摘要
该研究通过梳理国内外个性化学习资源建设现状,提出利用学习者自我评价和FelderSilverman量表进行前测以检测学习者的学习风格,利用学习者在学习过程中的学习行为和学习路径等分析出隐性学习者特征,采用协同过滤技术和数据挖掘技术相结合的方法将学习者特征与在线学习资源相匹配,建构基于协同过滤和数据挖掘的在线学习资源个性化推荐服务模型并进行案例实践,以期为在线学习者特征的维度确立以及在线学习资源个性化建设等研究提供参考。
By understanding the status of personalized learning resources construction at home and abroad, the study presents the following ideas ： using the learner s self-evaluation and pre-test method of Felder-Silverman scale to test learner learning styles; using learners ＇ learning behavior in learning process to construct learners ＇ hidden characteristics, adopting the combination of collaborative filtering technology and data mining technology to match learners＇characteristics with online learning resources, and constructing personalized recommendation service of online learning resources mainly based on collaborative filtering and data mining and carrying out case practice. We hope to provide reference for studies on establishment of online learner characteristics dimension and construction of personalized recommendation service of online learning resources.
出处
《中国医学教育技术》
2017年第2期172-176,共5页
China Medical Education Technology
关键词
在线学习资源
个性化推荐
协同过滤
数据挖掘技术
online learning resources
personalized recommendation
collaborative filtering
data mining technology
作者简介
张小雪（1994-）,女,新疆伊犁人,硕士研究生在读,主要研究方向：教育技术基本理论,网络与远程教育.
通信作者：张立国（1965-）,男,陕西榆林人,教授,博士,主要研究方向：教育技术基本理论,网络与远程教育.电话：18629426083;E-mail：zhangliguok@126.com
