A Knowledge-Based Teaching Resources Recommend Model for Primary and Secondary School Oriented Distance-Education Teaching Platform

  • Meijing Zhao
  • Wancheng Ni
  • Haidong Zhang
  • Ziqi Lin
  • Yiping Yang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)

Abstract

In distance education systems, the ranked list of resources is very important for learners and teachers to find useful resources effectively. Apart from user’s interest, the knowledge point of subject is a crucial factor for education system, especially for primary and secondary school oriented distance education. Much of the previous work are models based on recommender systems, however, these models considered only user’s interest, ignoring the crucial impact of subject knowledge. In order to improve the performance of recommender systems, we considered both the subject knowledge and user’s interest. To get this target, Latent Knowledge Model (LKM) is adopted. LKM is a knowledge-based and teaching task-oriented model. It enables subject knowledge resources through knowledge tree extended search strategy, and gets personalized resources through user feature mining strategy. LKM is realized on real data sets which are obtained from a popular distance education teaching platform. Recall and precision rate are used to evaluate the performance of our proposed method for resources recommendation tasks. Experimental results show that the LKM captures subject knowledge and personal preferences for resources selection, which yields significant improvement in recommendation accuracy.

Keywords

Distance education Knowledge tree Extended search User feature Recommender system 

Notes

Acknowledgments

We thank Dayong Wen and the subject experts for their helpful comments and suggestions about extracting subject knowledge nodes from the special subject.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Meijing Zhao
    • 1
  • Wancheng Ni
    • 1
  • Haidong Zhang
    • 1
  • Ziqi Lin
    • 1
  • Yiping Yang
    • 1
  1. 1.Department of CASIA-HHT Joint Laboratory of Smart EducationInstitute of Automation Chinese Academy of ScienceBeijingChina

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