文章基本信息

标题：Using algorithms for evaluation in web based distance education
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作者：Tuncay Sevindik ; Tuncay Sevindik ; Zafer Cömert 等
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2010
卷号：9
页码：1777-1780
DOI：10.1016/j.sbspro.2010.12.399
语种：English
出版社：Elsevier
摘要：Traditional assessment approaches are still being used in distance education environments. Positive changes have been experienced on dimensions of user, management and teacher in distance education systems at each passing day. In addition to these positive changes, new approaches to be used at the evaluation of distance education are emerging. Each of these approaches is an algorithm. In this study, the algorithms to be used at the evaluation of distance education platforms are analyzed and compared. Distance education algorithms as K-means, Apriori, C45, Support Vector Machines (SVM), KNN and Naive Bayes are created the universe and sample of this research. As a result, it is determined that which algorithms can be effective at analyzing of the student behavior, dimension of management and giving more impressive decision of the teachers.
关键词：Algorithm;Assessment;Distance Education;Evaluation