The Hoodies
Parents worry about whether their kid will get into the right school, making sure they understand the application process and not missing deadlines. School principals and staff worry about having too few enrolments (and perhaps having to lay off staff) or being over-subscribed and having to expend significant resources dealing with anxious parents who miss out.
The Victoria Government now has an excellent website - https://www.findmyschool.vic.gov.au/ - that provides clear guidance on whether a child is elgible to attend a school, the criteria that underpins that decision and the appeal process. The centrepiece is a form where parents type in their address and can see the primary, secondary or special school in their designated neighbourhood.
However, the website doesn't resolve the issues of parents 'school shopping', the desire to find the 'best' school (say based on schools' Naplan or ATAR rankings which various websites and media are happy to offer) rather than accept that the local school is where their child should attend.
We believe that to overcome this 'ranking' focus, schools need to deepen their relationship with parents and influencers (the wider community) in their zone ideally well before the parents are at the stage of choosing a school. We want parents to really bond with their school, and that the designated school become the school of choice.
We believe data has a role to play. Schools that have good intelligence on their catchment area can own the zone. Knowing the population, number of kids, religious institutions, volunteer groups and so on can help the schools engage with that zone.
Unfortunately, although there is a wealth of data out there, the sample area is never the school zone. With school zones crossing postcodes and suburbs, data at this level is very inaccurate, even if schools could easily find it.
Our solution, Schools in the hood, will provide lots of data groups, filtered by relevant school zone. All this happens in the back end using our own api. The school can access the data on a website tailored to their school. The website will have other functionality as well.
The data at https://discover.data.vic.gov.au/dataset/victorian-government-school-zones-2020 is the most critical resource. We also use ABS meshblock data and SA1 data which we use as building blocks to replicate the shape of the schools zones as closely as possible. Once we have these 'aggregate masks', we can zonify any data from data.gov.au or other database that is in meshblock or SA1 form. Note we weren't able to solve 'zonify transformation' work during the hack, but have no doubt it is a relatively straightforward 'spatial joins' job for a professional data scientist.
Description of Use Each meshblock unit covers a very small area. One can combine many meshblocks to form an area that is a reasonable fascimile of a school zone. Our solution will do this for every school zone in Victoria. Once done, this allows any meshblock-based data out there that covers Victoria to be filtered by school zone. A similar approach can be taken with SA1 data.
Description of Use Population is an example of a dataset at the meshblock level. The solution will be able to aggregate population from the meshblock level to the school zone level.
Description of Use This data tells us the shape and dimesions of each school zone or neighbourhood. In our solution, each zone is used as a mask or template to aggregate meshblock or SA1 data so that many disparate forms of data can be filtered to the relevant zone level.
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