'We need to gather as much data as we can': How AI could change everything about education

COVID-19 has been a trial by fire for technology in education, but the sector needs to gather what it has learnt quickly if it wishes to edge forward with digital transformation.

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The coronavirus lockdown and the school closures that have resulted have had a huge impact on the education of 1.2 billion children across 186 countries. Teachers have been scrambling to keep in touch with their classes, while parents have been trying to keep bored children engaged in learning while cut off from school and fellow students. 

As a result, virtual classrooms, language apps, online tutoring, and online education software (and new hardware) have seen a surge popularity, with some reports suggesting  the market could hit $350 billion by 2025.  But can the digital revolution in education, long been promised but rarely achieved, take a step forward as a result of these changes?

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Speaking at the CogX 2020 conference, Rose Luckin, professor of Learner Centered Design at University College London's Knowledge Lab, argued that the only way for the industry to evolve was to build on what it has learnt recently.

"We owe to everyone who has sacrificed their time and endured hardships during this time to make sure lessons are learnt and we build on these to move things forward," said Luckin.

"We need to gather as much data as we can so we can build on this and implement it in the long term. This will ensure that, first of all, we don't go back to the old way of doing things, but also so we can start to meaningfully digitize and transform the industry, long term."

But digitization doesn't just mean moving things online. Putting a teacher on one end of a webcam and the class on the other is a sure-fire way to disengage students, and lose much of what makes teaching so valuable.

"Just having the resources doesn't mean you can provide effective education," said Luckin. "Taking what works offline and taking it online doesn't necessarily work."

Instead, innovation needs to focus on real teaching problems. One example would be removing the bottlenecks in the examination process that are hindering wider change in the system.

This would help to unlock a lot of changes that really need to happen, said Luckin.

"It is perfectly possible to do continuous formative assessment using various different technologies," she added. "We could assess more than subject areas – we could look at resilience, self-efficacy – we could look at so much."

Another key facet of meaningful digitization is bringing teachers – and potentially parents – into discussions around the introduction of new technology. After all, those working in education need to be familiar with the digital tools they could be using in the years down the line.

"Ed-tech firms are nearly always started by computer scientists, but teachers are rarely brought to the top table to inform design," offered David Lefevre, director of the Edtech Lab at Imperial College Business London.  

"This needs to change – all parties need to have an equal voice and work together... If teachers just sit back and wait for technology companies to solve the problem for them, the results might not be the utopia we're hoping for."

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Lefrve also addressed what he considered a conflict between traditional, practical education systems and the need to make learning a more personalized experience for individual pupils. "We know that education is a deeply human experience," he said.

"The greatest use of technology within education would be to introduce a much larger degree of personalization to students, so they get a lot more personal attention, they can find their passion and they can find their areas of expertise. That's the utopia that we're hopefully heading towards."

But for all this, technologies like AI could remain a hard sell for the education sector. "It's hard to sell something transformational into an industry that hasn't transformed," said Luckin. 

"When it comes to AI, it is fundamental that teachers fully understand what it is and how it can work for them, [but] we also need to make sure AI developers understand what teaching involves."

The first step toward this, Luckin suggested, was encouraging schools, universities and other academic institutions to view themselves through the data lens; gathering all the necessary information to provide a view of the industry, and then identify the problems that need to be addressed.

In some ways, COVID-19 may have provided such an opportunity. "What we've seen through COVID is education digitized en masse," said Leferve. 

"Certainly, lots of things will go back to the way they were done before – people will go back into classrooms, I'm sure – but lots of these digital processes will remain. I hope what we've seen is a lot of progress toward that digitization. 

"Then we can bring the power of computers, AI, machine learning and analytics to bear."

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