1. STATISTICS IN SCHOOLS Vinay Bhardwaj Kim Jackson Catherine Rich Amy Zaffarese

2. Objectives  How government use performance data  Understand different types of data:  Raw data  Value added data  Contextual value added data  Understand the importance of types of data  How teachers use performance data  How schools can use performance data

3. Starter  Each table has a question  Work as a group to come up with as many different points you can think of to help answer this question.  Write these points on the sticky notes provided.

4. Why do we use data?  Analyses for different groups of pupils, and a range of indicators, to help identify strengths or areas for development/intervention;  Use the past to inform the future;  Show patterns of performance;  Give comparisons between groups of pupils;  Allow comparison of groups across subjects;  Possible difference between Teacher Assessment and test.

5. Data provides Questions  Note areas of strengths/weaknesses e.g. is it for all pupils or a particular group  Are there any surprises?  Does the estimate/actual report confirm findings from school’s other data sources?  How does this year’s results compare to previous results?

6. Why do we set Targets? o Estimates should be used to SUPPORT planning and target setting: o FFT analyses offer estimates not targets o Estimates help us to set targets o A teacher’s professional knowledge of the pupil, is vital in target setting o Targets are not predictions o Targets should be aspirational o Also refer to example of KS3 formative assessment used in relation to targets set

7. Why do we use Prior Attainment o Using Prior Attainment as an indicator of future performance, we know: o KS3/4 attainment is highly dependent on prior attainment o Girls make different progress than boys o Autumn born pupils have higher attainment than Summer born pupils o Pupils’ prior-attainment in English often has a greater impact on subsequent progress

8. Raw Data - Predictions o 3 levels of progress between KS2 and KS4 o KS2 - Level 4 = F o Add 3 levels o F-E-D- C o A pupil achieving a level 4 at KS2 should be predicted a C at GCSE. o Use this information to work out whether the pupils are above, on or below target.

9. TESTS  How do we test students?  When  What kind of tests  Do you agree with these?  Should SATs have been binned?  Should we test students more/less often  Formality of tests

10. TOP TRUMPS  In groups/pairs deal your cards equally.  When it is your go, read out the statement which you think will give you the highest value added scores.  If you think yours has won, the other player gives their card to you.

11. Value Added – Acorn Types  ACORN is a geodemographic segmentation of the UK’s population which segments small neighbourhoods, postcodes, or consumer households into 5 categories, 17 groups and 56 types  A Classification of Regional Neighbourhoods.  Contextual Value Added (CVA) is a measure of how well pupils have achieved relative to what they might have been expected to achieve.  takes into account not only each pupil’s prior attainment but also a range of contextual factors, e.g. gender, month of birth, SEN, EAL, ethnic origin, economic deprivation etc. Fill in the missing V. numbers

12. KS4 Adjustments  Use the graphs to work out the adjustments for each of the pupils given.  Work individually/in pairs, and check your answers with the rest of the table.  Each table has a different student profile.  Example:  British Female: KS3 > 8× Grade C

13. Example  Grade C = 40 points  The offset for being female is 15.8 points - table  Therefore a female student is required to gain more points to break even  Even if this student gains her 8 Cs she still has a negative value added  Implications if you teach in a girls school

14. Point Scores for GCSE A*- 58 A- 52 B - 46 C - 40 D - 34 etc……..

15. Outcomes  Use data to assist in planning of lessons and individual pupil performance  Use sample data to calculate value added (VA)  Use data to work out an adjusted Contextual Value Added (CVA) value for ‘example’ pupils  Recognise the limitations of data in drawing judgements on a school’s performance