Mapping Generational Digital Literacy and Internet Usage Patterns in Open and Distance Learning: A K-Means Clustering Analysis - Selly Anastassia Amellia Kharis; Melisa Arisanty; Anton Robiansyah; Arman Haqqi Anna Zili (Jurnal Kependidikan : Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran, dan Pembelajaran, 2026)
This study aims to map digital literacy and internet-use patterns among multigenerational new students in open and distance learning (ODL) and to determine whether the resulting profiles are differentiated solely by generation or also by occupational and behavioral characteristics. A quantitative exploratory design with K-Means cluster analysis was applied to data from 4,371 new students at Universitas Terbuka Jakarta. The analysis integrated generational profile, occupation, internet-access time, dominant online activity, preferred social-media platform, daily social-media duration, and digital-literacy classification. The Elbow Method indicated a five-cluster solution. The cluster represented 17.00%, 24.94%, 18.39%, 9.40%, and 30.27% of respondents, respectively. Overall, 62.18% of students were classified as High and 35.69% as Very High in digital literacy, while only 2.13% were Satisfactory and none were Low or Very Low. Cluster 3, dominated by Generation Y private employees, contained 97.01% Very High-literacy students, whereas Cluster 5, also dominated by Generation Y private employees, contained 98.49% High-literacy students. Generation Z appeared across three clusters with distinct access timed and online activities. These findings show that generation alone does not adequately explain digital-literacy patterns in ODL; occupational background and digital-use behavior provide additional differentiation. The results supports cluster-based digital-literacy support, flexible learner services, and targeted skill development in ODL.