Many of you will have downloaded this already but I thought it’d be useful to put it on my blog. For those who don’t already have it, it’s a rather low tech and unexciting word document designed to guide you through ASP and pull out the useful data. Aim is to summarise the system down to a few pages.
You can download it here
The file should open in Word Online. Please click on the 3 dots top right to access the download option. Please don’t attempt to edit online (it should be view only anyway). Also, chances are it will be blocked by schools computers (schools always block my stuff).
A couple of points about the template:
1) Making sense of confidence intervals
Only worry about this is progress is significantly below average, or if data is in line but high and close to being significantly above.
If your data is significantly below average, take the upper limit of the confidence interval (it will be negative e.g. -0.25). This shows how much each pupils score needs to increase by for your data to be in line (0.25 points per pupil, or 1 point for every 4th pupil). Tip: multiply this figure by the number of pupils in the cohort (eg. -0.25 x 20 pupils = -5). If you have a pupil – for whom you have a solid case study on – that has a score at least equal to the result (i.e. -5 in this case), removing that pupil from the data should make your data in line with national average.
If your data is in line and you are interested to know how far it would need to shift to be significantly above, note the lower part of the confidence interval (it will be negative, e.g. -0.19). This again shows how much your data needs to shift up by, but in this case to be significantly above. In this case, each child’s score needs to increase by 0.2 points for the overall progress to be significantly above (we need to get the lower limit of the confidence interval above 0 so it needs to rise by slightly more than the lower confidence limit). Obviously pupils cannot increase their scores by 0.2, so best to think of it as 1 point for every 5th child. Or. as above, multiply the lower confidence limit by the number of pupils in the cohort (e.g. -0.2 x 30 pupils = -6). If you have a pupil with a score at least equal to this result (i.e. -6) then removing them from the data should make the data significantly above average.
Easiest thing to do is model it using the VA calculator, which you can download from my blog (see August) or use the online version www.insighttracking.com/va-calculator
2) Difference no. pupils
This has caused some confusion. It’s the same concept as applied in last year’s RAISE and dashboards. Simply take the percentage gap between your result and national average (e.g. -12%), turn it into a decimal (e.g. -0.12) and multiply that by the number of pupils in the cohort (e.g. 30). In this case we work out ‘diff no. pupils’ as follows: -0.12 x 30 = -3.6. This means the schools result equates to 3 pupils below average. If the school result is above national then it works in the same way, it’s just that the decimal multiplier is positive.
If you are calculating this for key groups, then multiply by the number in the group, not the cohort. For example, the 80% of the group achieved the result against a national group result of 62%, which means the group’s result in 18% above national. There are 15 pupils in the group so we calculate ‘diff no. pupils’ as follows: 0.18 x 15 = 2.7. The group result therefore equates to 2 pupils above national.
I hope that all makes sense.
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