Contextual value added
Select the titles below to follow the sequence of steps involved. You can access spreadsheets that simulate this calculation at the bottom of the page.
Step 1: Prediction of attainment based on prior attainment
We obtain a prediction of attainment based on the pupil's prior attainment (fine grade point score). We find that prior attainment is by far the strongest predictor of outcomes.
Step 2: Prediction is adjusted based on characteristics
We then adjust this prediction to take account of the pupil's set of characteristics. Coefficients are used and represent the contribution that each factor makes to the CVA measures.

See also: Contextual value added characteristics
Step 3: Prediction is adjusted based on school's prior attainment
We adjust further by taking account of school level prior attainment. Even after allowing for pupil prior attainment and characteristics, the average level and spread of attainment on entry to a school will also affect the predicted outcome for a pupil.

Step 4: Difference between actual and prediction
We obtain a value added score by measuring the difference (positive or negative) between the pupil's actual attainment and that predicted by the model.
Pupil A achieved 368 points at Key Stage 4.
Therefore her value added score is 368 – 363.4 = +4.6

To access spreadsheets that simulate this calculation select the following link: http://www.standards.dfes.gov.uk/performance/1316367/CVAinPAT2005/?version=1
Please note that although the calculations are based on the contextual value added models used by RAISEonline, the spreadsheets are provided for demonstration only and final results might differ from those in RAISEonline.
See also:
Contextual value added characteristics
Contextual value added scatter plots
Value added graphs