Leading Intervention 1
17th September 2009
CPD overview
LI1 17th September 9-12 Finstall• Role of intervention leader• Sources and types of data
twilight1 13th October 4-6 Finstall• Identifying pupils for intervention
LI2 17th November 9-4 Finstall• Tracking and spreadsheets• Looking at data in depth• Intervention models and approaches
twilight2 8th December 4-6 Finstall• Resources for intervention
CPD overview
LI3 12th January 9-12 Pitmaston• Proactive rather than reactive intervention• Quality first teaching• Effective use of TA’s
breakfast 11th February 8-10 WRFC, Warriors Centre
• Behaviour and attendance as part of intervention
LI4 21st June 9-12 Pitmaston• Evaluating the year• Planning ahead
Role of Intervention Leader
Track pupil progressBe a source of data and analysis, and adviceCoordinate resources for staff and pupilsHave an overview of interventionMonitor the impact Liaise with subject leaders, with pastoral leaders,
with Strategy Manager, with school Data Manager etc
Aims of the morning
Be familiar with sources and types of data School data FFT RAISEonline
Begin to identify pupils for intervention
Begin to effectively analyse data
Using data key messages
• Data collection does not in itself solve anything• Data provides questions not answers• Data analysis should be used to promote
discussion, evaluation and planning• Analyses for different groups of pupils, and a
range of indicators, help identify strengths or areas for development/intervention
• Use the past to inform the future
What’s the point?
Historical data• Assessments at key points• Ongoing assessmentsTargets• Where should they be in the future? (externally set,
internally set, adjusting for pupil progress)• Interim targetsMonitoring• Comparing progress with targets (individuals and
overall) and reactingSummaries• Comparisons of overall estimates/targets with
actual results
Sources of data & targets
What are you collecting data for?
What data do you need?
Prioritise!SATs
Formal Teacher Assessments
Ongoing Teacher Assessments
Homeworks
Tests
Exams
Projects
FFT
Raiseonline
Pupil self-assessments
Traffic lighting
School historical data
Expected progress rates
Mocks
Behaviour School attendance
Lessonattendance
Rewards andsanctions
?
Data calendar
What decisions are made as a whole school?What decisions are made within subject/pastoral
teams?
What data is collected centrally by the school?What data is collected by subject/pastoral teams?
Does data inform decisions?Are decisions based on data?Could the process be improved?
Fischer Family Trust
Aims to help schools make effective use of test and TA data
Database of all matched pupilsIncludes past test and TA dataIncludes estimates of future attainment based on
national progress patterns
Using Prior Attainment and School Context
Using Prior Attainment as an indicator of future performance, we know:
• KS3/4 attainment is highly dependent on prior attainment• Girls make different progress to boys• Autumn born pupils have higher attainment than Summer
born pupils• Pupils’ prior attainment in English often has a greater impact
on subsequent progress than attainment in Maths or Science
Taking account of School Context, we know:• Pupils from deprived backgrounds tend to make less progress
(geodemographic data)• The spread of prior attainment for the cohort can have an
impact on estimates of future achievement
FactorsPupil Factors PA SE SX
Mean Test Level (Fine Grade)
Mean TA Level
Subject Variations
Gender
Month of Birth
EAL
FSM
SEN Stage, Statemented
Ethnicity
Mobility (joined late / time in school)
School Factors PA SE SX
Mean Intake Test Level
Spread of Intake Test Level
FSM Entitlement (Percentile Rank)
Geodemographic Data (Percentile Rank)
Value Added Models
Model PA (Prior Attainment)
Model SE (Socio Economic)
3 value-added models have been developed:
Model SX (School EXtended)
Prior Attainment
Gender Month of Birth
GenderSchool Context
Prior Attainment
Month of Birth
GenderSchool Context
Prior Attainment
Month of BirthPupil
Context
Which estimate type?
Advantages Disadvantages
Type A(PA)Similar pupils
Prior Attainment is a major factor upon future performance
Doesn’t take account of context. Doesn’t stretch pupils in advantaged schools
Type B(SE)Similar pupils in similar schools
Is a more accurate reflection of what actually happens
No element of challenge
Type D(SE + Challenge)Similar pupils in similar schools
Stretches pupils in schools with high value-added
May still be too low for schools in the top few % nationally for value-added
FFT Reports – www.fftlive.org
So where do the estimates come from?
