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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
Watson, John F. – North American Council for Online Learning, 2007
Online learning is growing rapidly across the United States within all levels of education, as more and more students and educators become familiar with the benefits of learning unconstrained by time and place. Across most states and all grade levels, students are finding increased opportunity, flexibility, and convenience through online learning.…
Descriptors: Definitions, Educational Resources, Student Evaluation, Educational Assessment