I believe data is critical to the work of improving schooling and how well we use data to improve student outcomes and teacher learning is a challenge that some of the best performing systems have had to address. I sometimes think the fear we have in using data stems from the fact that we aren’t trained in how to use it effectively or systematically as part of our practice and planning.
As Lyn Sharratt and Michael Fullan say in their new book Putting Faces on Data – ‘ some educators are really good at breaking down the data, but most are not trained or experienced at chipping away the marble in their system-reports.’ They argue that in order to build success in schools, we need to see the data not as numbers but as the names and faces of every single student. Simple concept with powerful outcomes.
Lyn Sharratt spent two days in Parramatta with our leaders during the school holidays discussing how we go about doing this. Lyn was the former superintendent of Curriculum and Instruction Services in the York Region District School Board, Canada so she understands the challenges at every level: classroom, school and district.
According to Lyn, systems have great visions on paper but most don’t have a strategy for getting there. In their 2009 book ‘Realization‘, they identified the 14 parameters that made a difference to school and student improvement. These are:
- shared beliefs and understandings among all staff
- designated staff member for literacy/numeracy
- daily sustained focus on literacy/numeracy instruction
- principal as literacy/numeracy leader
- early and ongoing intervention
- case management approach to monitoring student progress
- job-embedded professional learning
- in school team meetings as an example of collaborative examination of student work
- literacy/numeracy resources located in a designated area
- commitment of school budget to these priorities
- action research – staff committed to learning
- parental involvement in supporting literacy/numeracy
- appropriate instruction in all areas of the curriculum
- shared responsibility and accountability
The only parameter Lyn says is prioritised is the fundamental belief that all learners can learn. If we share this belief, then we share the responsibility and accountability for our students’ learning. I’m still not sure why this belief is not universally shared by all teachers but as John Hattie says it requires us to believe ‘that intelligence is changeable rather than fixed.’ If we believe intelligence is changeable, then we are empowered to look for better ways of continually moving students forward on the learning journey. Surely this is at the heart of our work as teachers?
Moving students forward is about knowing them as individuals through the use of data walls. Lyn provided some excellent examples of schools using data walls such as Park Manor Public School. Its principal set up a small private room enabling teachers to see and collaboratively discuss the progress of every student. The data wall allowed them to ‘narrow their focus to the key areas for effective countermeasures, or instructional interventions, and then to verify all students’ improvement through data.’ (p85) It is critical to identify the point of need for the learner if we are to design learning experiences targetted at student improvement.
The data wall is a powerful strategy for empowering and enabling teachers. It places them in a position where they are supported by the wisdom and experience of their colleagues; where they are encouraged to reflect on their own practice and where they can recognise their own weaknesses in terms of the skills and instructional strategies needed to address a particular learning problem. As Lyn points out, teacher learning needs to be differentiated within and across schools based on the data. Not only must we personalise student learning, we also need to personalise teacher learning if we are to continually improve the quality of learning and teaching for every student that comes through our system.
For me, the message of our work is simple – it’s not about making assumptions but how we can improve lives through learning. It’s about recognising that behind every data set there is a unique and diverse individual eager to learn.