کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
349741 | 618235 | 2009 | 16 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Dropout prediction in e-learning courses through the combination of machine learning techniques
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کلمات کلیدی
موضوعات مرتبط
علوم انسانی و اجتماعی
علوم اجتماعی
آموزش
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
In this paper, a dropout prediction method for e-learning courses, based on three popular machine learning techniques and detailed student data, is proposed. The machine learning techniques used are feed-forward neural networks, support vector machines and probabilistic ensemble simplified fuzzy ARTMAP. Since a single technique may fail to accurately classify some e-learning students, whereas another may succeed, three decision schemes, which combine in different ways the results of the three machine learning techniques, were also tested. The method was examined in terms of overall accuracy, sensitivity and precision and its results were found to be significantly better than those reported in relevant literature.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Education - Volume 53, Issue 3, November 2009, Pages 950–965
Journal: Computers & Education - Volume 53, Issue 3, November 2009, Pages 950–965
نویسندگان
Ioanna Lykourentzou, Ioannis Giannoukos, Vassilis Nikolopoulos, George Mpardis, Vassili Loumos,