Wiki Education Foundation supports hundreds of college and university classes each term in which the students are assigned to improve Wikipedia articles, typically as an alternative to a traditional term paper. These classes use the Wiki Education Dashboard (site: dashboard.wikiedu.org , code: https://github.com/WikiEducationFoundation/WikiEduDashboard) to structure their Wikipedia assignments and track the Wikipedia edits that students make.

When students and instructors are confused or stuck, they can request help from Wiki Education staff, which creates a ticket in the Dashboard's email-based ticketing system, and then staff can answer their questions and help resolve any problems. This is basically a "help desk" system integrated into Wiki Education Dashboard.

For this project, you will analyze tickets from recent terms, with the goals of quantifying the prevalence of common questions and points of confusion, determining which topics are becoming more or less common from term to term, and identifying the highest priority user interface issues and missing features that might head off commonly encountered problems.

How exactly to accomplish this is an open question, and will depend on the skills and experience you (the intern) bring to it. Background in data science, natural language processing, human-computer interaction and/or sociology may be helpful.