Looking at data is always an interesting thing. The same for school-wide achievement data. For years we had the National Education Monitoring Project, which was focussed completely on providing a robust picture of where we are as an education system in NZ. In the last few days we have the release of the National Standards data for the country. It makes interesting reading, as much for the odd things as for the data itself:
* if we take out the magin of error, which I would guess is in the region of 3-5%, then there is in fact no difference across the two years. There is also little or no difference between the three areas of Literacy and Numeracy
* there is no european ethnicity registered. Therefore the data for Total includes maori and pacifika data. Given these groups under-perform on these measures with respect to many other ethnic groups, if we made a comparison group by group the differences would be LARGER than comparing to the total which also includes them. In reality maori are probably over 10% below the rest of the population across the year levels. For pacifica students then, this means it is more like a 15-20% difference.
* Year 7 must be hard. Across the board students are achieving lower in this year level than any other.
* Writing achievement falls to Y4 then rises again to Y6; Reading does the opposite. What explains this? Y7-8 patterns are identical.
* Maths is pretty random, except it gets harder as the years go on, with fewer students meeting expectations (if we made an overall trend line).
So …. an odd mix of outcomes, much of which validly says nothing (even if we ignore the other issues where I have been pretty clear about what I believe before). The one thing that does come through though is that we are hiding the extent of the difference between maori, pacifica, and other ethnic groups in the data. The situation is more pronounced than the graphs show.
It is interesting that there appears to be no deeper analysis of this information anywhere. Like in a school it is only when you delve into the data, make an effort to understand it and present it in valid ways, and draw some conclusions that the really interesting stuff comes to the fore.