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Although Massive Online Open Courses (MOOCs) have the promise to makerigorous higher education accessible to everyone, prior research has shown thatregistrants tend to come from backgrounds of higher socioeconomic status. Inthis work, I study geographically granular economic patterns in registrationfor HarvardX and MITx courses, and in the accuracy of identifying users'locations from their IP addresses. Using ZIP Codes identified by the MaxMind IPgeolocation database, I find that per-capita registration rates correlate witheconomic prosperity and population density. Comparing these ZIP Codes withuser-provided mailing addresses, I find evidence of bias in MaxMindgeolocation: it makes greater errors, both geographically and economically, forusers from more economically distressed areas; it disproportionately geolocatesusers to prosperous areas; and it underestimates the regressive pattern in MOOCregistration. Similar economic biases may affect IP geolocation in otheracademic, commercial, and legal contexts.

Differences in Online Course Usage and IP Geolocation Bias by Local Economic Profile