S. Crossley, M. Dascalu, D. McNamara, R. Baker, Stefan Trausan-Matu
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Predicting Success in Massive Open Online Courses (MOOCs) Using Cohesion Network Analysis
This study uses Cohesion Network Analysis (CNA) indices to identify student patterns related to course completion in a massive open online course (MOOC). This analysis examines a subsample of 320 students who completed at least one graded assignment and produced at least 50 words in discussion forums in a MOOC on educational data mining. The findings indicate that CNA indices predict with substantial accuracy (76%) whether students complete the MOOC, helping us to better understand student retention in this MOOC and to develop more actionable automated signals of student success.
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