Web Usage Mining for a Better Web-Based Learning Environment

Web-based technology is often the technology of choice for distance education given the ease of use of the tools to browse the resources on the Web, the relative affordability of accessing the ubiquitous Web, and the simplicity of deploying and maintaining resources on the WorldWide Web. Many sophisticated web-based learning environments have been developed and are in use around the world. The same technology is being used for electronic commerce and has become extremely popular. However, while there are clever tools developed to understand online customers behaviours in order to increase sales and profit, there is very little done to automatically discover access patterns to understand learners behaviour on webbased distance learning. Educators, using on-line learning environments and tools, have very little support to evaluate learners activities and discriminate between different learners on-line behaviours. In this paper, we discuss some data mining and machine learning techniques that could be used to enhance web-based learning environments for the educator to better evaluate the leaning process, as well as for the learners to help them in their learning endeavour. KEY WORDS Data Mining, e-learning, Web Usage Mining, Learning Activity Evaluation, Adaptive Web Sites 1.