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Table 3 Predicting performance using SNA predictors by the end of course

From: How the study of online collaborative learning can guide teachers and predict students’ performance in a medical course

3.1 Final Grade (Model accuracy 41.6%)
Parameter Importance %
 Information centrality 26.71
 Eigenvector centrality 21.27
 Closeness centrality 12.69
 Eccentricity 11.67
 Out-degree 9.1
 In-degree 6.62
 Betweenness centrality 6.48
 Clustering 5.45
3.2 Clinical results (Model accuracy 51.9%)
Parameter Importance %
 Eigenvector centrality 40.85
 Clustering 24.25
 Betweenness centrality 23.10
 Closeness centrality 3.41
 Eccentricity 3.07
 Out-degree 2.82
 Information centrality 1.63
 In-degree 0.87
3.3 MCQ (Model accuracy 21.3%)
Parameter Importance
 Eigenvector centrality 39.62
 Information centrality 17.28
 In-degree 12.29
 Out-degree 10.22
 Closeness centrality 7.57
 Clustering 7.18
 Betweenness centrality 5.84