2026-10-06T19:51:09Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33950767 2026-10-01T05:44:10Z category_26143 item_type_3 month_year_10_2026

From online early warning to student support Ling Dai (24718043) Jingru Qu (24717976) Higher education learning analytics online learning <p dir="ltr">Online early-warning systems use learning analytics to identify students at risk, but the resulting predictions do not determine how finite human support should be allocated. This study develops a five-stage analytical framework linking allocation to outcomes: allocation, delivery, response, repeat allocation, and final outcomes. It compares risk-agnostic random allocation, highest-risk allocation, and risk-band randomization under equal capacity. </p> 2026-10-01T05:44:10Z Dataset Dataset 10.6084/m9.figshare.33950767.v2 https://figshare.com/articles/dataset/From_online_early_warning_to_student_support/33950767 CC BY 4.0