IP Geolocation Underestimates Regressive Economic Patterns in MOOC Usage
Abstrak
Massive open online courses (MOOCs) promise to make rigorous higher education accessible to everyone, but prior research has shown that registrants tend to come from backgrounds of higher socioeconomic status. We study geographically granular economic patterns in ~76,000 U.S. registrations for ~600 HarvardX and MITx courses between 2012 and 2018, identifying registrants' locations using both IP geolocation and user-reported mailing addresses. By either metric, we find higher registration rates among postal codes with greater prosperity or population density. However, we also find evidence of bias in IP geolocation: it makes greater errors, both geographically and economically, for users from more economically distressed areas; it disproportionately places users in prosperous areas; and it underestimates the regressive pattern in MOOC registration. Researchers should use IP geolocation in MOOC studies with care, and consider the possibility of similar economic biases affecting its other academic, commercial, and legal uses.
Topik & Kata Kunci
Penulis (2)
Daniela Ganelin
Isaac L. Chuang
Akses Cepat
- Tahun Terbit
- 2019
- Bahasa
- en
- Total Sitasi
- 7×
- Sumber Database
- Semantic Scholar
- DOI
- 10.1145/3369255.3369301
- Akses
- Open Access ✓