Can babies teach us how to build smarter machines? Yes, says cognitive scientist Moira Dillon. What we know about how babies learn should inform how we design machines with AI (Artificial Intelligence). When AI is modeled after human intelligence, we will get better, smarter machines, and in turn, we can test how human knowledge is built and perhaps improve human cognition. Dillon proposes testing cognitive science-based AI and babies’ intelligence in tandem and on a large scale, allowing results from one field to inform the other. Read more > here.
Many people—including teachers—believe that innate ability is key to learning certain subjects, such as math. How do beliefs about the role of innate abilities affect students’ intrinsic motivation to learn math? Anke Heyder and her research team found that low-achieving students had less interest and enjoyment in math when their teachers strongly believed that innate ability was crucial to their learning. The researchers suggest that teachers concentrate on growth and learning rather than innate abilities as they seek to motivate all students. Read more > here.
A self-described former “math flunkie,” Barbara Oakley mined techniques from neuroscience and cognitive psychology to teach herself how to learn difficult material. She is now an engineering professor who also teaches students how to learn to learn so they can master math and develop analytical skills. Her free popular Massive Open Online Course (MOOC), “Learning How to Learn,” draws 6,000 new subscribers each week. That success has spurred Oakley to advocate for MOOCs as an efficient, inexpensive means to bring high-quality education to large populations worldwide. Learn more > here.
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