Machine Learning And The Future Of Education

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When publishing on the Internet, content creators have considerable insight into what readers are doing, whether it’s where they’ve come from, how much they consume and whether they share content on social media.  This real-time feedback has allowed publishers to tailor content specifically to the needs of their audience.

Suffice it to say, with the trusty paperback book, this kind of feedback isn’t available, and it creates a bit of a black box, whereby the only real feedback authors and publishers get is via things like reviews, awards and sales figures.

With books entering a digital age however, they bring with them the possibility of richer feedback for readers, teachers, authors and publishers alike.  I spoke recently with Alfred Essa, Vice President, Analytics and R&D, at McGraw-Hill Education ahead of his presentation at the Predictive Analytics Innovation Summit, and he explained how data is driving innovation, both at his company and in education more generally.

 

Transforming The Learning Experience

They are attempting to move away from the traditional, one size fits all way of learning that doesn’t really reflect a more complex reality.  Because, not only do people learn at different speeds, but they often arrive from different start points and with different backgrounds.

The use of digital books and adaptive learning allows for a much more tailored and customizable learning experience, as teachers now have access to data on what exactly students are consuming, and how they’re coping with the concepts they’re trying to learn.  Armed with this data, teachers can see if a student, or the class as a whole, is not grasping certain ideas or topics. This insight allows teachers to adjust their lessons accordingly and help at-risk students from falling behind or dropping out.

 

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Author: Adi Gaskell