IP地理定位低估了MOOC使用中的回归经济模式

Daniela Ganelin, Isaac L. Chuang
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引用次数: 4

摘要

大规模在线开放课程(MOOCs)承诺让每个人都能接受严格的高等教育,但之前的研究表明,注册者往往来自较高的社会经济地位背景。我们研究了2012年至2018年间约76,000个美国注册的约600个HarvardX和MITx课程的地理粒度经济模式,通过IP地理定位和用户报告的邮寄地址确定注册者的位置。无论采用哪一种衡量标准,我们都发现,在更繁荣或人口密度更高的邮政编码地区,注册率更高。然而,我们也发现了IP地理定位存在偏见的证据:对于来自经济困难地区的用户来说,它在地理和经济上都造成了更大的错误;它不成比例地将用户安置在繁荣地区;它低估了MOOC注册的回归模式。研究人员应该在MOOC研究中谨慎使用知识产权地理定位,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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IP Geolocation Underestimates Regressive Economic Patterns in MOOC Usage
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.
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