Identifying course characteristics associated with sociodemographic variation in enrollments across 159 online courses from 20 institutions.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 33052947.
- Also identified by DOI 10.1371/journal.pone.0239766 and PMC identifier 7556443.
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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.
Medical subject headings
- Computer-Assisted Instruction
- Curriculum
- Education, Distance