Data Analysis

What is left behind now education’s Data Wave has receded?

Is data the solution to all education’s issues? About a decade ago the prevailing wisdom said it was. Advocates of this Data Wave argued that harvesting internal statistics would help schools solve issues such as teacher accountability and attainment gaps. As with all waves, after crashing onto the beach they recede, leaving space for another to roll in. In this blog, teacher, author and data analyst Richard Selfridge looks at the legacy of the Data Wave to see what schools can take from it.

Date04/04/24

AuthorRichard Selfridge

What message has the Data Wave left for educationalists?
photo: Jayne Harris/Unsplash

What was the Data Wave in education?

In ‘The Next Big Thing in School Improvement’ (2022), Professor Becky Allen, Matthew Evans and Ben White identify a series of ‘waves’ which had washed across the education landscape.

If you were working in schools in the 2000s you will probably remember the ‘Differentiation Wave’ where thinking shifted towards recognising and addressing the diverse needs of individual students.

Those in school now will be feeling the impact of the current ‘Curriculum Wave’ which advocates curriculum reform as a solution to educational inequalities.

In between those two waves was a ‘Data Wave’, which pushed data analysis as the dominant solution for educational issues.

The aftermath of this is still being felt in the school system.

What is the legacy of the educational Data Wave?

One lingering legacy is the notion of Expected Progress - the idea that schools, teachers and students could be judged using assessment data generated within the system.

Another of its legacies is the surplus of ‘tracking systems’.

These tend to encourage a short-term view of a student’s journey through school and endlessly ‘baselines’ them.

This could entrench a mindset which expends a great deal of effort generating and storing data with potentially very little impact on what actually happens in the classroom.

It is now rare to find a school in England which does not generate assessment information multiple times a year.

But, in my experience, it is equally rare to find a school which actually does much of genuine use with this data other than worry about it.

How can data be used to improve education outcomes and efficiency?

Research summarised by the Education Endowment Foundation suggests that schools should focus on quality teaching, targeted academic support and wider strategies to maximise their impact.

Where students aren’t keeping up with their peers, schools need to act quickly to provide support.

High-quality data will help identify what is working and what is not.

That analysis will guide schools to make changes which can have a direct impact on outcomes for those needing additional support.

How can schools use statistics to guide teaching priorities?

Schools can use a range of data to identify which students are in school, in class, focused and learning what we want them to.

The data will show that, provided they are developing as expected, this group needs the lightest of touches.

At the same time it gives schools clarity about which children do need support.

If significant numbers of students in any given school need help to ensure they are in school or in class, good data will identify who they are and allow support to be focused on them.

That, in turn, will generate more in-depth data which will help schools understand and address the challenges these students face and help them to get back on track as soon as possible.

This sounds deceptively simple but requires an understanding that high-quality assessment data, although crucial, is only one part of the statistical toolkit schools need.

It is most effective when combined with contextual and developmental data as well as details of any support given to pupils in the past.

How do schools create the best data?

So, what should schools be doing to ensure that they are generating the highest quality student assessment data?

A good start is to ensure that all those involved in creating, collating and analysing student data have a good understanding of both the benefits and potential pitfalls of using assessment data to summarise educational experiences.

Understanding how and why assessments are standardised, for example, and how data can be used to build pictures of students over time can help avoid expending time and energy on low-grade data which may misinform or misdirect.

What has the education Data Wave left behind?

Given the increasing power we have to generate and collate information, harnessing data on students will become more - not less - necessary in future.

Schools have every reason to focus on increasing the efficiency and effectiveness of their systems to process, analyse and act on student data so that they take less time to generate more useful information on which they can act.

The ‘Data Wave’ may have washed over education and receded, but it has left behind the knowledge that developing a strategic approach to refining use of student data will ensure that what remains will make a difference where it counts, reducing unproductive effort and focusing on getting support to where it is most needed.

Richard Selfridge is a teacher, education data consultant and author. His latest book, Using Student Data is due to be published later this year.

As part of AQi’s work, we are inviting people from a wide range of viewpoints to engage with us on a wide range of topics. We welcome alternative views to help stimulate discussion and ideas. The views of external contributors do not necessarily represent the views of AQi or AQA.

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