| 学习资源个性化推荐系统的学习者模型构建 |
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| 引用本文： | 田枫,李欣,刘芳,刘贤梅,王梅,张可佳,富宇.学习资源个性化推荐系统的学习者模型构建[J].教育教学论坛,2020(10):304-305. |
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| 作者姓名： | 田枫 李欣 刘芳 刘贤梅 王梅 张可佳 富宇 |
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| 作者单位： | ;1.东北石油大学计算机与信息技术学院 |
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| 基金项目： | 黑龙江省高等教育教学改革研究项目（SJGY20180079）;黑龙江省高等教育教学改革研究项目（基于虚拟仿真实验平台的教育技术学专业实验课程教学改革探索与应用）;东北石油大学研究生教育创新工程项目（JYCX_07_2018）;教育科学青年专项课题（GBD1317016）;黑龙江省哲学社会科学基金项目（19SHE280）;大庆市哲学社会科学规划研究项目（DSGB2019042） |
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| 摘 要： | 互联网的高速发展导致网络学习资源数量迅速增长,案例教学、理论教学等教学资源的个性化推荐受到更多关注。学习者模型是实现个性化推荐的依据。文章以CELTS-11学习者模型规范为基础,针对学习者的个性差异,在学习过程中对基本信息、学习风格、知识状态、认知能力、兴趣偏好等个性化特征展开研究,解决目前资源推荐系统的学习者模型中学习者特征描述不全面、个性化程度不高等问题,构建出了个性化的学习者模型,为学习资源的推送提供了有力的依据,应用效果表明了该方法的有效性。
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| 关 键 词： | 学习资源 个性化 推荐系统 学习者模型 |
The Learner Model Construction of Personalized Learning Resource Recommendation System |
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| TIAN Feng,LI Xin,LIU Fang,LIU Xian-mei,WANG Mei,ZHANG Ke-jia,FU Yu.The Learner Model Construction of Personalized Learning Resource Recommendation System[J].jiaoyu jiaoxue luntan,2020(10):304-305. |
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| Authors: | TIAN Feng LI Xin LIU Fang LIU Xian-mei WANG Mei ZHANG Ke-jia FU Yu |
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| Institution: | (School of Computer and Information Technology,Northeast Petroleum University,Daqing,Heilongjiang 163318,China) |
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| Abstract: | The rapid development of the Internet has led to a rapid increase in the number of online learning resources,and more attention has been paid to personalized recommendation of teaching resources such as case teaching and theoretical teaching.Learner model is the basis of realizing personalized recommendation,in this paper,based on CELTS-11 learners model specification,according to the learner’s individual differences,in the process of learning the basic information,learning style and knowledge state,cognitive ability,study interest preferences such as the personalized features,to resolve the resource recommender system learners model describing is not comprehensive,the learners do not have a high level of personal problems,construct,the personalized learner model for learning resource push provided the powerful basis,application results show the effectiveness of the method. |
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| Keywords: | network learning resources personalized recommended system learner model |
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