An Adaptive Intelligent Recommendation Scheme for Smart Learning Contents Management Systems

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 240)

Abstract

This study aims to provide personalized contents recommendation services depending on a learner’s learning stage and learning level in the learning management system using open courses. The intelligent recommendation system proposed in this study selects similar neighboring groups by performing user-based collaborative filtering process and recommends phased learning contents by using prior knowledge information between contents and considering the relevance and levels of learning contents. The proposed learning contents recommendation is applied flexibly according to a user’s learning situation and situation-specific contents recommendation link is created by performing the intelligent learning process of recommendation system. This service allows a variety of industrial classification learners using open course to effectively choose more accurate curriculum.

Keywords

Personalization Recommendation system Collaborative filtering E-learning Learner’s preference 

Notes

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2011-0014394).

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Copyright information

© Springer Science+Business Media Dordrecht(Outside the USA) 2013

Authors and Affiliations

  1. 1.Innovation Center for Engineering EducationMokwon UniversityDaejeonKorea
  2. 2.Division of Computer EngineeringMokwon UniversityDaejeonKorea
  3. 3.Center for Teaching and LearningHannam UniversityDaejeonKorea

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