Daniel Hocutt of Old Dominion University is curating a conversation at Media Commons on algorithms, specifically what kind of influence educators can have over how they are designed and deployed. The whole conversation is worth reading, but our own Bill Hart-Davidson has contributed a short essay in which he discusses the dangers of teaching students to write for algorithms and how algorithms might instead aid the human work of teaching and learning:
Rather than trying to create machines that read (or write) like humans, we can instead create systems that give humans a chance to focus more on how we might improve as writers and communicators.
Bill gets specific when talking about how that approach has shaped the development of Eli Review:
In our peer learning service Eli Review, for instance, we track activity – feedback that reviewers and instructors give to writers, as well what writers do with that feedback – to evaluate the “helpfulness” of a review. We do this as a way to help students learn to become better reviewers, something which itself has been shown to improve writing performance.
Bill discusses other work by the WIDE Research Center (where Eli was originally created) related to algorithms and the ways they can be used to “make the world more human”.
Photo credit: Vintage Toys, Mint Museum of Toys, Singapore