After writing a book ‘AI for Learning’, I have given a lot of talks and podcasts on the need to use smart software to make people smarter. That means using the technology of the age – AI and data. In the book (p228), and in many of these talks, I explained how China is forging ahead with AI in this field. Unlike the West, China has focus, investment and a view that access to education needs to be cheaper, faster, smarter and with a massive increases in access.
Meanwhile, we continue with a view that Higher Education needs to remain scarce and expensive, very expensive. We put more attention into AI and Ethics than real projects. Our Universities and colleges do little more than write reports on AI for learning. That’s a shame.
Meanwhile the Open University of China has been awarded a UNESCO Prize for its use of AI to empower rural learners. Their ‘One College Student Per Village’ is an ambitious and inspiring initiative that puts equitable access at the heart of their offer. This is all about improving access to education for the poor. Running since 2004, financed by the Chinese Ministry of Education to tackle access problems, it does far more than reach out with infrastructure. AI lies at the heart of their efforts to provide scalability.
Scalability
In its efforts to provide quality learning experiences, the OUC set up over 500 cloud-based classrooms and smart classrooms in poorer areas in 31 provinces, municipalities and autonomous regions. The trick was to make the courses demand-led by asking what local people wanted and providing largely practical, vocational courses. They also built the courses to be accessible on mobile devices for farmers and those in rural professions and places. The numbers are impressive:
· 29 programmes (using AI)
· 825,827 learners enrolled
· 529,321 graduated
· 1,500 OUC study centres
· 300 online courses
· 100,000 mini-lectures
· all open to general public
AI for Learning
But the secret, sweet without the sour sauce, is AI. The learning is personalised using personal and aggregated data. This adaptive learning means that different students take different paths through the courses, a bit like the SatNav or GPS in your car, go off course, and it re-sequences content and provides feedback to get you back on course. I’ve been working with this for five years – believe me it works.
The really clever stuff is the use of AI to recognise text (text to speech), as well as semantic analysis of answers. This allows open input from students, as opposed to MCQs. I’ve also been working with this for some time in WildFire. This approach allows learners to answer or ask questions which are automatically recognised through semantic analysis, then feedback automatically provided by the system. This feedback (should really be called feedforward) is what oils the wheels of learning and provides real scalability. The immediate feedback with learning opportunities means that the system does not depend as much on human tutors. Semantic analysis of learner answers is something we’ve implemented. It is powerful and pedagogically superior to MCQs as it is more realistic, requires greater cognitive effort and can be more diagnostic for the purpose of feedback.
They also use AI for knowledge mapping, automatic content generation and smart chatbots for 24/7 online learner support. This use of AI for content creation is something we’ve been doing at WildFire. It reduces the cost of learning per student, as new content can be created quickly from documents, PowerPoints and videos. The point is to create content quickly, cheaply but using AI for semantic analysis and retrieval practice for high retention.
AI and assessment
The automation of assessment and essay marking is what allows them to scale sophisticated learning to so many people free from the tyranny of time, place and expensive human effort. Automating much of the assessment allows human tutors to focus on closing knowledge and skills gaps, rather than marking. As Li Ganged, a tutor at the OUC says, “Automated essay scoring is efficient in that I don’t have to mark these assignments myself but I can get a clear picture of where learners need help.” This idea of using AI to create assessments on all of your content at little extra cost is also something we've been doing using AI.
Conclusion
Another feature of this initiative, something our rigid system can’t really handle is the mix of programmes, degrees, diplomas and short courses. The focus on vocational training is also something we desperately need but underfund in favour of longer degree courses. We have to move beyond our sclerotic system of high cost content creation, high cost delivery and dependence on physical campuses. There’s too much at stake here for us to focus on education of the few at the expense of the many. Who would have thought that China is leading the way. They’ve just clocked up over 18% of economic growth but it’s not just about that, it’s the simple fact that they are leading the world in educational innovation.
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