@inproceedings{94ad3b1cabf5482eb2edf3da47db8994,
title = "Online learning style modeling for course recommendation",
abstract = "E-learning systems offer new ways of learning and change the approaches of delivering learning materials. In the face of massive instructional data, efforts should be made to help learners choose more suitable materials based on their level and preferences. In this paper, we proposed a model of online learning style which offers a comprehensive description of learners{\textquoteright} cognitive style and other abilities. Then, we introduce an enhanced method for course recommendation based on our learner model. Experiment results show that the enhanced method evidently outperforms traditional collaborative filtering method, while maintaining a computational advantage.",
keywords = "Adaptive learning, Course recommendation, Online learning style",
author = "Rumei Li and Chuantao Yin and Xiaoyan Zhang and Bertrand David",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2019.; International Conference on Intelligent Computing, Communication and Devices, ICCD 2017 ; Conference date: 09-12-2017 Through 10-12-2017",
year = "2019",
doi = "10.1007/978-981-10-8944-2\_120",
language = "英语",
isbn = "9789811089435",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "1035--1042",
editor = "Srikanta Patnaik and Vipul Jain",
booktitle = "Recent Developments in Intelligent Computing, Communication and Devices - Proceedings of ICCD 2017",
address = "德国",
}