fact 3 – The percentage of students ** // completing // ** university degrees is significantly in favour of government school students.

__Data wise clip__

[] __ Data wise model __ [] The Data wise model could provide an excellent model for considering the data we have in schools in our data teams. __ John Hattie – Meta Analysis __ John Hattie considers ‘effect size’ (i.e. what impact specific actions or events have on student outcomes and achievement) Baseline – The effect size of doing ‘nothing’ = 0.3 (with no intervention students will ‘grow’ 0.3 of a year) Interesting effect sizes 0.88 Acceleration – Moving up a year 0.73 Feedback on performance and achievement 0.72 Student teacher relationships 0.59 Teaching / study groups 0.50 Intervention programs – reading recovery / assisted reading 0.41 co-operative learning – working in teams 0.29 Homework 0.22 Individualised instruction 0.12 Abilty grouping -0.16 Retention – holding down a year (repeating) -0.34 Changing schools When effects are compounded the effect size also compounds but not to the total effect size. i.e. Acceleration and feedback creates a larger effect than acceleration on it’s own but not a direct doubling of the combined effects. Next meeting we will be looking closer at John Hattie’s work and will be using a formula to apply effect size to our setting (back at school) when we are interrogating student data.