Formative Essay Feedback Using Predictive Scoring Models


A major component of secondary education is learning to write effectively, a skill which is bolstered by repeated practice with formative guidance. However, providing focused feedback to every student on multiple drafts of each essay throughout the school year is a challenge for even the most dedicated of teachers. This paper first establishes a new ordinal essay scoring model and its state of the art performance compared to recent results in the Automated Essay Scoring field. Extending this model, we describe a method for using prediction on realistic essay variants to give rubric-specific formative feedback to writers. This method is used in Revision Assistant, a deployed data-driven educational product that provides immediate, rubric-specific, sentence-level feedback to students to supplement teacher guidance. We present initial evaluations of this feedback generation, both offline and in deployment.

In KDD 2017
Bronwyn Woods
Data about plants riding bicycles?