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The Feedback Prize: A Case Study in Assisted Writing Feedback Tools

Authors
Perpetual Baffour,
Scott Crossley,
Yu Tian,
Alex Franklin,
Natalie Rambis,
Meg Benner,
Ulrich Boser
Date
Publisher
The Learning Agency Lab
Teachers must be on AI writing tools to impact student outcomes, and our research highlights the importance of involving teachers at various stages of the AI development process from data collection to evaluation of performance in order for these algorithms to have a significant impact. Our research also showed that machines alone are not enough, and AWFTs are best viewed as tools to support teachers rather than a cure-all. High-quality algorithms are able to demonstrate human-comparable accuracy in evaluating student writing, showing machines can be as effective as humans in evaluating student work and indicating the potential of algorithms to provide valuable feedback.
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