A hybrid learning object recommendation algorithm in E-learning context

作者：Wan, Liyong^*; Zhao, Chengling

来源：International Journal of Digital Content Technology and Its Applications, 2012, 6(18): 442-448.

DOI：10.4156/jdcta.vol6.issue18.53

• Adaptive e-learning systems
• Content recommendations
• Content-based recommendation
• Learning objects
• Recommendation
• Recommendation algorithms
• Recommendation methods
• Recommendation precision

In adaptive e-learning system, the researchers focused on how to provide the learners with learning objects depending on their preferences and needs. This makes the process of filtering unwanted learning objects an increasing challenge for the learners. Content recommendation systems can suggest the users what they should learn. People have made great efforts on research about recommendation systems using content-based recommendation and collaboration-based recommendation. In this paper, the authors proposed a hybrid learning object recommendation method to improve the accuracy of the recommendation. The experiment result shows that recommendation precision of hybrid recommendation method is higher than content-based recommendation method and collaboration-base recommendation method.

• 出版日期2012
• 单位华中师范大学