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Championing Young People’s Learning
YPLA Strategic Analysis & Research team
LAT Value AddedKnowledge SharePart 2
Championing Young People’s Learning
Championing Young People’s Learning
The Methodology
Championing Young People’s Learning
Championing Young People’s Learning
Value Added Specification• It’s long and it’s got some complex equations• Producing a version with a bit more plain English in it
• Methodology independently reviewed by NfER• Underlying concepts are complex…
…but individual steps are not so bad
Championing Young People’s Learning
Multi Level Modelling: More detail• MLM applied at qualification & subject level (e.g. A level History)• Attempting to fit a polynomial equation• Complexity of equation based on number of records & insts• Where there are very few records things are grouped together at
SSA level
Championing Young People’s Learning
Multi Level Modelling: Polynomials
Quadratic (order 2)
A + Bx + Cx2
Cubic (order 3)
A + Bx + Cx2 + Dx3
Quartic (order 4)
A + Bx + Cx2 + Dx3 + Ex4
80 to 500 cases 500 to 5000 cases 5000+ cases
Championing Young People’s Learning
Multi Level Modelling: Polynomials
Quadratic (order 2)
A + Bx + Cx2
Cubic (order 3)
A + Bx + Cx2 + Dx3
Quartic (order 4)
A + Bx + Cx2 + Dx3 + Ex4
80 to 500 cases 500 to 5000 cases 5000+ cases
A, B, C, D and E are known as ‘gamma’ coefficients
Championing Young People’s Learning
Multi Level Modelling: Provider Lines
Championing Young People’s Learning
Multi Level Modelling: Provider LinesNational Line = 10 – 5x + 0.5x2 + 0.01x3
Provider A Line = 12 + 10x + 0.5x2 + 0.01x3
Provider B Line = 1000 – 3x + 0.5x2 + 0.01x3
Provider C Line = -400 + 10x + 0.5x2 + 0.01x3
Championing Young People’s Learning
Multi Level Modelling: Equations
111
0
oo
33
221 xxxy o
Error
2
2101
0120
1
0
:,0~
:,0~
ij
j
j
National Line
Provider Line Variation
Distribution Of Results(Variance)
Championing Young People’s Learning
Multi Level Modelling (S+ and R)• Cannot be done with SQL or version of SPSS we have• R & S+ are programmes that support MLM calculation• Data Service use S+ but has licence issues• YPLA getting open source programme R onto estate• Both use the same programming language
• Code used works in a similar way to SPSS
Championing Young People’s Learning
Multi Level Modelling Basic R Syntax
base<-read.table('C:\\DriveD\\LAT VA\\Q_111_S12330.dat',
header = TRUE, fill = TRUE)
library (lme4)
a<-lmer(POINTS~PRIORC+PRIOR2C+PRIOR3C+PRIOR4C
+(PRIORC+PRIOR2C|LAESTAB),data=base)
fixef(a)
Championing Young People’s Learning
The Calculation Process
Championing Young People’s Learning
Championing Young People’s Learning
Step 1: Data from FFT• Received in SPSS format• FFT can advise on issues with the data• Includes data fields on:• Provider code (UPIN & LAESTAB)• Qualification type (A09 and LAT VA qual codes)• Prior attainment and outcome attainment• Learner Names
Championing Young People’s Learning
Step 2: Check and sort data• Data service do a range of checks on the data• Drop any qualifications that are too small to include• Check all providers we expect to be included are in the data• Produce “centred variables”• They then split into lots of small files (one per qual & subject)
Championing Young People’s Learning
Centred Variables• Many equations include quartic term (i.e. x to the power 4)• For a prior attainment score of 58 this is a big number
58 x 58 x 58 x 58 = 11,316,496• To make the MLM calculation run quicker the variables are centred• This means smaller numbers are used
• Involves some fiddly calculations but just basic maths• If you hear reference to “Prior C”, “catalyst file” or “beta variables”
these are interim steps used in this centring process
Championing Young People’s Learning
Step 3: Apply MLM• Data is fed into S+ programme one file after another• This will fit the national line and give details on distribution of results• Gives an output as text file• These text files are then grouped together using a compiler routine
Championing Young People’s Learning
Step 4: Check solutions• The individual solutions are fed into a spreadsheet to check whether
they look reasonable• This spreadsheet is known as the “Batch LAT”• Original FfE version was very complex (Over 6000 lines of code)• For 2009/10 we will be using a simplified version (1000 lines of
code)
• General checking by eye• Some mathematical checks too (positive definite matrix)• Produces “decentered coefficients”
Championing Young People’s Learning
Step 5: Re-apply MLM• If the solution does work then apply a lower order equation
…or group data up to SSA level• Then re-check solution• End point of this is national lines for all of the qualifications
Championing Young People’s Learning
Step 6: Upload data to Online LAT• The national lines and individual provider data are uploaded into
the Online LAT• This undertakes the same calculations as the Batch LAT• It also generates reports for all providers• These are viewable through the provider gateway
Championing Young People’s Learning
Step 7: Extract result files• Bulk data files can be exported from the Online LAT• The “new style” reports will be generated using these files• Results files sent to OfSted to be used in their reports• Results files uploaded to SQL for use by YPLA
• Results for 2007/08 and 2008/09 are on MISVS001 in LSC_MI_DB_PUB (the filenames start LATVA_)
Championing Young People’s Learning
The ReadyReckoner
Championing Young People’s Learning
Ready Reckoner• Providers were keen to get an early view of LAT VA scores• Excel spreadsheet that allows them to model their own data• Due for release in early October• Uses data from LAT VA 08/09 amended data release
• First line support by Data Service’s Service Desk• Second line support by YPLA
Input Data
Output Data
Championing Young People’s Learning
Work scheduled for the next 6 months
Championing Young People’s Learning
Timescales
• Unamended run mid November• Updated LAT Handbook and communications at same time• Amended run planned for mid January
Conclusion
Championing Young People’s Learning
Average GCSE grade
ABCDE
A le
vel r
esul
t
A
B
C
D
ENatio
nal average achievement
Remember the basics