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The Writing Pal is an intelligent tutoring system designed to support writing proficiency and strategy acquisition for adolescent writers. A fundamental aspect of the instructional model is automated formative feedback that provides concrete information and strategies oriented toward student improvement. In this paper, the authors explore computational methods for expanding automated feedback by taking into account students' essay revising patterns. High school students (n = 87) used the Writing Pal to write and revise a persuasive essay each day across eight daily sessions. Analyses of the linguistic properties of original and revised essays revealed that students were more likely to implement document-level revisions focused on improving elaboration, organization, and cohesion, rather than surface word-level edits focused on incorporating bigger words or less common words. Implications and applications of essay revising data for automated feedback and essay scoring are discussed.