摘要： 结合首师大虚拟学习社区网络教学支撑平台，提出了一个基于联机分析技术（OLAP）的教学诊断与评价模型。文中使用DMQL语言给出了一个由学生、知识点、时间和认知技能4个维度构成的数据立方体，以及利用OLAP的上卷、下钻、切块和切片等技术实现对该数据方体进行数据挖掘的解决方案。提出的基于OLAP技术的数据挖掘方案，可以在教学诊断与评价中解决诸如判断学习者学习难点、了解学习者集体或个人的学习特征，以及获得学习者认知过程等问题，为实现因材施教的个性化教学和以学生为中心的自主学习提供支持与服务。

关键词: 诊断, 评价, 数据挖掘, 远程教育

Abstract: This paper presents a suggestion of the diagnosis and evaluation model that is based on on-line analytical processing (OLAP). The data are organized as a 4-dimension data cube, in which the 4 free variables are student, knowledge-point, time-point, and cognitive-ability. According to OLAP, this 4-D data cube can be managed by five kinds of data mining techniques, namely 'roll-up', 'drill-down', 'slice', 'dice' and 'pivot'. The paper describes, by using DMQL language, how to use these techniques to the diagnosis and evaluation process in the support platform of the virtual learning community of Capital Normal University. This kind of the diagnosis and evaluation model can solve many key problems such as judging the learning difficulties, obtaining the characteristics of the learner and learner group, and finding the cognitive process of the learner. Solving these problems can improve the learning system for the individuation education and the active learning manner.

中图分类号: 

• TP399