Meeting the needs of WriteLab's three end users: students, instructors, and writing centers, meant knowing what their pain points were, and what they were trying to accomplish. To find the right experience that our users would find familiar, appealing, and rewarding, the UX and UI of the product was influenced by web apps ranging from music platforms to development tools.
Scenario: Students wait until the last minute to write an essay, then turn it in. Instructors use most of their time grading low-level errors, instead of substantial arguments and content. This is the classic pain point of countless writing instructors that drove WriteLab into existence.
WriteLab uses natural language processing and machine learning to identify a range of writing features. Data mining, along with input from users, allows the program to algorithmically generate responses into writing feedback.
As a software program, WriteLab goes beyond just fixing grammar and spelling by responding to sentence-level features of prose, helping users every step of the way by drafting, revising, polishing, and proofing writing. WriteLab also has capabilities to help instructors assign work, respond to student writing, and review student progress. In sum, it's an all-in-one writing tool.
For instructors, WriteLab offers actionable analytics about student progress across multiple drafts and essays. Creatively, WriteLab's analytics features line graphs and pie graph views that display students' strengths and weaknesses, as well as the number of comments for each draft.
Product Designer // WriteLab