English Maths Science Average Points Score
Rebecca Mango 4 4 4 27
Jack Tomato 4 4 4 27
Tim Cumin 4 4 4 27
David Apricot 4 4 4 27
Abigail Garlic 4 4 4 27
Jane Apple 3 5 4 27
Edward Onion 4 4 4 27
Liam Peppercorn 4 4 4 27
Take eight ‘similar’ students at the end of Key Stage 2:
All 8 students have the same overall prior attainment using an Autumn Package points score.
The chances graph Average points score of 26 to 28
Last year, 33% of
students with average
points score of 26-28
achieved grade C
So… estimate of 55% chance of achieving grades A*-C
26<= KS2 Average Point Score <=28
…and estimate of 77% of achieving D+
FFT factors: Prior Attainment Model
Difference between students
KS2 Attainment A* -C Estimate
En Ma Sc Pts Score PA Model
Rebecca Mango 4.2 4.4 4.8 23%
Jack Tomato 4.2 4.4 4.8 23%
Tim Cumin 4.4 4.0 4.5 23%
David Apricot 4.9 4.7 4.6 23%
Abigail Garlic 4.8 4.6 4.3 23%
Jane Apple 3.8 4.4 5.5 23%
Edward Onion 4.5 4.5 4.4 23%
Liam Peppercorn 4.5 4.5 4.4 23%
Gender26%
10%
Month of birth
16%
18%
Marks4%
36%
Subject differences
48%
12%
Student Estimates
Most likely levelModel Used
Prior AttainmentYear 6 Test
& TA
Level achieved bytop 5% - 25% ofsimilar pupils
ProbabilityA* - C
Example Student
NC SS Y6
Y6 Test Levels Y6 Teacher Assessment
Eng Ma Sci Eng Ma Sci
116 5 4 5 5 4 5
% chance of achieving KS4 Grade % chance
G F E D C B A A* A*-C Pass
1% 1% 2% 10% 31% 36% 17% 3% 87% 99%
Prior Attainment
Estimates
Questions:• What would you expect this student to achieve at GCSE? • What targets would you set?• What other information would you need to reach a more informed
decision?
Grade B or C
Example Student
NC SS Y6
Y6 Test Levels Y6 Teacher Assessment
Eng Ma Sci Eng Ma Sci
116 5 4 5 5 4 5
% chance of achieving KS4 Grade % chance
G F E D C B A A* A*-C Pass
1% 1% 2% 10% 31% 36% 17% 3% 87% 99%
Prior Attainment
Estimates
Activity
Highlighted sheet (Pupil Estimates Type D)• Estimated grades highlighted if close to boundary• High percentage chances in yellow• Low percentage chances in pink• Rest in blue
Without additional action, how many A* - C would you expect?
Which students would you target for intervention?What other questions would you want answered?What action would you take next?
School Estimates CHANGE
Range of Estimates
• Matched students only
• A, B, D• Box: 3 year trend
for this school• LA guidance is to
use Type D to build in some challenge
• Includes E, M 2 levels progress
• Targets may be set above these
• Also: Breakdown by gender, upper/ middle/lower, etc
So where do these estimates come from?
Difference between
pupils
KS3 Attainment A* - C Estimate
En Ma Sc Pts Score PA Model
Rebecca MangoGender
4.2 4.4 4.8 23% 26%
Jack Tomato 4.2 4.4 4.8 23% 10%
Tim CuminMarks
4.4 4.0 4.5 23% 4%
David Apricot 4.9 4.7 4.6 23% 36%
Abigail Garlic Subject differences
4.8 4.6 4.3 23% 48%
Jane Apple 3.8 4.4 5.5 23% 12%
Edward Onion Month of birth
4.5 4.5 4.4 23% 16%
Liam Peppercorn 4.5 4.5 4.4 23% 18%
Kim Bolton 24%
Basil Don 6%
How many A* - C would you expect from this list?
For the FFT school estimate:
Add the percentages, divide by 100
26+10+4+36+48+12+16+18+24+6 = 200
200 ÷ 100 = 2
So A* - C estimate is 2 students out of the 10
What are the implications for intervention?
