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Macfadyen, Leah P.; Dawson, Shane – Computers & Education, 2010
Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…
Descriptors: Network Analysis, Academic Achievement, At Risk Students, Prediction