Ofsted should use artificial intelligence to determine which schools will fail, a report has suggested.
Researchers from the Behavioural Insights Team, which operates in partnership with the Cabinet Office, examined how data science can be used to inform policy.
They found that a combination of the right data and machine learning can predict whether a school will be rated inadequate or requires improvement.
Previous inspections, census information, and workforce data are used to build an algorithm, all of which is publicly available.
Ofsted is already using statistical models to target inspections at the schools which are in the most desperate need of improvement, the report said.
Data analysts who compiled the report found that 65 per cent of ‘requires improvement’ and ‘inadequate’ schools were within the 10 per cent of schools identified as highest risk by the model they built.
Writing the forward to the report, John Manzoni, the chief executive of the Civil Service, said: “The huge growth in data, and in tools for analysing it and putting it to use, has changed the world and continues to do so.
“There is great potential for government to improve the performance and productivity of services through the smarter use of data.
“This data includes outcomes, use patterns, costs, and citizen experiences. With this wealth of data, we have an obligation to make government services the best they can be.”
Mr Manzoni said that using data science to inform policy is key to driving innovation in Government.
The National Association of Head Teachers (NAHT) warned against a using a “data-led” approach to school inspections.
“It is important that the whole process is transparent and that schools can understand and learn from any assessment,” a spokesman for NAHT said.
“Leaders and teachers need absolute confidence that the inspection system will treat teachers and leaders fairly.”
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Author: || World Economic Forum