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Identifying course characteristics associated with sociodemographic variation in enrollments across 159 online
René F Kizilcec1, Anna Kambhampaty1
1Department of Information Science, Cornell University, Ithaca, New York, United States of America.
Abstract:
Millions of people worldwide use online learning for post-secondary education and professional development, but participation from historically underrepresented groups remains low. Their choices to enroll in online courses can be influenced by course features that signal anticipated success and belonging, which motivates research to identify features associated with sociodemographic variation in enrollments. This pre-registered field study of 1.4 million enrollments in 159 online courses across 20 institutions identifies features that predict enrollment patterns in terms of age, gender, educational attainment, and socioeconomic status. Among forty visual and verbal features, course discipline, stated requirements, and presence of gender cues emerge as significant predictors of enrollment, while instructor skin color, linguistic style of course descriptions, prestige markers, and references to diversity do not predict who enrolls. This suggests strategic changes to how courses are presented to improve diversity and inclusion in online education.
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