Automated marking

by Amy Woodgate

Re-humanising the de-humanised – automated marking is nothing without the carefully articulated human-input evidence base. It needs a suitable volume of steer to make judgements and try to create algorithms to simulate the thinking of the academic markers.


“But think about this. Machine learning can assess students’ work instantly. The output of the system isn’t just a grade; it’s a comprehensive, statistical judgment of every single word, phrase, and sentence in a text. This isn’t an opaque judgment from an overworked TA; this is the result of specific analysis at a fine-grained level of detail that teachers with a red pen on a piece of paper would never be able to give. What if, instead of thinking about how this technology makes education cheaper, we think about how it can make education better? What if we lived in a world where students could get scaffolded, detailed feedback to every sentence that they write, as they’re writing it, and it doesn’t require any additional time from a teacher or a TA?

That’s the world that automated assessment is unlocking.”