论文标题
IP地理位置低估了MOOC使用中的回归经济模式
IP Geolocation Underestimates Regressive Economic Patterns in MOOC Usage
论文作者
论文摘要
大规模开放的在线课程（MOOC）承诺将使所有人都可以接受严格的高等教育，但是先前的研究表明，注册人往往来自具有较高社会经济地位的背景。我们在2012年至2018年之间在约76,000个美国注册中研究了约76,000个美国注册的地理经济模式，使用IP地理位置和用户报告的邮件地址确定注册人的位置。通过指标，我们发现繁荣或人口密度更高的邮政编码之间的注册率更高。但是，我们还发现IP地理位置偏见的证据：在地理和经济上，对于来自经济困难的地区的用户而言，它在地理和经济上造成了更大的错误；它不成比例地将用户置于繁荣的地区。它低估了MOOC注册中的回归模式。研究人员应在MOOC研究中使用IP地理位置，并考虑影响其其他学术，商业和法律用途的类似经济偏见的可能性。
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 about 76,000 U.S. registrations for about 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.
