How do OfSTED determine which schools to inspect? On Wednesday 11th April, I attended an NAHT meeting, a new commission on accountability, spanning every phase and sector of education. Over the next few months it will canvass the views of some of the foremost thinkers in this area of education policy with the aim to have interim findings before the summer term and to publish our full report in September 2018. This post captures a presentation delivered by an OfSTED representative and not the meeting itself. When will [XYZ school] be inspected?

Ofsted has said that from next term a computer algorithm will be used in deciding whether to inspect good and outstanding schools. In a methodology note published today, the inspectorate says that rather than using pre-determined thresholds on performance data, as in previous years, it will use "supervised machine learning" for the first stage of decision making from the summer term of 2018. It says that it has now created an algorithm which "has effectively produced a probability of a forthcoming inspection being less than good", which is known as the "raw risk score". "We believe [our new methodology] will improve our capacity to identify concerns about performance," the note states. The machine learning algorithm was created by looking at data on progress and attainment, school workforce data and parent view responses to see how it fitted with the known inspection outcomes.

The government's'Nudge Unit' is experimenting with using machine learning algorithms to rate how well schools and doctors' surgeries are performing. For the last year, The Behavioural Insights Team (BIT) has been trialling machine learning models that can crunch through publicly available data to help automate some of the decisions made by bodies such as Ofsted, which inspects schools, and the Care Quality Commission, which regulates health and social care in England. Michael Sanders, head of research at the BIT says it is working with Ofsted to put the technology into use during 2018. "We're working with them to feed into variations on our model and to improve it using additional data that they have that isn't public," he says. The school-evaluating algorithm pulls together data from a large number of sources to decide whether a school is potentially performing inadequately. It is said the system can help to identify more schools that are inadequate, when compared to random inspections.

Plans to use algorithms to identify failing schools have been criticised by the National Association of Head Teachers. A data science unit, part-owned by the UK government, has been training algorithms to rate schools, using machine learning - a form of AI. It plans to work with England education watchdog Ofsted to help prioritise inspections. The NAHT said effective inspection of schools should not be based on data. "We need to move away from a data-led approach to school inspection," the union said in a statement.