E-Learning数据挖掘:模式与应用

E-Learning Data Mining:Patterns and Applications

随着教育信息化的快速发展特别是数字化校园和网络高等教育的日益普及,教育领域中部署了众多的软件系统,在这些软件系统中存储着海量的教育数据。如何利用这些教育数据,使这些数据转变为信息、知识,并为教育决策、教学优化服务,可从E-Learning数据挖掘中找到一些答案。文章系统梳理了国内外E-Learning数据挖掘的研究进展,并采用格语法分析方法对"E-Learning"的关键要素和过程进行分析,提出可以"谁在学、学什么、怎么学、学得如何"这一系列问题为主线,开展E-Learning数据挖掘工作,从而获得对E-Learning现状的更加完整的认识。在尝试回答"谁在学、学什么、怎么学、学得如何"的过程中,分解出三类挖掘任务情境即用于回答"谁在学"的学习者特征挖掘,用于回答"学什么、怎么学"的学习过程挖掘以及用于回答"学得如何"的学习结果挖掘,并对应地构建出三种数据挖掘模式。对模式的应用结果表明,这三种数据挖掘模式在E-Learning要素和过程分析中是有效的,较好地拓展了对E-Learning关键要素认识的完整性,包括对"谁在学"有了更全面的认识、对"学什么、怎么学"有了更准确的认识和对"学习的结果如何"有了更深入的认识。

As educational informatization especially digital campus and online higher education develop rapidly, more and more software systems have been deployed and there stores massive educational data. How could we fully use the massive educational data and transfer the data into useful information and knowledge in order to make scientific educational decision and optimize instruction？ Maybe we could find some inspirations from E-Learning data mining. In this paper, the author reviews domestic and overseas literatures about E- Learning data mining and analyses the key elements and processes of E-Learning in the frame of case grammar. Then the author brings forward a new research route of E-Learning data mining which is constituted by a series of questions Who to Learn, What to Learn, How to Learn, How about the Learning Result. In this way, a much more integrated understanding about E-Learning could be acquired. For answering the questions above, the author puts forward three data mining task situation including learner characteristics data mining for answering Who to Learn, learning process data mining for answering What to Learn and How to Learn, and learning result data mining for answering How about the Learning Result. Correspondingly, the author constructs three E- Learning data mining patterns. The application of these three patterns shows that the patterns are effective in analyzing E-Learning elements and processes. And the information and knowledge acquired in the E-Learning data mining process of this paper extends the integrity of understanding about E-Learning, which includes more overall understanding about Who to Learn, more precise understanding about What to Learn and How to Learn and deeper understanding about How about the Learning Result.