Abstract
The educational applications of AI are a combination of what Pasteur's Quadrant describes as use-inspired basic and pure applied research. This article gives an overview of the classical and emerging architectures for AI in education. Early researchers focused on creating personalized teaching systems based on solitary learners, whereas recent work takes account of other people and the learning context. Various Grand Challenges illustrate the issues still facing AI in education.
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