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AI is good at narrow, prescribed tasks, it is hopeless at general tasks. This, in my view is why big data and learning analytics projects are less appropriate in learning than more precise, proven uses of AI. There’s a paucity of data in learning and it is often messy, difficult to access and subject to overfitting and other problems when trying to make predictions.
On the other hand, using specific techniques at specific points on the learning journey – engagement, support, delivery and assessment, one can leverage AI to best effect. So here’s five ways this was done in 2018, in real projects, in real organisations, some winning major awards.
