2018 version of ASP summary template free to download here.
Some tweaks on last year's template - now takes account of time series and 3 year average.
Feel free to modify, copy and share. Just credit the source and please download it first before attempting to complete it (it will open in Word online. To download, click on 3 dots in top right window of browser).
If you are confused by the 'Impact scores' concept (and who can blame you. I made up that term by the way), the idea is to find the minimum score required to improve an overall progress score from below average (orange or red) to average (yellow); or from average (yellow) to above average (green). The former is most critical and often it a case of just removing one pupil from data.
Schools that are below average (orange) will have a negative progress score (e.g. -1.9) and a confidence interval that is entirely negative (e.g. -3.6 to -0.2). If the confidence interval does not include the national average of zero - i.e. it does not cross the zero line - then it is deemed to be significantly below average (as in the example given above).
It would be neat to find out if removing one pupil would improve our data from below (orange) to average (yellow). Let's return to our example above. We take the upper limit of the confidence interval (the right hand number, i.e. -0.2). This is how far the progress score is away from average; how far the confidence interval is away from the zero line (safety!). Essentially, if every pupil's progress score increased by 0.2, the overall score would be in line with average, but that doesn't really help.
A better approach is to take that figure of -0.2 and multiply by the number of pupils included in progress measures (clearly stated in ASP). Let's say that's 30 pupils:
-0.2 x 30 pupils = -6.
This means by removing just one pupil with an individual progress score below -6, the 'below average' (orange) indicator will change to 'average' yellow.
Note: if your progress scores are average (yellow) and you want to determine what it would take to make them above average (green), use the lower limit of the confidence interval (the left hand figure) instead. Same applies: multiply that by the number of pupils, and if you have a pupil with a negative score equal to the result, removing a pupil with a progress score lower than the result should change overall scores from average to above.
Hope that makes some kind of sense. If it doesn't, tweet me and I'll do my best to explain it again.