周 晔 张刚要
（南京邮电大学 教育科学与技术学院，江苏 南京 210023）
【摘 要】个性化试题推荐能够帮助学生摆脱“题海战术”，是在线教育、个性化教育领域的重要研究课题。已有的个性化试题推荐利用知识关联规则与推荐算法来设计针对试题或知识单元层面的推荐策略，甚少提及知识关联本身，研究重心向算法实现和推荐系统设计方面倾斜。因此，本研究将知识关联思想纳入研究体系，对个性化试题推荐进行系统阐述，首先根据知识关联的类型与结构建立不同层级的关联关系，其次构建“知识单元—试题”二次推荐的个性化试题推荐概念模型，最后从认知诊断、薄弱知识单元定位、试题规律生成三部分对概念模型的实现机制进行理论剖析，以期给教育工作者和研究人员循证实践提供信息借鉴。
【关键词】知识关联；个性化；试题推荐
Research on Personalized Question Recommendation Based on Knowledge Association: Conceptual Model and Implementation Mechanism
ZHOU Ye and ZHANG Gangyao
(School of Education Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China)
Abstract：Personalized test question recommendation can help students in getting rid of “exercises-stuffed teaching method”, which is an important research topic in online and personalized education. The existing personalized question recommendation only used knowledge association rules and recommendation algorithms to design recommendation strategies at the level of test questions or knowledge units, and seldom mentioned knowledge association itself. Therefore, this paper incorporates the idea of knowledge association into the research system to systematically elaborate personalized test question recommendation. Firstly, establishing different levels of associations according to the type and structure of the knowledge association. Secondly, building a conceptual model of personalized test question recommendation based on the secondary recommendation of “knowledge unit - test question”. And finally, analyzing the realization mechanism of the conceptual model from cognitive diagnosis, localization of weak knowledge units, and generation of test questions in order to provide educators and researchers with information for evidence-based practice.
Keywords：knowledge relevance; personalized learning; question recommendation
下载：
基于知识关联的个性化试题推荐：概念模型及实现机制.pdf
