Learning Activity-Based E-Learning Material Recommendation System

Along with the increasing development of Internet, it changes the life styles of human being. For example, the traditional learning styles are previously limited with the space and time, but the current learning activity places are shifted from the traditional classrooms to Internet gradually. The e-learning has become one of the important parts in digital life even it cannot substitute for the whole traditional teachings. In recent years, the technologies of data mining, such as the data clustering, decision tree learning and association rule, etc. are widely applied to the information industry. In addition, because that the e- learning gets more popular as well as the Internet technologies become more mature, if adopting the concept of data mining to e-learning system, it will be helpful to make learning more efficient. Thus, we plan to integrate the techniques of LDAP and JAXB to reduce the load of development of search engine and the complexity of content parsing. Additionally, through analyzing the logs of learners' learning behaviors, the likely keywords and the association among the learning course contents will be conducted or figured out. And then, we integrate with the metadata of the learning materials distributed in different platforms, and maintain them in the LDAP server. Based on the experienced behaviors of previous learners, it will be better for learners to efficiently navigate the e-learning course contents with such the assistance of suggestion of relevant contents.