PUMA publications for /user/jaeschke/dmhttps://puma.uni-kassel.de/user/jaeschke/dmPUMA RSS feed for /user/jaeschke/dm2024-03-29T05:45:48+01:00Educational data mining: A survey from 1995 to 2005https://puma.uni-kassel.de/bibtex/2746d12e92e58587461ffcb8dc381e283/jaeschkejaeschke2008-12-19T16:16:46+01:00data dm e-learning mining survey webzu <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="C. Romero" itemprop="url" href="/author/C.%20Romero"><span itemprop="name">C. Romero</span></a></span>, и <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="S. Ventura" itemprop="url" href="/author/S.%20Ventura"><span itemprop="name">S. Ventura</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>Expert Syst. Appl.</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">33 </span></span>(<span itemprop="issueNumber">1</span>):
<span itemprop="pagination">135--146</span></em> </span>(<em><span>2007<meta content="2007" itemprop="datePublished"/></span></em>)Fri Dec 19 16:16:46 CET 2008Tarrytown, NY, USAExpert Syst. Appl.1135--146Educational data mining: A survey from 1995 to 2005332007data dm e-learning mining survey webzu Currently there is an increasing interest in data mining and educational systems, making educational data mining as a new growing research community. This paper surveys the application of data mining to traditional educational systems, particular web-based courses, well-known learning content management systems, and adaptive and intelligent web-based educational systems. Each of these systems has different data source and objectives for knowledge discovering. After preprocessing the available data in each case, data mining techniques can be applied: statistics and visualization; clustering, classification and outlier detection; association rule mining and pattern mining; and text mining. The success of the plentiful work needs much more specialized work in order for educational data mining to become a mature area.Educational data mining