  We present the design and evaluation of a web-based intelligent writing
assistant that helps students recognize their revisions of argumentative
essays. To understand how our revision assistant can best support students, we
have implemented four versions of our system with differences in the unit span
(sentence versus sub-sentence) of revision analysis and the level of feedback
provided (none, binary, or detailed revision purpose categorization). We first
discuss the design decisions behind relevant components of the system, then
analyze the efficacy of the different versions through a Wizard of Oz study
with university students. Our results show that while a simple interface with
no revision feedback is easier to use, an interface that provides a detailed
categorization of sentence-level revisions is the most helpful based on user
survey data, as well as the most effective based on improvement in writing
outcomes.
