Could AI play a role in boosting literacy rates?

Jayne Mullane, headteacher at Mersey Vale Primary, reveals how artificial intelligence is having a positive impact on her pupils’ reading attainment

Reading skills are the cornerstone of a child’s education, which is why I am so encouraged to see that literacy rates across the country are on the rise. In the latest SATs results, 75% of pupils met the expected standard in reading at Key Stage 2, which is an increase of four percentage points on last year.

That’s great news, because without secure reading attainment, children can so easily fall behind in all areas of the curriculum and, once that happens, it’s hard for them to make up for lost time.

So, catching problems early is crucial, and being able to identify reading difficulties in younger pupils and help to address them can make a big difference.

But could artificial intelligence (AI) be the key to helping schools do this?

Helping teachers not replacing them

In the past few years, we have become increasingly aware of the positive impact AI is having on people’s lives; in helping doctors detect illness, for example, or assisting banks in preventing fraud. But mention AI in education and, for many people, the unwelcome image of a robot teacher springs to mind.

However, the role of AI in education is not to replace teachers, with all their valuable human skills and years of experience; rather, it is to help schools uncover patterns they might not otherwise detect.

Take, for instance, a tool that can help teachers spot which children are finding reading difficult by tracking the way their eyes move when they read aloud from a piece of text.

“Eye-tracking tests revealed examples of children who were not previously identified as having reading difficulties.”

Machine learning in action

Like any school, Mersey Vale relies heavily on traditional reading comprehension tests, along with teacher assessments, to evaluate pupils’ reading. But AI innovations – such as Lexplore’s revolutionary eye-tracking technology – can add startling new insight into pupils’ reading attainment.

Children whose eyes rest longer than usual on one word, and move more slowly along a line of text, find reading more challenging. Knowing this you can provide targeted support to help them build on their literacy skills.

And the beauty of machine learning technology is that it can get better the more it is used. The tool can be trained how children read so that, as more schools start to use it, the more accurate the picture of pupils’ reading attainment will be in the future.

Fun is an essential ingredient

But does such a highly technical concept – built on complex algorithms, based on years of academic research – have a place in a primary school classroom?

Absolutely. From the pupils’ point of view, the Lexplore assessment is fun, enjoyable and interesting. Readers of all levels told me that they loved doing the tests, and it made a welcome change from the written assessments they are used to.

Jayne Mullane

My teachers were equally full of praise for the tests. When I initially announced that we would be screening all of our children from Years 2 to 5, I imagine the staff were a little apprehensive about the additional workload this would entail.

But the time-saving power of technology came to the rescue, because the tests only took a couple of minutes for each pupil and we easily fitted them in to the daily routine.

Informing discussions on reading

The real power of this type of technology is the added dimension it can give schools in sharing information about pupils’ reading with teachers and parents. In our case, the eye-tracking tests revealed examples of children who were not previously identified as having reading difficulties.

One pupil in particular had developed effective coping strategies to manage these difficulties. The child was verbally very strong and, presumably, had been using other cues – such as images – to help them understand any text they were reading. As she was very capable, her issues with reading were not uncovered. However, following the tests, we talked to the child’s parent ,who had also noted a certain reluctance to read at home.

We provided additional support and gave the pupil interesting reading material with simpler text, and are now seeing the impact of that intervention.

For pupils already receiving literacy support, the extra insight we gained from the tests helped us to ensure that targeted interventions were put in place before the children moved up a year. By re-testing selected groups of pupils, we can check that these interventions are working.

We live in an exciting age, where advances in AI – combined with the traditional know-how of teaching – can help children secure the core skills they need for the journey ahead.

If you want to know more about using eye tracking in your classroom, visit