Teachers armed with data and taking a full part in analysing and identifying ways to improve is the way to create consensus, increase ownership and move learning forward.Iain Hope
Iain Hope, the Deputy Head of Primary at the British School Jakarta, explains how a combination of data from Progress Tests and teacher informed ‘data driven dialogues’, can be used to create next steps in learning on an individual, cohort and school level to create true ‘data informed’ action plans. Within this, Iain Hope focuses on the example of development of ‘mastery’ in mathematics.
Use of data to inform learning has become more and more important. However, knowing how to contextualise the data to make it real and meaningful for improving learning, is not easy.
Using a ‘data driven dialogue’ method helps to create action plans that are informed by a broad spectrum of data to accurately target learning needs and reduces the risk of getting an incomplete or misleading picture.
• Firstly, contextualise the data; relate it to individuals and teaching programmes so that teacher judgements of students are scaffolded by data.
• Secondly, value all kinds of data; formative assessment data and knowledge of the students and their pastoral needs or learning styles should be used alongside formal summative data.
• Lastly, data needs to be looked at objectively: data enables better questions to be asked (for which there may be multiple answers) and must be interpreted without any worry about judgement of teacher performance.
The Data driven dialogue process is key to how we are using data to impact learning and it has a specific structure.
1. Data is collated from Internal formative assessment rubrics, Progress Tests in English and Mathematics (PTM/PTE) and the Cognitive Abilities Test (CAT4). Data is also collated
for significant sub-groups such as English as an Additional Language, Individual Needs, low attenders, new arrivals and key national groups.
2. Initially data is kept at year group/department level rather than looking at individual classes in order to maintain neutrality and foster a team approach.
3. Begin with mixed year group/department teams who look at anonymised data (names of children, classes and year groups are hidden). Mixed teams look for strengths and areas to develop. They give possible ways to develop objectively.
4. Mixed teams are reorganised into year group/department teams and the previously anonymised data is revealed so that patterns identified in the mixed teams can be examined. Knowledge of individual students and teaching programmes is then used to contextualise the data. Possible reasons
for patterns are discussed and from this, key actions are developed for the year group or department.
5. Data from all year groups and departments is shared and actions are synthesised and prioritised to create a school ‘data informed’ Action Plan that is shared with all.
6. Learning Support and EAL interventions are targeted strategically to areas of the school that need it most.
7. Action Plan priorities are linked to Professional Learning Communities (PLCs) which explore strategies for the actions given, and to develop pedagogy, resources or plans to support this. They also help identify staff training and areas of focus for Professional Learning Visits by peers.
Priority Areas for Years 1 to 6 Maths, Reading and Writing
1. Target support to next year’s Y2 reading, Y3 maths and writing, Y5 and 6 writing as weaker groups in the school
2. Further develop SPAG for EAL (and all children) – need dedicated lesson every week. Need consistent phonics in lower part of the school and a transition to a spelling programme (Y2–Y6)
3. Further develop progression links in English from FS to Y1 and from Y6 to Y7
4. Develop compositional elements in upper KS2 and make composition and purpose more of an emphasis in writing
5. Continue to improve the timing, regularity, responsiveness and targeting of EAL/IN (particularly in maths for IN)
Recent changes in curriculum in the UK, most particularly in Mathematics for the English National Curriculum, led to a focus on deepening of learning in mathematics; what is more commonly referred to as ‘mastery’.
The school performed well in mathematics, but examination of new curriculum changes meant that ‘mastery’ pedagogy was an area to develop. During data driven dialogues, it was noticed that there were certain patterns to mathematical performance. PTM data showed that Asian students often
performed well, particularly in areas of fluency and procedural work, but were weaker in reasoning and problem solving. This was almost exactly polarised with students who came from countries where English was the first language, such as the UK, US and Australia.
From dialogues based upon PTM data, knowledge of the students and consequent research, five areas of mathematics were identified that linked to ‘mastery’ and the patterns identified from student performance.
Three of these areas were directly linked to the PTM Process Categories which would later allow measurement of impact in these areas. The other two areas identified ‘the use of language’ and ‘the ability to show/explain mathematical strategies’ as key components to improving conceptual understanding and problem solving.
|Area of Maths Mastery||PTM Process Category|
|Fast efficient fluency in procedures and with basic facts||Fluency in facts and procedures|
|Reasoning to solve problems||
Fluency in conceptual understanding
|Explaining/showing ‘how to’ solve problems|
|Understanding and speaking mathematically|
|Investigating patterns and links that aid problem solving||Problem solving|
Consequently, a Professional Learning Community group was set up to identify and trial strategies and pedagogy in mathematics that could impact these five areas. Strategies around improved language support and use for mathematics and use of the ‘Concrete to Abstract’ model have been the
1. Use of manipulatives/practical resources (even for advanced mathematical concepts) to give students a better method for visualising and explaining their strategies and solutions.
2. Use of EAL type support for mathematical language and concepts, e.g. pre-teaching, use of word banks.
3. Use of apps (such as ‘Explain Everything’) that allow students to record their reasoning and demonstrate/ reinforce their ability to use key language and to explain concepts.
4. Use of simple pictorial methods to visualise a range of concepts and relative amounts, e.g. the bar model.
5. Use of investigative models for introducing mathematical concepts and for problem solving where there are many solutions and the strategies for solving them can be varied.
A full understanding of what we mean by ‘data’ and the use of objective dialogue amongst teachers to explore reasons and strategies to improve learning can highlight patterns in learning that would otherwise be missed. Teachers armed with data and taking a full part in analysing and identifying ways to improve is the way to create consensus, increase ownership and move learning forward.
Seeing himself as always a leader in development, Iain is now developing his leadership as Deputy Head of Primary at the British School Jakarta. Prior to this, Iain has held various leadership roles in a career that spans nearly 2 decades. He has led learning in the Far East, Middle East and the United Kingdom.