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Bridging AI Research and Education Practice to Drive Changes in the Ecosystem of Innovation

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From the November 13th 2017 Symposium “Innovation Ecosystems for AI-Based Education, Training and Learning” Bruce McCandliss, Professor, Stanford Graduate School of Education and (by courtesy) Psychology at Stanford University addresses these points...
1. Setting the stage of the eco-system for educational innovation: who are the stake-holders? What limits their engagement and innovation?
2. AI research plays out at multiple, interacting levels of complexity: i.e. neural systems (biological and artificial), the whole developing child, the school classroom and school district level.
3. Systems neuroscience may provide a key level of explanation for a learner’s trajectory through a learning environment.
4. Educational systems have increasing degrees of freedom for differentiated instruction and engagement.
5. AI, when combined with insights from the Learning Sciences, may provide decision relevant information to enhance children’s development during the early school years, enabling schools to become learning institutions that learn.
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Academic
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