Activity
Highlighted sheet again
What are the A* - C estimates for the sheet, using the
% chances?What are the implications for intervention?
Accessing the FFT data
Website (www.fftlive.org), password from Data Manager
• Updated automatically with validated data• ‘old’ estimates will be overwritten
Know the school policy on the versions:• Which version are the estimates taken from?• Are they fixed for the year or key stage, or are
they flexible?
FFT Key messages
Use the individual pupil estimatesUse the school estimatesBe aware of both when identifying pupils for
intervention
Use the ‘actuals’ reports to review the success of intervention and inform future action
Raiseonline
Match the cardsHow many can you match in 5 minutes?
STOP!
Estimates/Targets
National expectations are set by DCSF
Estimate is based on statistical evidenceAn estimate may be a likely outcome for a typical
school, or a likely outcome for a school performing in the top 25%
Prediction is based on past performance + professional knowledge of a pupil
Target is based on prediction and builds in aspiration
Raiseonline
www.raiseonline.org
Based on each pupil’s prior attainmentCompares top 50% and 25% of schoolsShows estimates (as targets) for pupils, groups,
cohorts Allows moderation of the suggested pupil targets
Two sets of pupil data
Initially these are identical
National provided data
School’s own data
• Oct/Nov• Spring• July• Updates overwrite any
school amendments
• Amended pupil results• School defined pupil
attributes and teaching groups
• Optional test data• Question level data• Moderated pupil targets
Updated/amended by the school Data Manager
Updated by DCSF
Can be shared with Ofsted, SIPs, LA;
sharing requires school action
Used for the full PANDA report,available to
Ofsted, SIPs, LA
RAISEonline
The Report Wizard
view all analyses
Reports with grouping
Use the drop-down boxes to change• graph• year• subject• gender• other groupings
Click this link to save any report you find usefulChange the file name if you wish, then Save
Click on data points to identify groups or pupils
Interactive VA graphs
RAISEonline Key messages
Use the individual pupil resultsUse the school resultsCompare with the national pictureUse these to reflect on the success of previous
intervention and hence to inform future action
FFT v RAISEonline
use historic national pupil data use social context dataprovide summaries of attainment
creates estimates of future attainmentsummaries largely at school level
database includes FFT estimatessummaries include national data for comparisonallows question-level analysis
FFT
both
RAISEonline
So…
Use FFT pupil estimates, FFT school estimates to aid selection of pupils for intervention
Use RAISEonline pupil & school tables & graphs to learn lessons from the past to inform future intervention
Use school data and teacher knowledge to refine selection of pupils & choice of intervention package
National Expectations
Sets out DCSF expectations:KS1 to KS2
all L2 + 45% of L1 L4All to make at least 1 level of progressAll should make at least 2 levels of progress
Reporting:
% achieving L4+ in both Eng and Ma% making 2 levels of progress in Eng% making 2 levels of progress in Ma
National Expectations
Sets out DCSF expectations:KS2 to KS3
all L4 + 50% of L3 L5(and increasing majority L6)all L5 (in both Eng and Ma) L6(and increasing majority L7)All to make at least 1 level of progress
Reporting:
% achieving L5+ in both Eng and Ma, and % L5+ in Sci% making 2 levels of progress in Eng% making 2 levels of progress in Ma
National Expectations
Sets out DCSF expectations:KS3 to KS4
30% of average L5 + all L6 5 A*-C (incl Eng and Ma)All L6 (in Eng and Ma) make 2 levels of progress in bothIncreasing majority of L5 in Eng and Ma make 2 levels of progress in both.
Reporting:% of 5A*-C including Eng and Ma% making 2 levels of progress in Eng% making 2 levels of progress in Ma
Setting targets
Estimates should be used to SUPPORT planning and target setting:
• FFT reports offer estimates not targets• Estimates help us to set targets• A teacher’s professional knowledge of the pupil
is vital in target setting• Targets are not predictions• Targets should be aspirational• Targets need not be fixed• School policy may impact on target-setting
So…
Use the individual student estimatesUse the subject estimatesUse your department’s knowledge of the studentsCreate moderated targetsUse these when identifying students for intervention
Use the ‘actuals’ reports to review the success of intervention and inform future action
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